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Gift vouchers at Lepo-Lepše. The perfect present for every occasion

There are many special situations and dates when you can make someone close to you happy with a gift. What better than a voucher for beauty care treatment at Lepo-Lepše antiaging centre?

Who is that person close to you?

Friend? Girlfriend? Boyfriend? Wife? Husband? Mum? Granny? Sister? brother? Neighbour?

What’s the occasion?

For new Year? For an anniversary? For Christmas or Easter? For a birthday? For graduation? For recovery after childbirth? For recovery after a long job or a journey? Or just to say you love them!

For all those loved ones and all those important dates, our GIFT VOUCHERS are a touching solution.

We have prepared gift vouchers with amounts tailored to the usual prices of our treatments:

  • BEAUTIFUL – 3,000 RSD
  • INFINITELY BEAUTIFUL – the amount of your choice

Choose which voucher suits you and contact us in any of the ways on the CONTACT page.

You can pay for gift vouchers by:

  • Cash
  • m-Banking
  • Cheques, in 3 installments
  • Credit/debit cards (Visa, MasterCard, Maestro, DinaCard, UnionPay)
  • Bank transfer


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Acrylic on canvas
Original Artwork

THICKETS COLLECTION - This series draws on the genre of landscape painting exploring themes of human need and interdependence.

The works depict not only an above ground view of colorful, abstracted objects reminiscent of plants and trees, but the complex network of interconnection below the surface, showing the intermingling of life forms that might otherwise appear independent.

This work was done during the COVID-19 pandemic, when our well-being was dependent on the behavior of strangers while we were simultaneously thrown into near constant contact with our immediate families. The pandemic highlighted our broad interdependence of the global community. I aspire to expose our intense human interdependency in these works.

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Challenging Fears

I’m the in clarity-seeking and courage-building phase of a major life change. And like any change, it’s scary. Especially in that wind-up to the actual leap. I’m very aware that I need to manage this anxiety around the transition, otherwise it will keep be stuck in the same place that is sending me clear signalsContinue reading “Challenging Fears”

Looking For a Challenge

Kazh’s training is progressing well. He’s super-responsive, wants to please his humans and hasn’t shown any signs of aggression. Based on observing him in many situations, our biggest obstacles are going to be building his confidence and working to moderate his tendency towards excited dominance behaviors. Yesterday, we loaded him up with a weighted packContinue reading “Looking For a Challenge”

In Perpetuity

“Mom, what does ‘in perpetuity’ mean?” I asked from the backseat as we drove by an intown San Antonio theater advertising Rocky Horror Picture Show Friday 10 pm  with the unfamiliar words posted beneath. “It means it keeps repeating, going on without end.” “So they show that same movie every Friday? That’s dumb,” I concludedContinue reading “In Perpetuity”


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Baby’s First Year Classes

Baby’s First Year is a 4-week long class that provides a comfortable and pressure-free environment to connect with others who are also learning to navigate the adventure that is parenting. Through the duration of this weekly course, you will gain practical advice, encouragement, the opportunity to discuss questions & concerns, all the while increasing your supports and confidence as a parent.

You’ll cover topics including:

  • Family & emotional adjustments
  • Physical development
  • Food & nutrition
  • Goal setting
  • Common infant illness
  • Parenting styles and more

Classes are available three times a year.

Next session starts on September 13, 2022!

Classes will be held in person at the LPCC's newly renovated classroom space downtown. Alberta Health Services recommendations will be followed, including cleaning and sanitizing.

Contact us for more information, (403) 942-1819.

Register for the next available session!

Are you currently an LPCC client?(Required)
Note: We are only able to offer programs and classes to current LPCC clients. If you would like to become a client please give us a call to discuss if our services are a fit for your needs, (403) 942-1819.
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Event Schedule

Leather History Preservation Weekend

2022 Schedule

This may serve as a useful rough draft for your
Trip Through History

Because of travel, family, medical and other issues may arise,

 Schedule is subject to change

FRIDAY - November 4, 2022

SATURDAY - November 5, 2022

SUNDAY - November 6, 2019

Back to the Weekend         Meet our Keynote          Back to Historians


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Crew list of Ships hit by U-boats

Hercules Scott Findlay

RNR. British

Born   1902
Died  11 Dec 1941(39)

Roster information listed for Hercules Scott Findlay

ShipTypeRank / roleAttacked onBoat
HMS RosabellePatrol yachtLieutenant11 Dec 1941 (+)U-374

Personal information

Son of Robert and Jane Reid Findlay; husband of Isabella Margaret Findlay, of Rutherglen, Lanarkshire.

Crew list for Ships hit by U-boats


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Project Management: PMGT 430 Advanced Project Management

Click on the tabs below for resources on this subject.

Quick Links

Suggested Resources

The library provides various types of resources to support PMGT430.  The links below will connect you to eBooks from the library collection and journal articles from the library databases.  Relevant streaming videos from both the library databases and the Internet are also listed, as well as useful websites. Click on one of the links below to access these resources. You will be prompted for your BU Connect login if you are off-campus.

Books from the General Collection
These print books may be checked out.

These electronic books can be accessed directly from this LibGuide by clicking on the title.

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Videos from library databases, as well as those freely available on the web, are included. Most are embedded and may be played directly from this LibGuide.

Useful websites are listed. See the Websites tab on this LibGuide to see many more websites related to Project Management.

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Film and Video Studies: Home

Resources for the study of film.

At a Glance: Locating Materials for Your Research

Search URSUS by keyword, author, subject, title, etc. for materials of interest to your research need(s). URSUS is the online library catalog for all libraries in the University of Maine system, plus Bangor Public Library, Maine State Library, Maine State Archives, and Maine State Law & Legislative Reference Library.

Interested in what libraries in other parts of the state, country, and around the world, have to offer on your topic?

Search MaineCat, the online catalog for libraries across the state.

You can also search WorldCat, an online catalog of materials held by over 72,000 libraries worldwide.

Place an Interlibrary Loan request for materials that we don't own. We will request material(s) from other libraries on your behalf.

Filming in Maine

Welcome to the Guide for Film Studies

In this guide, you will find print and digital resources related to film studies.

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how to do seo optimised copy

How do you optimize copies for SEO?

5 important tips to optimise your copywriting for SEO
Get your keywords into the copy while ensuring density and placement is right. .
Write an optimised page title and meta description. .
Include external and internal links. .
Ensure your text is clear and easy to read. .
Include a relevant and effective call-to-action.

How do you do SEO copywriting?

SEO Copywriting Tips For Better Rankings
Choose A Realistic Keyword Goal.
Analyze The Top-Ranking Content.
Understand And Write For Search Intent.
Outline Your Structure.
Prioritize Quality Over Everything Else.
Explore Your Topic In-depth.
Write For Passage Ranking.
Use A Content Optimization Tool.

Is SEO important for copywriting?

SEO copywriting is crucial for every business, but especially for those in the eCommerce space. To beat your competitors, you need copy that not only motivates your consumer to purchase but also gets your products seen before others.

Which is better SEO or copywriting?

Copywriting is slightly different to SEO content with the key difference being the overall goal. While SEO content is created to educate users and increase rankings, the main purpose of copywriting is to take readers to the next step and convert traffic into leads and, eventually, sales.

Is SEO and copywriting same?

You could say that both types of writing are optimized to meet the reader or consumer where they areSEO writing meets them on a webpage, while copywriting may meet them on a TV commercial, printed ad, or the product labeling.

What does SEO copywriting mean?

SEO copywriting is the process of pairing standard SEO best practices that drive traffic (like keyword research) with compelling words that entice users to take a specific action, like buying a product or subscribing to an email list.

How dofind SEO keywords?

Step 1: Make a list of important, relevant topics based on what you know about your business. .
Step 2: Fill in those topic buckets with keywords. .
Step 3: Understand How Intent Affects Keyword Research and Analyze Accordingly. .
Step 4: Research related search terms. .
Step 5: Use keyword research tools to your advantage.

How docreate SEO content?

SEO Content Strategy
Make a list of topics.
Make a list of long-tail keywords based on these topics.
Build pages for each topic.
Set up a blog.
Create a consistent blogging schedule.
Create a link-building plan.
Compress media files before uploading them to your site.
Stay up-to-date on SEO news and best practices.

What are keywords for SEO?

Keywords are ideas and topics that define what your content is about. In terms of SEO, they’re the words and phrases that searchers enter into search engines, also called “search queries.” If you boil everything on your page  all the images, video, copy, etc.

How much do SEO copywriters make?

Salary Ranges for Seo Copywriters

The salaries of Seo Copywriters in the US range from $10,376 to $185,270 , with a median salary of $33,840 . The middle 57% of Seo Copywriters makes between $33,840 and $83,938, with the top 86% making $185,270.

How do you write SEO examples?

SEO Content Writing  10 Simple Tips (Plus Examples)
Write Enticing Page Titles and Descriptions.
Use Headings and Subheadings.
Use Appropriate Keyword Density (and LSI Keywords)
Use Internal and External Links.
Answer User Search Intent.
Use a Simple URL.
Use Bullet Lists.
Include a Call-to-Action.

What type of content is best for SEO?

Here are the types of content that are best for SEO.
Authoritative Blog Posts. In a world where content is a top ranking factor, it’s but normal for a website to have its own blog. .
Infographics. .
Videos. .
Trending Content. .
How-To Guides. .
Lists. .
Extra Resources for SEO Content.

What are the 4 types of keywords?

When researching to discover a user’s intentions behind making a search, we can classify all keywords into four main categories of intent: commercial, transactional, informational, and navigational. We’re going to identify what these types are with a short breakdown of each type.

How many keywords shoulduse for SEO?

It’s much more likely that you’ll want to target two or three keywords per page, even if they’re just close variations. Any more than four is a bit crowded; after all, each page only has one title tag and meta description. With a range of keywords per page determined, we can estimate how many keywords we’ll track.

What are the different SEO techniques?

12 Types of SEO
White-Hat SEO. When you hear someone say white-hat SEO, that means the SEO practices that are in-line with the terms and conditions of the major search engines, including Google. .
Black-Hat SEO. .
Gray-Hat SEO. .
On-Page SEO. .
Off-Page SEO. .
Technical SEO. .
International SEO. .
Local SEO.

How docreate a keyword list?

How to Build a Keyword List
Step 1: Identify Your Target Audience. .
Step 2: Brainstorm. .
Step 3: Review Your Log Files. .
Step 4: Research and Analyze the Top Ranked Sites. .
Step 5: Research and Analyze Your Direct Competition. .
Step 6: Employ Google AdWords Keyword Tool. .
Step 7: Employ Other Keyword Sources.

Which keywords are best to target in SEO?

Long tail keywords are long (usually 4+ word) terms that searchers use in Google and other search engines. And they tend to have a lower keyword difficulty compared to 1-3 word head terms. So for people that are new to SEO, long tails are usually the best keywords to start with.

Is SEO a good career?

‘ Yes. SEO is a good career option as it is among the most sought-after careers in the Digital Marketing field. There are several organizations around the world, hiring SEO professionals to generate better content and hence produce more business leads.

Is SEO writing profitable?

A well-optimized content will make it easier for your blog to appear on Google and other search engine results. Thus, the market demand for SEO freelance writers is enormous. So if you’re an SEO freelance writer, you’re in a profitable niche. Businesses will pay you more to write content that ranks higher on Google.

How much shouldcharge for a 500 word blog post?

All things considered, 500 words is a fairly short article length, appropriate for a short newsletter article or personal profile. A typical rate for this would be $


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With age, the elasticity of the lens decreases, which also reduces your refractive power.
This mechanism, which is physiological in old age, results in presbyopia (in technical terms also Presbyopia called).
It is characterized by the fact that it is difficult to see close up. Reading small letters is particularly difficult.

Presbyopia is a normal process that affects everyone as they age. It starts around the age of 40. The term presbyopia is actually wrong, as there is no farsightedness in the original sense. With farsightedness, namely, the eye is too short. The increasing weak eyesight in old age has other causes.

The lens becomes less elastic over time and is less able to roll off. Thus, the refractive power decreases and things that are close to the eye can no longer be seen clearly. The only remedy is reading glasses.

Presbyopia is a slowly progressing process that is completely physiological, i.e. normal, and is part of getting older.

Cause of presbyopia

The eye is composed of many individual components.
For sharp vision and its pathomechanism (Mechanism that brings about a disease and by which the development of the disease can be explained) the interaction between lens and cornea is primarily responsible.
The lens is part of the visual system of the eye. It is biconvex (arched outwards on both sides) and consists mainly of proteins and water. By changing its curvature, the refractive power can be changed so that objects near or far can be seen clearly.
This mechanism is known as accommodation.To see sharply up close (for example when reading) the lens loops. This balling with increasing curvature is based on the inherent elasticity of the lens.
In order to see in the distance, the lens is stretched in length and width by fibers attached to it, i.e. flattened. The lens is nourished and supplied by the aqueous humor surrounding it, which is located in the eye around the lens. The lens has no blood vessels and is completely colorless and transparent.

In the case of presbyopia or farsightedness, this balling process is now hindered or restricted. The more elastic the lens, the greater the increase in lens curvature. This elasticity is lost with age and thus leads to so-called presbyopia.
The rigid core of the lens becomes larger, which takes place at the expense of the soft cortex. So the ability to accommodate continues to decline. This process begins at birth, but progresses slowly. The presbyopia only becomes noticeable above a certain narrow range of the ability to accommodate. This process can be identified from around 40 to 50 years of age. People with farsightedness at a younger age notice this process earlier.

When does presbyopia begin?

The refractive power of the eye decreases continuously in the course of life. Presbyopia is the poor eyesight that results from the reduction in the elasticity of the lens.

From the age of 40, the reduction in elasticity manifests itself as poor eyesight: the patient can suddenly no longer see objects clearly near them. From this age onwards, the poor eyesight also increases rapidly. Up to the age of 55 it increases faster and faster, after that less quickly.

Here, too, one must bear in mind that the values are variable for each individual person and that the symptoms of presbyopia do not appear in everyone at the same age.

Presbyopia manifests itself primarily in the fact that the affected patients have more and more difficulties reading.
With the onset of presbyopia (presbyopia) reading is perceived as exhausting. The text to be read must be kept further and further away from the eye in order to be seen clearly. When reading for a long time, a dull feeling of pressure can develop in the forehead or eyes area, and sometimes lead to headaches.

Read more on the topic: Eye pain.

Diagnosis of presbyopia

Presbyopia is diagnosed (Presbyopia) mostly about the complaints expressed by the patient when reading. If the eye doctor then checks the eyesight, defects in near vision are found.

What tests are used to diagnose presbyopia?

Presbyopia can be determined by an optician using normal eye tests. The optician first lets the patient read something from a newspaper or book as normal. The posture that a patient with presbyopia adopts provides some important clues about the disease: he stretches his arms as far away from the body as possible, while at the same time pushing his head back. This increases the distance between the eye and the reading.

After this orientational assessment, the optician determines the eyesight using eye charts and glasses of different strengths. It works in the same way as a normal eye test at an optician's: The patient is put on test glasses and is supposed to read letters from a certain distance. As soon as he can no longer read something, the optician changes the glasses until reading is again possible without any problems. In this way, it determines the patient's diopter, i.e. the individual refractive power of the eyes. The diopter value also provides information about the strength of the lenses in order to be optimally adapted to the patient.

How many diopters does the refractive power of the eyes deteriorate in presbyopia?

How many dioptres the refractive power changes in presbyopia cannot be said in general terms. Rather, it is an individual value that is different for each patient. Presbyopia becomes symptomatic at the age of 40.

In the beginning, an additional diopter is usually sufficient to increase the refractive power. In the course of time, however, the elasticity of the lens decreases more and more quickly. From the age of 40, the elasticity of the lens decreases exponentially. This means that at the age of 50 the patient still needs 2 additional dioptres of refractive power in order to see clearly in the vicinity.

However, these values must be determined individually by the ophthalmologist or optician, as they can deviate considerably from these guide values.

Therapy of presbyopia

Presbyopia can only be treated with reading glasses. The glasses of the reading glasses are so-called converging lenses. So they are curved outwards on at least one side, sometimes on both sides (convex).
Outwardly curved lenses concentrate the incoming light rays. Thus, they help the patient with presbyopia to compensate for the inability of the lens to roll off. These glasses bundle the rays before they hit the lens of the eye. They also help the “decrepit” lens to see close up sharply.

Find out more about the topic here Glasses.

Laser therapy for farsightedness

Not so long ago, a laser treatment for presbyopia, as has been possible for some time with other disorders of accommodation, was not crowned with success Presbyopia a decrease in elasticity of the lens is the cause of the decreasing ability of the eye to focus.

But now, in Germany too, patients with presbyopia are being treated using laser procedures. In most cases, these are still studies in which experience is to be gathered and long-term results are to be made available, so that the current state of knowledge at the national level does not yet allow any statement to be made about the long-term success of laser surgery in presbyopia.

Read more on the topic: Have presbyopia lasered.

Contact lenses for presbyopia

As a rule, the therapy of choice for presbyopia (Presbyopia) first of all reading glasses. It is a pair of glasses with converging lenses that compensate for the lack of accommodation capacity of the eye lens due to a loss of elasticity as well as possible.

But contact lenses are also a way to remedy visual impairment.

Both patients who were previously normally sighted and those who were previously farsighted or also nearsighted can counter presbyopia with contact lenses.
The required diopter values must be specially calculated in each case.

Otherwise, the same applies to wearing contact lenses in presbyopia as in all other accommodation disorders: It is important to find the right lens and to maintain hygienic handling so that wearing it remains comfortable and the eyes are not damaged.

If the presbyopia still progresses, the contact lenses have to be readjusted every now and then, if the person concerned notices that he is having difficulty seeing up close again.
However, this does not happen quickly, but usually rather slowly, so that a readjustment all (pair) Years is often sufficient.

As for the choice between hard and soft contact lenses, it is up to the person concerned.
Both types of contact lenses can help with normal presbyopia, so it is a personal decision which contact lens suits you better and is more comfortable to wear.

What should you watch out for with contact lenses and presbyopia?

Anyone who suffers from presbyopia but does not want to wear glasses can have contact lenses made by the optician. These contact lenses differ from conventional contact lenses in that they must enable the reader to see clearly both in the distance and up close. So you have to meet the same conditions as a progressive lens.

The most commonly used models are so-called monovision lenses. With this lens system, one eye is corrected into the distance and the other nearer. That sounds irritating at first, but the brain is only able to adjust to close-ups or television.

Other types of lenses are built according to the progressive lens system: the upper part of the lens is designed for near vision, the lower part for far vision. It is important with this lens system that the lenses can slide easily on the eye and that their position does not change. You also have to get used to using these lenses first.

It is best to discuss which lenses are best for you with your eye doctor or optician.

What is a lens implant?

A lens implant is an artificial lens that can be inserted into the patient's eye in the event of lens opacification or gross ametropia (caused by the lens). There is also the option of removing the old lens. This is the case with lens opacification. If you have poor eyesight, you can leave the old lens in the eye. Then the new one is also used.

In the case of presbyopia, multifocal lenses are recommended. These lenses have two focal lengths: one for near vision and the other for far vision. They enable the patient to read without reading glasses.

There are also so-called accommodating intraocular lenses. These imitate the refraction of the lens of the eye, and thus also replace reading glasses.

Rehabilitation is unfortunately not possible, as the lost elasticity of the lens cannot be regained. A certain amount of reading glasses can help.

Which eye training helps against farsightedness?

It is questionable whether regular eye training can really prevent presbyopia or reduce its symptoms. Presbyopia is caused by a stiffening of the eye lens, which occurs naturally in old age. You can't really do anything about this stiffening. Eye exercises may help insofar as the movement promotes blood flow to the entire eye and thus also to the lens. As a result, the lens is better supplied with nutrients and remains more elastic. However, the benefits of eye training have not been scientifically proven. You have to decide for yourself individually whether eye training really helps.

Below are some specific eye exercises.

  • Close your eyes and let your eyeballs circle in all directions.
  • Extend your arm forward and bring it back towards your body. Fix your thumb with your eyes. This exercise trains the eyes to react and adapt quickly to different distances.
  • Change your gaze frequently between near and distant objects.

Nothing can be done preventively with this disease. This process is age related and cannot be stopped.
The loss of elasticity cannot be counteracted to this day. The lens loses its ability to loosen up a little more every day from birth. Fortunately, this continuous progress is only noticeable late. In a patient with normal vision, the decreasing elasticity only affects everyday life from the age of 45.

However, you can get used to some behavior to keep your eyes fit in everyday life.

  • Healthy nutrition - it promotes regenerative processes in the eye.

  • Regular eye training - keeps the eye muscles fit.

  • Watch TV or work on the computer in moderation (if possible). The artificial light from electrical devices has been proven to be harmful to the eye. In addition, the constant stare at a screen from the same distance rusts the eye muscles.

Is there a connection between presbyopia and diet?

It is controversial whether there is actually a connection between diet and the extent of presbyopia. There are sources claiming that certain vitamins and trace elements, taken in sufficient quantities, can reduce or delay presbyopia. However, this theory has not been scientifically proven. Nevertheless, a balanced diet promotes health and has a positive effect on regenerative processes in muscles, tendons and, last but not least, in the brain, which enables visual perception at all.

What role do vitamins play in presbyopia?

Since the development of presbyopia is a natural process, it can only be stopped to a limited extent, but never completely. There are certain vitamins that are responsible for the regeneration of certain antioxidants in the lens. These antioxidants are responsible for removing radicals in the eye that would otherwise damage the lens tissue.

The vitamins responsible for this are called lutein and zeaxanthin. They are mainly found in carrots, spinach, cabbage, Swiss chard and other leafy vegetables.

The effect of homeopathic remedies on presbyopia has not been scientifically proven. For this reason, we cannot recommend any specific homeopathic remedies. If you believe in homeopathy, you can discuss the subject with your alternative practitioner.

Presbyopia (Presbyopia) is a slowly progressing and actually normal aging process of the eyes which is based on a loss of elasticity Eye lens is based.

In this respect, it can be said about the prognosis of presbyopia that as a rule no regression or improvement pre-existing symptoms occur unless they go beyond the normal extent of the aging process.

In general, however, the inability to accommodate to close proximity does not increase indefinitely but comes to a halt sooner or later.

Most older people live with farsightedness around +1 to +3 diopters.
In a person with previously healthy eyesight, presbyopia begins at around 45 yearsto slowly become noticeable. For example, the newspaper or book must be held further away so that it can be read clearly.

After a certain age, practically everyone needs one Reading glasses or one other correctionthat helps with the close-up focus that the eye can no longer manage on its own.


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Inflammation of the shoulder blade

In the area of the shoulder blade (scapula) there are various structures, such as tendons, ligaments, muscles or joints, which can be inflamed. Bursa located in the shoulder are also often the trigger for inflammation of the shoulder blade.

You can find detailed information on the topic here: Inflammation in the shoulder

Inflammation on the shoulder blade can result from improper loading and long-term wear and tear. One cause is calcium deposits that develop in the bursa and on the tendons that run through them, so-called calcified shoulder.

Also, conditions like gout or rheumatoid arthritis can cause inflammation of the shoulder blade. Another group of patients are those who suffer from inflammation due to excessive or improper stress at work (e.g. painter) or sport (e.g. tennis or volleyball). However, infections of the bursa or other soft tissue structures with bacteria in the should not be ignored

Get an overview of the causes of shoulder blade pain here: Shoulder blade pain - these are the causes

Inflammation of the shoulder blade due to tendinitis

A common problem with the shoulder is inflammation of one of the rotator cuff tendons. The rotator cuff is made up of 4 muscles that form a common tendon cap that encompasses the shoulder joint. Due to long-term incorrect or overstressing, calcification and inflammation of the tendon and the bursa occur. This leads to a narrowing of the affected tendon and exacerbates the symptoms.

Read more on the topic: Inflammation of the rotator cuff

Patients experience pain and mobility restrictions, especially when the muscle to which the tendon belongs is tensed. This is also known as impingement syndrome. In most cases, such an inflammation of a tendon does not heal by itself, but requires therapy consisting of exercises to be performed by yourself and therapeutic support.

Everything about the topic of impingement syndrome can be found here: Impingement Syndrome

Appointment with a shoulder specialist

I would be happy to advise you!

Who am I?
My name is Carmen Heinz. I am a specialist in orthopedics and trauma surgery in the specialist team of .

The shoulder joint is one of the most complicated joints in the human body.

The treatment of the shoulder (rotator cuff, impingement syndrome, calcified shoulder (tendinosis calcarea, biceps tendon, etc.) therefore requires a lot of experience.
I treat a wide variety of shoulder diseases in a conservative way.
The aim of any therapy is treatment with full recovery without surgery.
Which therapy achieves the best results in the long term can only be determined after looking at all of the information (Examination, X-ray, ultrasound, MRI, etc.) be assessed.

You can find me in:

  • Lumedis - your orthopedic surgeon
    Kaiserstrasse 14
    60311 Frankfurt am Main

Directly to the online appointment arrangement
Unfortunately, it is currently only possible to make an appointment with private health insurers.I hope for your understanding!
You can find more information about myself at Carmen Heinz.

Nerve-related inflammation of the shoulder blade

Various nerves run along the shoulder blade area. Bad posture, e.g. at the desk, they can become irritated and inflammation can develop. This becomes noticeable through pain sensations radiating into the arms or the back or through pain sensations localized in the shoulder.

A special problem of an irritated nerve on the shoulder blade is the incisura scapular syndrome of the suprascapular nerve. This is the nerve that supplies important parts of the rotator cuff. This nerve runs through a bottleneck on the shoulder blade (Incisura scapulae). In different cases it can lead to a ossification come this bottleneck. Then symptoms arise like a tendon injury of the rotator cuff or an inflammation of this nerve.

The typical symptoms are severe and sharp pain in the area of the affected shoulder blade. These occur during movements that load or move the shoulder, e.g. at work or during sports.
If the inflammation of the structure on the shoulder blade is more advanced or more pronounced, then pain can occur even with less stressful movements or even at rest.
The inflammation also shows a restriction in mobility.
In addition to the pain (dolor) and restricted mobility (functio laesa), there are other typical signs of inflammation. These include overheating (calor), redness (rubor) and swelling (tumor).

The diagnosis can be made clinically by an experienced doctor using a combination of symptoms, such as pain, restricted mobility or swelling. The diagnosis can also be confirmed by ultrasound, X-ray or, in exceptional cases, by an MRI.

Read more on the topic: Pain between the shoulder blades

The treatment of inflammation on the shoulder blade is based on anti-inflammatory and pain-relieving medication with e.g. Ibuprofen or diclofenac. In an acute situation, if there is inflammation on the shoulder blade, rest and rest can often help. As a result, ongoing inflammations often subside.

If the inflammation does not regress or if there is a chronic process, then there should be no permanent relief of the shoulder if possible, as this can lead to increased movement restrictions and muscle loss.
The use of shock waves and ultrasound can also be used as therapeutic agents to treat inflammation. The use of cold is helpful in both acute and chronic processes, as it slows down the inflammatory processes and, on the other hand, relieves pain.

Find out more about the anti-inflammatory drugs here:

  • Ibuprofen
  • Diclofenac

The application of heat is rather counterproductive in active inflammation. The warmth increases the blood circulation and the inflammation is further intensified. The swelling would also increase as more fluid would accumulate due to the heat. If there is inflammation on the shoulder blade, it is better to resort to cold.

TENS (transcutaneous electrical nerve stimulation) can help with inflammation of the shoulder blade by inhibiting the transmission of pain signals. In itself, TENS does not reduce inflammation. However, by reducing the pain, the chronic use of pain relievers can be minimized.

You can find more information about TENS at: Electrotherapy

The duration of an inflammation can persist within days to weeks in the case of an acute cause and heal promptly with adequate treatment. If the cause is of a chronic nature, inflammation on the shoulder blade can drag on for months and years.


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How to Post Attendance

Here are the steps to posting attendance for your Life Group each week:

If you want to make changes to your roster or group, you can fill out this short form, or email [email protected]

1. Go to, and click on Login

2. Log in with your Username and Password
(You were emailed a username – if you’ve forgotten your password, click the link to reset it).

3.  Once you’re logged in, click on Leader Toolbox

4.  Click on the name of your group.

5. You should see everyone listed on your roster. Click the Take Attendance to record attendance.

6. Click on the Add New Date button.

7. There are three steps to your attendance.

  • Click on the date box and calendar will pop up. Click on the date your group met.
  • Add any notes about your meeting – notes, group changes, prayer requests, etc.
  • Check off anyone that attended your group.
  • SUBMIT! And you’re done!


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Let’s just skip to Christmas (Or: Kruidnoten spotted!)

Marco spotted some kruidnoten (Wikipedia) by the local Albert Heijn today. If you’re keeping track, today is 31 August. Traditionally they appear in the grocery stories by 1 September, although we spotted them on 23 August back in 2018. So we seem to be on track this year.

Flavored kruidnoten are also available already. Caramel sea salt, white chocolate, truffle, stroopwafel…
And some speculaas

Marco was sweet and bought some gevulde speculaas (Albert Heijn recipe) for us. It is speculaas cookies filled with almond paste. Yum yum yum.

Of course you can’t blame anyone for wanting to skip to Christmas (and New Year’s, and 2021…) in these crazy times. Give me a shout when you put up your Christmas tree. Good riddance to 2020, I say!

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Jackpot July!

The Great Wahuhi here by dubs this month… Jackpot July and Spirit agrees! It is like winning the jackpot of life. So many good things manifest and most importantly we see our own personal growth and are truly moving forward. A great awakening within!

Many Blessings,

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6 thoughts on “Meanwhile in Oklahoma 10.27.20

    • The worst ice storm I’ve lived through. Still possible problems due to strong winds tonight which could take out tree limbs weakened by ice that could come crashing down and take out power lines.

      • We are OK in our little piece of OK. Thanks for the concern. The newspaper this morning reported still over 200,000 without power around the state. The yard looks like hell. But no one is in the hospital and no one has perished in our household.

      • Climate change is real. The only argument is how much is caused by people vs natural cycles. I am in the natural cycles camp and believe humans have made the situation worse.

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Lavender and oranges take you into a dreamlike summer. The gentle warm scent of lavender and orange essential oil relaxes your skin and senses.

100% nourishing plant power without water additives.

The main ingredient of our palm oil free bath chocolate is precious cocoa butter.

The special recipe with organic coconut oil, organic argan oil and essential oils pampers you incredibly intensively. Break off 1-2 pieces and melt in warm bath water. The precious vegetable oils are distributed in warm bath water and are absorbed into the skin.

Theobroma cacao seed butter, coconut nucifera oil, argania spinosa kernel oil, lavandula angustifolia flower extract, ginkgo biloba leaf extract, citrus aurantium dulcis flower extract, flavor, d-limonene, geraniol, linalool, citral, citronellol.

Made from natural essential oils.


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In line with the Paris Agreement and the United Nations sustainability goals, i.e., the development and implementation of a sustainable energy system including a phase-out of fossil power plants, the share of renewable energy sources (RES) in the global energy mix has already risen significantly in the past years and continues to grow steadily (United Nations 2015). Despite decreasing carbon dioxide emissions, the increasing share of RES also poses several challenges: On the grid level, the inherent intermittency of RES leads to challenges for grid stability and requires cost-intensive congestion management (Rausch et al. 2019). In Germany alone, these circumstances yielded costs of € 1.5 bn in 2018 for redispatch interventions (Bundesnetzagentur 2019). Ultimately, as both electricity grids and electricity demand have not yet been adjusted to the new generation structure of high shares of RES, the intermittent electricity supply of RES can ultimately not be optimally used within the system (Linnemann et al. 2011; Nieße et al. 2012). This demonstrates an increased need for flexibility, referring to the ability to balance electricity demand and supply at short notice to ensure grid stability and the successful integration of RES (Heffron et al. 2021; Palensky and Dietrich 2011).

Moreover, on the level of individual plant operation, a major challenge of RES consists in the highly volatile and even negative electricity prices (Fanone et al. 2013): Increasing the uncertainty of (future) income of RES-plant operators, such price characteristics directly challenge a viable operation of existing RES-plants and pose a possible barrier to further investments in new RES-plants.

Hence, research and practice intensively consider different possibilities to tackle challenges related to RES’ intermittency: Among others, corresponding flexibility technologies comprise batteries, sector-coupling, grid expansion, and demand response (Heffron et al. 2020; Lannoye et al. 2015). Furthermore, research in the field of energy economics already discusses the approach of a local integration, i.e., the possibility to supply local flexibility by converting excess electricity on-site into goods, e.g., hydrogen, that may be stored or then sold on other non-electricity markets (Glenk and Reichelstein 2019; Hosseini and Wahid 2016).

With respect to the development of a sustainable energy system with sufficient flexibility, research reflects the crucial role of Information Systems (IS), constituting the fields of Energy Informatics (EI) and Green IS (Buhl and Jetter 2009; Goebel et al. 2014; Watson et al. 2010). In this context, there exists a wide-ranging research stream dealing with the energy consumption of data centers (DC) and with the question how DCs can be designed more efficiently (Beloglazov et al. 2011; Pedram 2012). This includes (technical) literature concerning an efficient DC operation and a corresponding design. Moreover, this research stream also includes conceptual literature that elaborates on benefits of using DCs for the whole electricity system, e.g., by supplying flexibility through a participation in Demand Response (DR) programs. Another example relates to a spatial distribution of DCs and corresponding flexibility (Klingert 2018; Shi et al. 2016). In this context, Fridgen et al. (2017) discuss the idea of utilizing spatially distributed DCs to effectively supply flexibility by spatial load migration of computational power. Moreover, related literature already introduces the local combination of DCs and RES-plants (Ahmad et al. 2019; Goiri et al. 2013). However, this literature puts DCs at the core of research and mainly aims for lowering the electricity bill and the carbon-footprint of a DC. Thus, it lacks the ability to address the challenges of the development of a sustainable energy system with respect to a viable future operation of RES.

As highlighted above, to address the challenges of future energy systems, research needs to focus on an appropriate implementation and operation of RES-plants. Hence, – and in contrast to existing literature on DCs – our work puts the RES-plant at the core of our research and reflects on energy-intensive DCs as a means to contribute to a viable operation of and investment in RES-plants. We note that there are first companies, e.g., WindCORES, which integrate RES-plants and DCs in reality. However, the RES-plant and the DC are predominantly not operated by the same company (Moss 2018), while the theory behind these first real-world examples is still missing. So far and to the best of our knowledge, research does not consider the approach of a local integration of RES-plants and electricity conversion into computing power (with respect to an IS-application) with the aim of increasing the economic viability of an RES-plant operation. Hence, we pose the following research question in the light of EI:

How can the integration of an intermittent RES-plant and a computationally intensive, energy-consuming DC yield an increased Net Present Value compared to a stand-alone RES-plant?

In line with Gholami et al. (2016), our paper constitutes application-oriented IS research that addresses the two challenges, namely the need for additional flexibility in the future electricity system and an economically viable operation of RES-plants. Hereby, we refer to the concept of integrated energy systems (IES), in general consisting of at least two plants, one of which is an energy consumer and the other an energy supplier (Bai et al. 2016). Following Bai et al. (2016), who provide an optimization model for an operation of gas-electricity IES, in this paper we analyze the impact of an IES – consisting of an RES-plant and a temporally flexible DC application – on the economic viability of an RES-plant using two exemplary use-cases. Within our IES, the RES-plant generates electricity that may either be sold on a corresponding electricity market or consumed locally within the IES by the DC. We reflect that an increasing Net Present Value (NPV) of the RES-plant within an IES may lead to increasing investments in RES-plants, and can, therefore, be considered as a means to promote new RES-plants.

We note that the NPV of the IES can be increased by a variety of use-cases for the integrated plant, ranging, e.g., from (training) Machine Learning (ML) algorithms by cloud-computing DCs to (computerized) batch production of physical goods. However, we are also aware of the fact that the production of physical goods may be associated with a higher complexity when compared to a DC use-case. To illustrate the applicability of our approach, we therefore evaluate it with real-world data for two use-cases: While also providing the basis for future research in the context of IESs, in this paper we exemplarily reflect an integrated DC (1) as instances for training ML algorithms (here: Amazon Web Services (AWS)), and (2) for mining cryptocurrencies (here: Bitcoin). Hence, the objective of this paper is the development and quantitative evaluation of an economic model that considers an optimal investment decision into an IES using the NPV. To the best of our knowledge, an IES has neither been modeled nor quantitively evaluated as (1) opportunity to increase investments in RES-plants in times of volatile electricity prices and (2) as a supplier of energy flexibility in the light of EI. Moreover, we note that our model may also be of high relevance for RES-plant operators whose RES subsidy programs expire in the near future – as is, for example, the case in Germany where subsidies for 45GW of wind capacity have expired in 2020 (Friedemann 2018).

Our work contributes in various ways to research and practice: We build on (1) research on optimizing costs of DCs, on (2) research on Green IT, i.e., the environmentally friendly and resource-saving use of IT throughout its entire life cycle, and on (3) research on Green IS, i.e., using IT to increase sustainability in various fields. We are the first to introduce the approach of integrating RES-plants and DCs to increase the economic viability of RES-plants, and our evaluation illustrates that this approach is applicable in practice. Additionally, we contribute to IS research on energy flexibility, see e.g., Kahlen et al. (2014), Fridgen et al. (2016), and Keller et al. (2020). Moreover and following Watson et al. (2010), our IES provides the opportunity to use flow networks more efficiently as it is able to shift energy demand and, in this way, to supply local flexibility.

The structure of our paper is as follows: We provide relevant background for our research in Sect. 2. In line with the research cycle proposed by Meredith et al. (1989), Sect. 3.1 introduces our methodology while we develop and describe our economic model in Sect. 3.2. Concerning our evaluation, we discuss the applicability and relevance of our use-cases in Sect. 4. Then, Sect. 5 describes the data used for the evaluation and discusses corresponding results. Section 6 highlights the contribution of our paper, and Sect. 7 finally concludes, providing limitations and an outlook for further research.

Related Literature and Background

In addition to the literature mentioned in the introduction, we identify the following four research streams in academic literature that provide background for our analysis of integrating an intermittent RES-plant and a DC: EI, DCs, IESs, and energy flexibility.

Regarding EI, Watson et al. (2010) propose the field of EI that aims to implement a sustainable energy system by “analyzing, designing, and implementing systems to increase the efficiency of energy demand and supply systems” (Watson et al. 2010, p. 24). In this light, our paper analyzes both, the RES-plant and the integrated DC, as a part of a flow network where both parts constitute sensitized objects that are adaptable with respect to their electricity demand and supply (Watson et al. 2010). The recent streams of EI combine – as also highlighted in the call for this special issue – “the perspectives of electrical engineering, energy economics, and information technology” (Staudt et al. 2019). This is in line with Zhang et al. (2018), who state that EI analyzes various digital technologies and “their applications in the energy sectors” to tackle energy-related challenges, see, e.g., Förderer et al. (2018) or Holly et al. (2020). Literature in this field finds that the intelligent management of DCs can introduce positive effects on the stability of such flow network and offer appropriate economic incentives (Thimmel et al. 2019). This is also closely related to the prevalent idea in IS research of IT-enabled transdisciplinary sustainable business transformations, according to Elliot (2011), who proposes the idea that EI can help to lower humans’ ecological impact through research on these complex phenomena. Zhang et al. (2011a) state that there are diverse opportunities to contribute to EI goals and thus motivate the need for and development of a strategic framework to effectively implement those. This is in line with EI researchers, who highlight both, the responsibility of IS research and corresponding opportunities in the near future (Buhl and Jetter 2009; Goebel et al. 2014). Therefore, our work contributes to EI research by reflecting a DC as an enabler for a more viable operation of RES-plants, which may, in turn, foster a sustainable transformation.

Regarding DCs, we already mentioned the wide-ranging research stream on energy consumption of DCs in our introduction. While research on the operation of DCs has focused on increasing their performance for decades, reducing energy costs gained more attention in the last years due to rising electricity prices (Beloglazov et al. 2011). As DCs are expected to account for about 20% of total electricity demand in 2030 (Jones 2018), research analyzes the question of how to make DCs more energy-efficient in various ways (Pedram 2012). Such ways include, e.g., technical aspects of DCs redundancy architecture and workload prediction, approaches to use heat generated by the DC, or the participation of DCs in DR-programs (Kliazovich et al. 2013; Klingert 2018; Shi et al. 2016; Shuja et al. 2012). The ability to take part in DR-programs is, of course, dependent on the level of flexibility the DC is able to provide with respect to Service Level Agreements (SLAs) deadlines (Keller et al. 2020). Vieira et al. (2015) distinguish between three levels of flexibility handling DC services requests: (i) “fixed-time requests “ (no flexibility), (ii) “floating-time requests “ (partly temporally flexible, e.g., interruptible), and (iii) “variable-time requests” (temporally flexible). Overall, current literature on energy-efficient DCs seems to be focused on lowering the electricity bill and the carbon-footprint of a DC.

Regarding (renewable) IESs, literature specifically addresses two streams. On the one hand, IESs play an important role in remote areas where reliability is important in the subsystem (Kanase-Patil et al. 2010). On the other hand, storage options for an efficient use of RES offer new prospects for IESs, which are especially discussed with respect to electricity battery storage (Connolly et al. 2012) and power conversion in Power-to-X plants (Glenk and Reichelstein 2019). Research suggests that Power-to-X plants converting electricity into a storable good like hydrogen or fuel may play an important role in future energy systems with their property to store electricity and use it in a flexible manner (Bai et al. 2016; Glenk and Reichelstein 2020). Within the energy research community, this research stream is also sometimes referred to and considered using the term smart energy systems (Lund et al. 2017). To the best of our knowledge, we are the first to present a model and an evaluation for an integration of an RES-plant and a DC.

Finally, regarding energy flexibility, research considers the concept of DR as a possible subset of Demand-Side Management and as a possible key element for tackling the challenge of grid stability for decades (Gellings 1985; Palensky and Dietrich 2011). Here, literature defines DR as the adaption of a load profile given, e.g., time-varying electricity market price signals (Palensky and Dietrich 2011). In this way, DR is a form of energy flexibility on the demand side (Haupt et al. 2020). Research repeatedly stresses the crucial role of IS for an efficient DR (Fridgen et al. 2020; Kahlen et al. 2018; Körner et al. 2019). Consequently, also IS research addresses the topic of load shifting. For example, Fridgen et al. (2016) assess the value of IS-enabled flexibility on the demand side, with a focus on electric vehicles. Gelazanskas and Gamage (2014) further elaborate on what information is needed to decide on specific DR measures. IS research also analyses how DR can be used to gain a financial advantage in various markets, e.g., on the electricity spot market (Jäckle et al. 2019). In the light of energy flexibility, DR may, therefore, help to increase the overall efficiency of an energy system, while at the same time reduce the cost of energy demand for consumers (Paulus and Borggrefe 2011). Against this background, our work contributes to this research stream by illustrating that an IES supplying flexibility is applicable and economically viable.

Methodological Approach

To answer our research question, we follow the research cycle proposed by Meredith et al. (1989) that is widely used in IS research (Banz et al. 2016; Bürger et al. 2017). According to Meredith et al. (1989), model development should build on a research cycle consisting of three stages, namely the description, the explanation, and the testing stage. Accordingly, we develop a model that describes investment decisions in the IES and the optimal usage of the IES in Sect. 3.2 (also cf. Appendix A; available online via Our model is based upon analytical modeling, as we assume a rational utilization of the IES (Meredith et al. 1989). To test our model, we evaluate it with real-world data in Sect. 5. In the following, we consider all three stages of the research cycle in more detail.

Meredith et al. (1989) state that the description stage is essential for model development as it characterizes the examined system. In line with such approach, we introduce and locate our IES into relevant fields of research that we identify in the literature (Sect. 2). Furthermore, we describe how the IES relates to similar technological systems in research, especially with respect to Power-to-X plants.

The explanation stage is characterized by developing the causal structures or complex relationships of a system. We constantly shift backward and forward between the description and the explanation stage in Sect. 3.2, as new aspects of the examined system are first described and then analyzed, as suggested by Meredith et al. (1989). In the light of Meredith et al. (1989), our analysis classifies as rational and artificial in analyzing the operation of an IES. We do so by conducting formal deductive quantitative modeling in Sect. 3.2. Our model assumes an investor, who acts as an economic agent that chooses the investment in the respective plants maximizing the NPV (Hirshleifer 1958). Building the basic framework for our model, we utilize the approach presented by Glenk and Reichelstein (2019), who identify an optimal investment decision into an IES consisting of an RES-plant and a Power-to-Gas plant. Subsequently, in line with Meredith et al. (1989), we illustrate the impact of our IES on promoting RES-plants.

In the testing stage, we examine the identified model along with a more detailed description of the situations that the testing is based on (Meredith et al. 1989). We begin the testing stage in Sect. 4 by describing how the application of AWS instances for ML and Bitcoin mining fits the examined relationships and stating the specific assumptions for the testing. We then quantitively apply our model in line with Taylor (2005) and describe the results in Sect. 5. Subsequently, we discuss the results in light of our RQ and illustrate the contributions of our paper.

Model Development

Based on the methodological approach described above, we first introduce the setup of our IES. We then briefly define the most relevant variables/parameters and derive the mathematical representation for an optimal investment decision. Figure 1 depicts the specific setup of the IES. The RES-plant (1) generates electricity that is either sold on the electricity market (2) or consumed within the IES by a DC (3). The DC thus consumes either electricity bought from the electricity market or electricity generated within the IES to execute computations, which are then compensated for by an external market (4). The IES itself consists of (1) and (3); hence the IES’s system border relates to the connections between the IES and the respective markets (2) and (4). The relevant electricity market referred to in this work is the electricity spot market.

Fig. 1
figure 1

(Adapted from Glenk and Reichelstein (2019))

Integrated energy system.

The objective of our model is to maximize the NPV of an investment in an IES based on the capacity investment decisions for the RES plant \(k_{e}\) and the DC \(k_{DC}\) (cf. detailed variable overview in Appendices A and B). We note that our model is based on previous work from the energy economics community, especially on the work of Glenk and Reichelstein (2019) and Glenk and Reichelstein (2020). We broaden the scope of application of their model, e.g., being applicable to real-world IS cases: we expand the model by temporally varying efficiency factors and output price determinants that account, for example, for the specifics of DC hardware and DC operation (cf. Appendix A).

We refrain from detailing out the model development step by step but instead give an overview on the overall model (see Appendix A for detailed model development). The overall operation of the IES is split into four operation modes, which base on the comparison of the economic input factors, namely: the electricity selling price \(p_{s} \left( t \right)\), the electricity buying price \(p_{b} \left( t \right)\), and the conversion value of utilizing electricity in the DC \(CV_{DC} \left( t \right)\). The operation mode describes how to optimally utilize the IES given the input factor prices and, thus, corresponds to the behavior of a rational operator. Based on the specific operation mode, the effect on the electricity grid may change when the IES shifts from a net supplier to a net consumer. We note that the four operation modes are not sequential, and hence, there is no fixed order of their occurrence. The four operation modes are described as follows and are illustrated in Fig. 2:

  • Operation mode 1: The DC is idle as electricity prices are too high to operate the DC economically. The RES-plant operates at full capacity and sells the generated electricity on the electricity market. This may reflect times, when there is overdemand for electricity and when there are low values for utilizing electricity in the DC. Therefore, the following relation holds: \(p_{b} \left( t \right) \ge p_{s} \left( t \right) \ge CV_{DC} \left( t \right) \ge 0\).

  • Operation mode 2: The DC utilizes electricity generated by the RES-plant as the utilization ensures a positive contribution margin, and additional DC capacity remains idle, as an operation with bought electricity is not economically viable. We have the following conditions: \(p_{b} \left( t \right) \ge CV_{DC} \left( t \right) > p_{s} \left( t \right) \ge 0\).

  • Operation mode 3: The DC operates at full capacity utilizing both the electricity generated by the RES-plant and additional electricity bought from the market. The following condition characterizes mode 3: \(CV_{DC} \left( t \right) > p_{b} \left( t \right) \ge p_{s} \left( t \right) \ge 0\).

  • Operation mode 4: The DC operates at full capacity utilizing electricity bought from the electricity market, while the RES-plant is idle. The operator is compensated for electricity bought from the electricity market (negative electricity prices), which implies that external electricity is utilized idling the RES-plant. The following relation holds:\(CV_{DC} \left( t \right) \ge p_{s} \left( t \right) = 0 > p_{b} \left( t \right).\)

Fig. 2
figure 2

Operation modes of the IES: Four different operation modes

Based on these operation modes, the NPV of an IES as our objective function writes as follows (bars indicate a variable’s mean; see Appendices A and B for further details):

$$\begin{aligned} NPV\left( {k_{e} ,k_{DC} } \right) & = \left( {1 - \alpha } \right)\cdot L\cdot [\left( {\Gamma^{s} \cdot \overline{p}_{s} - LCOE} \right)\cdot \overline{CF} \cdot k_{e} \\ & \quad + \left( {\overline{p}_{b + } - \overline{p}_{b} - LFCCP} \right)\cdot k_{DC} \\ & \quad + \left( {\overline{p}_{ + } - \overline{p}_{s} } \right)\cdot z\left( {k_{e} ,k_{DC} } \right)] \\ \end{aligned}$$

The parameter \(\alpha\) accounts for the operator’s tax factor, \(L\) represents a levelization factor, \(\Gamma^{s}\) gives the deviation of input factors from their mean, \(LCOE\) represent the levelized cost of electricity of the RES-plant, \(LFCCP\) describe the levelized fixed cost of computing power, and \(z\left( {k_{e} ,k_{DC} } \right)\) is an auxiliary variable taking into account the respective capacities of the two plants, whereas \(\overline{p}_{b + }\) and \(\overline{p}_{ + }\) constitute price helper variables (a detailed description can be found in Appendices A and B).

The above equation reflects the stand-alone values of the specific parts of the IES by its first two terms as well as the synergistic value by the last term. Thus, the last term in the above equation allows us to state that the integration of an energy-intensive DC may well increase the NPV of an RES-plant as a part of the IES. The synergistic value is based on the fact that costs, e.g., transmission and storage costs, associated with the consumption of electricity from the market may be avoided. This is in line with the findings of Glenk and Reichelstein (2019) since these costs may be identified as the difference between \(p_{b} (t\)) and \(p_{s} \left( t \right)\) in operation mode 3. Besides, the consumption of the DC increases as it also operates economically viable, if \(p_{b} \left( t \right) \ge CV_{DC} \left( t \right) \ge p_{s} \left( t \right)\) holds in operation mode 2. Hence, the above objective function already illustrates that investments in IESs, and therefore in RES-plants, may increase when integrated with a DC.

Machine Learning and Cryptocurrency Mining as Use-Cases

In the testing stage of our methodological approach, we evaluate our model with real-world data. Our IES may be applicable for a variety of use-cases, i.e., the plant that is to be integrated with the RES-plant may take a wide variety of different forms. These forms may range from production plants that convert electricity into physical goods to more IS-related forms, such as the conversion of electricity into computational power by a DC. With respect to the latter, we evaluate two specific use-cases that differ concerning their ratio between electricity input and product sales price, namely AWS (on-demand) instances for training ML algorithms and the mining of Bitcoin. While for these specific use-cases this ratio is much higher for Bitcoin mining as compared to AWS instances, we note that this may result from distorted (high) prices for using AWS instances. In this context, recent trends within the ML industry may lead to electricity costs becoming much more relevant for training ML algorithms (Sze et al. 2017). However, we note that today’s AWS on-demand prices do only depict a relatively small ratio between electricity input and product sales price. Moreover, we note that SLAs may prevent the operator from idling the DC because of direct costs (due to SLA breaches) or indirect costs (due to lower customer satisfaction as a result of downtimes). However, regarding our evaluation, we consider the two use-cases to execute”variable-time requests” that may be shifted temporally in line with Keller et al. (2020) and Vieira et al. (2015). In the following, we give some more details on the two exemplary use-cases.

Machine Learning

ML – as a subset of artificial intelligence – provides entities with the possibility to compute human-like decisions by algorithms being able to produce knowledge by generalizing from examples, i.e., relations in exemplary data (Domingos 2012; Kratsch et al. 2020). The field has grown new interest over the past years in both, research and practice. A variety of computing algorithms exist that “learn” a new model based on an existing data set, e.g., to predict unknown data. This utilization of computing power also fits the setup of an IES as the learning needs not to take place at a specific time but may instead be shifted based on external market signals, in this context, specifically electricity market prices. Hence, we reflect it as temporally flexible in the sense of Vieira et al. (2015) – which may be some simplification with interesting future research opportunities. Furthermore, research critically evaluates the increasingly high demand for ML use-cases and the corresponding energy demand (Jobin et al. 2019). AWS is the largest operator of cloud computing capacity and offers a variety of computing instances that are specifically designed to run ML applications. Therefore, its setup may serve as a use-case for an evaluation of our work.

Bitcoin Mining

Bitcoin mining constitutes the process of creating Bitcoins as well as validating transactions within the Bitcoin system (Nakamoto 2008). In order to be allowed to add a new block to the blockchain, a network participant must prove that the user has solved the according hashcash. A hashcash constitutes a cryptographic problem that is designed to be arbitrarily difficult to solve; if a solution is found, it can easily be verified whether the provided solution is correct or not. The only opportunity to solve a hashcash is that a computing machine randomly tries possible answers until the right one is met (Narayanan and Clark 2017). This process makes Bitcoin mining extraordinarily energy-intensive (Sedlmeir et al. 2020). However, we note that not all Blockchain applications may solely be regarded as energy-intensive consumers (Albrecht et al. 2018). For example, Nieße et al. (2018) reflect Blockchain as a technology to manage parts of the energy system by introducing a Blockchain-based system for congestion management. Moreover, for example, Utz et al. (2019) propose a Blockchain-based smart contract system for shared energy assets, while Wu and Tran (2018) review several Blockchain applications, e.g., for carbon emissions certification and trading. Regarding our evaluation, Bitcoin mining is not only implementable in practice, but the Bitcoin price also allows for an immediate price determination for the product corresponding to the energy input. Additionally, the operation of Bitcoin mining may be time-independent, i.e., adjustable to electricity generation or electricity prices without consumption catch-up effects. Thus, Bitcoin mining is utilized as a second evaluation case.

Results and Implications

Description of Data and Assumptions

Both use-cases are evaluated using real-world data from the German electricity market of the latest available three years 2016–2018 (see Appendix C, D). The German market serves as a relevant use-case given two reasons. First, there is a high share of intermittent RES on the German electricity market already today, resulting in quite volatile price patterns. Second, with respect to Germany’s subsidy programs, the first government-subsidized RES-plants will phase out soon, creating a new market environment that may challenge the further operation of these plants. Therefore, we consider a wind power station in Germany as an exemplary RES-plant, and use the electricity spot price (intraday) for the German price region as the price for electricity sold on the electricity market \(p_{s} \left( t \right)\). However, we note that the decision concerning the market(s) to address is itself a complex task. Our IES may also be able to operate in long-term markets, e.g., by Power Purchase Agreements, and short-term markets, e.g., in control energy markets. Also, hybrid solutions may be possible, where parts of the generated energy are traded at different markets. As a starting point, we consider the spot market which gives important price signals for plant operators. Regarding the purchase of electricity, \(p_{b} \left( t \right)\), we assume a fixed surcharge based on industry electricity purchase (Glenk and Reichelstein 2019).

Regarding the ML-case, we additionally assume a DC output price in line with the publicly available on-demand utilization prices for ML instances provided by AWS (see Appendix C). We calculate electricity usage and costs based on the energy consumption of the associated hardware stack, including the respective investments. To incorporate overhead server energy consumption, i.e., cooling and memory, we add a surcharge of 70% on the DC’s processing chip energy consumption in line with Dayarathna et al. (2016). As (i) the specific cost structure and the respective energy consumption of an AWS server stack is not publicly available, and (ii) the modeling of highly specific costs, e.g., costs for switching on and off or stand-by costs of the idle DC, yields a high model complexity due to discrete decisions (Dayarathna et al. 2016), we simplify these costs and assume that they are included in the fixed operating costs. In line with Fridgen et al. (2017), we further assume that the energy consumption of the DC is proportional to its load operated. Considering research and practice, we note that there are several promising approaches demonstrating and further improving the proportionality between a DC’s processing capacity and its load (Gandhi et al. 2010; Ganesh et al. 2013; Lin et al. 2013; Tolia et al. 2008; Whitney and Delforge 2014). However, we also note that this assumption may limit the accuracy of our numerical results but does not affect their general explanatory power. To address this issue, we conducted sensitivity analyses regarding the input factors, e.g., costs for equipment, especially overhead costs, or energy consumption of this equipment, (for example, of cooling servers). Some DCs also utilize significant shares of electricity when they are idle, which is why we increased fixed operating costs by 50%, 100%, and 200%. The operation modes and corresponding results presented hereinafter do not change significantly (cf. Sect. 5.2 and 5.3), whereas the NPV of the investment as well as the optimal DC capacity shrinks due to increased costs.

Regarding the BC-case, we evaluate the model with Bitcoin price data and the respective mining network characteristics, i.e., mining difficulty, block reward, and transaction fee, based on publicly available sources (see Appendix D). We base our assumptions regarding costs and computational power on mining hardware that was available at the beginning of the observation period to ensure coherent results. We maintain the assumption of proportionality between the DC load and the corresponding energy consumption as stated above.

Figure 3 depicts the conversion values and electricity prices used in our evaluation. The dots depict the conversion value range of the Bitcoin mining plant. The hours within the observation period of three years, i.e., 26,304 h, limit the abscissa in Fig. 3. The level of the conversion value of Bitcoin mining \(CV_{BC} \left( t \right)\) is temporarily above, below, or between the prices for buying electricity \(p_{b} \left( t \right)\) (see the drawn through line) and the price for selling electricity \(p_{s} \left( t \right)\) (see the dashed line), which illustrates the different operation modes of IES operation an illustrates that the four operation modes of our model (cf. Figure 2) indeed occur within our real-world evaluation case. We note that the conversion value \(CV_{ML}\) based on the constant on-demand price for AWS ML instances is above the prices for buying and selling electricity at all times (represented in Fig. 3 as dashed-dotted line).

Fig. 3
figure 3

Conversion values and electricity prices of the IESs

Results for an Investment in Stand-alone RES-Plants and DCs

When assessing the NPV of a stand-alone DC (without an RES-plant), the variable \(k_{e}\) that describes the capacity of the RES-plant is set to zero, implying that the DC can only consume electricity that is bought from the electricity market. The left subfigure in Fig. 4 depicts the NPV of an investment in a stand-alone ML-DC, depending on the chosen capacity \(k\) of the DC. The NPV proportionally increases (ML-case with capacity \(k_{ML}\)) or falls (BC-case with capacity \(k_{BC}\)) with increased investment. This is mainly based on two facts. First, no synergies within an IES can be used, as electricity can only be bought from the market. Second, our model suggests that investments and operating costs behave proportionally to the invested capacity. In our evaluation setting, the optimal decision of an investor is to fully invest in the ML capacity (\(k_{ML} = 1\)) but not at all in the mining plant (\(k_{BC} = 0\)). The latter is due to the fact that the price to purchase electricity on the market is too high to recoup the capacity investment, although the DC is active in 35% of the considered time periods. This finding is in line with the low amount of Bitcoin mining in Germany (Willms 2019), and also persists – given the results of our sensitivity analyses – if the fixed operating costs are increased. The optimal capacity of the respective DC remains either 1 in the ML-case or 0 in the BC-case. Based on the used data, the NPV of a stand-alone RES-plant \(NPV_{{k_{e} }}\) is positive in our evaluation setting. This analysis is generally independent of the capacity of the plant as indicated in the right subfigure of Fig. 4, as the slope of the NPV function is constant. The constant slope depicts an idealized setting since a continuous construction and dismantling of the capacities of DCs as well as RES-plants may not be possible in reality.

Fig. 4
figure 4

Depiction of the NPV of the stand-alone plants: ML-DC (on the left), Bitcoin mining DC (in the middle), and RES-plant (on the right)

Results for an Investment in an Integrated Energy System

For the investment in an IES, we assume that the RES-plant either sells its electricity to the electricity market or the electricity is locally consumed in the integrated DC. As we already described above, the NPV of the stand-alone ML-DC may be positive (due to high ML conversion values). Our results thus illustrate that the NPV of an IES, consisting of an RES-plant and a ML-DC, yields a positive NPV alike. The IES does not feed-in electricity into the grid at any time, but it uses the generated electricity locally for the integrated ML-DC. This effectively results in the absence of operation mode 1 of the model. It corresponds to expectations from real-world observations, as DC services are normally not deactivated by providers due to high electricity costs. The result for the ML-case demonstrates that the integration indeed yields synergistic effects, i.e., the NPV of the IES is higher than the sum of the NPV of the two stand-alone plants. This may effectively reduce the electricity bill for operating the energy-intensive ML application. Furthermore, the utilization of the RES-plant may increase as its generated electricity may also be used in the ML-DC at times when the selling price for electricity drops below 0. This effect is accompanied by an increase in the share of RES that is utilized within the ML-DC in comparison to the stand-alone case (utilizing only market electricity), resulting in a decrease of the DC’s carbon-footprint. The conducted sensitivity analyses suggest that the optimal investment size remains the same, whereas the NPV of the IES is lower in case of higher fixed costs, e.g., the NPV is reduced by 9% if the fixed costs are increased by 100%. The synergistic value persists as well.

As the stand-alone Bitcoin mining plant yields no positive NPV in our evaluation setting, an investment in Bitcoin mining capacity larger than the capacity of the RES-plant cannot maximize the NVP of the IES. Thus, if we normalize the capacity of the RES-plant \(k_{e}\) to 1, the optimal investment in the Bitcoin mining plant \(k_{BC}\) must lie in the closed interval \(\left[ {0,1} \right]\). In contrast to the evaluation of each stand-alone case, the left subfigure in Fig. 5 shows a concave NPV function for the IES. This concavity implies that synergies between the two parts of the IES exist as identified in our model. In particular, our results illustrate that the NPV of the IES has a single optimal capacity of \(k_{DC} = 0.45\). This implies that the peak capacity of the mining plant equals 45% of the peak capacity of the RES-plant. In this way, our evaluation finds that the NPV of the IES is 32% higher than the stand-alone NPV of the RES-plant. In comparison to the stand-alone case, the operation of the IES changes significantly. The IES’s inherent RES-plant supplies 73% of the electricity that is consumed by the mining plant. The share of 73% RES supply is more than doubled, if compared to the German grid mix having an average of 35.1% of RES supply during the observation period (BMWi 2019). For this use-case, our IES may help to reduce the carbon-footprint of Bitcoin mining. Here, we also note that – as illustrated by Sedlmeir et al. (2020) –other consensus mechanisms such as proof of stake or proof of capacity may help to reduce the carbon-footprint. Furthermore, the mining plant now operates 82% of the time, which constitutes a significant increase compared to the stand-alone mining plant (35%). Overall, the IES is characterized by a net energy supply within the observation period: the RES-plant feeds-in 12% more electricity to the grid than the mining plant consumes. Overall, we find that 36% of the total energy generation of the RES-plant is fed-in the grid. The mining plant consumes internal energy at low electricity prices, which indicate a high (over-) supply of electricity on the market. Anyhow, the underlying data suggests a negative correlation (\(\rho = - 0.33)\) between RES generation and the price for selling electricity at the market \(p_{s} \left( t \right)\), which is supported by existing research (Sáenz de Miera et al. 2008). Consequently, the mining plant consumes internally generated electricity when the opportunity cost for selling this electricity on the market is low and the (overall) amount of electricity that is fed into the grid is high. Hence, the IES may contribute to grid stability by locally using generated electricity instead of feeding it into the grid, i.e., by supplying (local) flexibility.

Fig. 5
figure 5

Depiction of NPV of the IES that consists of an RES-plant and a Bitcoin mining plant (on the left) and the NPV of the same IES assuming higher maintenance costs for the RES-plant (on the right)

In the near future, there will also be settings, in which the specific stand-alone NPV of the RES-plant is negative, e.g., due to higher fixed maintenance costs for the RES-plant at the end of the plant’s lifetime RES-plant (Ziegler et al. 2018). We also find that in cases where the NPVs of both, the RES-plant and the DC, are negative, the optimal decision of an investor may be to invest in the IES. In other words, even if both parts of the IES cannot be operated economically viable on a stand-alone basis, the IES may be profitable. The subfigure on the right only depicts a shift of the NPV function (cf. vertical axes), as the synergies that stem from the integration of the two plants remain unaffected. The optimal investment in both cases is again \(k_{DC} = 0.45\) and even in the setting illustrated in the right subfigure we derive a positive NPV. We also note that this result supports the findings of Glenk and Reichelstein (2019), who analytically show that the synergistic value of an IES may outweigh the negative NPVs of both stand-alone plants. The conducted sensitivity analyses suggest that the optimal capacity may decrease if fixed costs are higher. For example, the optimal capacity may decrease to \(k_{DC} = 0.25\) if the fixed costs may be 200% higher. Such lower capacity further decreases the share of electricity used internally and consequently the synergistic value of the IES (then 41%).

To sum up, both use-cases, the ML-case and the Bitcoin-case, yield positive NPVs resulting in the promotion of RES-plants. Moreover, when integrated with an RES-plant, the Bitcoin mining plant is able to provide significant demand-side flexibility.

Based on the modeling and evaluation in the previous sections, we summarize first research contributions of our work as well as first insights for practice and decision-makers.

Concerning the contribution to IS research, our results build on research on optimizing energy costs of DCs, on research on reducing the carbon-footprint of DCs (Green IT), and on research on how to use IT-infrastructure to increase the sustainability of the energy system (Green IS) as described in Sect. 5. Moreover, our work contributes to the research stream on IS-enabled energy flexibility, see, e.g., Kahlen et al. (2014), Fridgen et al. (2016), and Keller et al. (2020). Our IES constitutes a new way of providing (local) energy demand-side flexibility. Such flexibility results from the operation mode of the IES reacting to electricity market signals, i.e., electricity prices; if market signals indicate that overall electricity feed-in is (too) high, i.e., electricity prices are low or negative, the IES’s electricity will be used by the integrated DC and the overall amount of electricity in the system decreases. Our evaluation suggests that the more relevant electricity costs of the converted good are, as compared to its output price, the more sensitively the IES operates with respect to external electricity market signals (see Sect. 5). This may be of particular interest as recent trends suggest that the relevance of electricity costs for ML applications will increase significantly. Furthermore, we also contribute to IS-research and theory by building on the work of Watson et al. (2010). Our IES provides new opportunities for increasing the efficiency of flow networks as introduced by Watson et al. (2010), given that the IES supplies local flexibility by converting excess electricity on-site into computational power. In this sense, our approach may help to use flow networks more efficiently by implementing IS applications, e.g., an IES. In addition, both parts of our IES, the RES-plant as well as the integrated DC, may constitute sensitized objects. In this context, our research also contributes to further developing use-cases for the concept of edge computing as the IES may shift computational power towards the edges of the network. This may be particularly relevant for research focusing on topics of sustainable edge computing (Li et al. 2018). Moreover, we contribute to research by transferring approaches from outside the IS-community, i.e., Glenk and Reichelstein (2019), into the field of EI. We develop an economic model for an IES that reflects IS cases in which the consuming part of the IES is a DC.

Our work is also highly relevant for practice and decision-makers when reflecting on the implementation of IESs. In our evaluation, we illustrate that the IES performs well for practical settings, e.g., for ML and for Bitcoin mining as examples for (energy-intensive) applications. In both cases, the IES has a positive NPV, i.e., the operation of the RES-plant and the DC within the IES is economically viable. We also analyze the situation where the NPV of a stand-alone RES-plant is negative, e.g., due to high fixed maintenance costs or due to the expiration of subsidy programs, resulting in a situation where a (further) operation of the RES-plant on its own may not be economically viable (Friedemann 2018; Ziegler et al. 2018). For such cases, our results illustrate that the NPV of the IES may be positive even if the NPV of both, the stand-alone RES-plant and the respective DC, is negative. Moreover, as highlighted above, our work will also be increasingly relevant for companies that deal with ML applications, reflecting that energy costs for ML will increase within the next years, and its usage may be shifted temporally. In summary, as our IES has a higher NPV compared to the stand-alone plants, it may increase investments in RES-plants by tackling uncertainties of RES-plant operators concerning income in time periods with low electricity prices. From an overall energy-system perspective, the RES generation could be promoted through a corresponding integration with an energy-intensive DC.

Conclusion, Limitations, and Further Research

In this paper, we present an economic model that illustrates how the integration of an RES-plant with an energy-intensive DC into an IES may increase the economic viability of an RES-plant operation. We evaluate our model by applying two use-cases, namely, ML and Bitcoin mining to make use of the DC. Our results illustrate that the NPV of the IES can be higher than the NPV of the stand-alone RES-plant as well as of a stand-alone DC. We argue that a higher NPV of an IES may promote investments in RES-plants. Especially with respect to the prevalent negative correlation between RES generation and electricity market prices, the IES could tackle uncertainties for RES-plant operators concerning their income in times of low electricity prices. Moreover, we argue that our IES is also be able to contribute to grid stability by supplying flexibility. We also note that the DC – when used within the IES – may consume a higher share of RES and thus distinctly reduce its own carbon-footprint. Overall, we conclude that our IES promotes the operation of RES-plants by integrating energy-intensive DCs.

Given our first results, we briefly sketch some limitations of our work. In general, our methodology in terms of application-oriented modeling inhibits limitations itself, including a simplification of a real-world application and the exclusion of specific contextual factors such as the need for a timely execution of computing services. These factors may be incorporated as SLA costs or deadlines that introduce additional constraints to the model at hand. Our evaluation use-cases may limit our results as they are based on specific economic parameters and assumptions that may differ when assessing other applications. For example, we base our ML-evaluation on several assumptions concerning the costs of operating a DC, however, the cost structure of AWS server stacks is not publicly available. Moreover, we simplify the economics of a mining plant in our evaluation; in particular, we assume that a large part of the DC has no recovery value at the end of the three-year term, whereas the future use in reality is rather complex. For example, the utilization of the mining processor may become obsolete due to future mining difficulties or new mining technologies. In such cases, the equipment may still well be utilized in application areas with lower electricity prices and therefore sold to other operators. In consequence, specific assumptions of our evaluation cases may not fit generic real-world applications, which may require a more detailed consideration of additional (technical) constraints of an IES operation.

Our work also provides various starting points for further research that may extend our approach, for example, by considering other markets or the interconnection between the IES and the grid in more detail. Here, research may address the above limitations by applying additional use-cases and corresponding markets, e.g., control energy markets. Reflecting and incorporating the value of addressing several markets with one IES may constitute the basis for the development of specific decision support systems for operators. Further research may also quantify the IES’s contribution to addressing grid stability issues in full details. Moreover, further research may consider specific cost structures of DCs in all their particulars. With respect to further EI research, we suggest reflecting the role of edge computing in the light of consuming electricity locally as it inherently shifts electricity consumption towards the edges of a computing grid. Moreover, future work may also discuss relevant implications for policymakers, e.g., analyze whether and which kinds of subsidy programs for promoting RES-plants (that typically bear huge costs for the general public) are needed under consideration of concepts like IESs. Here, our first results suggest that the implementation of (new) subsidy programs, especially feed-in tariffs, may reduce synergistic effects of the IES. Feed-in tariffs generally entail higher opportunity costs for the operator of an IES when consuming the electricity within the IES. Against this background, our work may serve as a profound starting point for future research in the highly relevant field of EI.


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