Energy Informatics 2023 in Vienna -- Call for Papers

The EU aims to be climate-neutral by 2050 – an economy with net-zero greenhouse gas emissions. This objective is at the heart of the European Green Deal and in line with the EU’s commitment to global climate action under the Paris Agreement. The transition to a climate-neutral society is both an urgent challenge and an opportunity to build a better future for all. Energy informatics support in solving many challenges of the energy transition, by providing solutions for intelligent management and operation of energy systems and their assets.

The objective of the DACH+ conference series on Energy Informatics is to promote research, development, and implementation of information and communication technologies in the energy domain and to foster the exchange between academia, industry, and service providers in the German-Austrian-Swiss region and its neighbouring countries (DACH+).

We seek high-quality original contributions addressing the design, adoption, operation and management of smart energy systems, the integration of intermittent renewable generation and energy efficiency gains through ICT, market approaches and mechanisms for ICT-enabled energy systems, and research on associated (decentralised) data-driven decisions. We welcome theoretical contributions as well as publications addressing system design, implementation, and experimentation. The list of topics of interest to the conference includes, but is not limited to:

• ICT for future energy systems, sector coupling and the integration of intermittent renewable generation
• Information and decision support systems for future energy markets and mechanisms
• Energy system modelling and (open) energy system data
• Protocols and architectures for IT systems in the energy sector
• Data analytics and machine learning for smart energy systems and decentralised decision-making, as well as platforms for data analysis
• Open data and software for energy research
• Management of distributed generation and demand side management
• ICT for (multi-) energy networks and micro-grids
• Energy-efficient mobility, charging management for electric vehicles, energy-aware traffic control, and smart grid integration of mobile storage
• Smart buildings, digital metering, occupant comfort, and user interaction
• Adoption of ICT in the energy sector
• Cross-cutting issues including cyber security and privacy protection, interoperability, verification of networked smart grid systems

Posters, Demos and Workshops

Submissions for posters, demos, and workshop suggestions are welcome, too. The topics of interest are the same as indicated above. Posters and demos require the submission of an extended abstract, which will be peer-reviewed. If accepted, the abstract will appear in the conference proceedings. Further details can be found on the conference website.

Submission and Publication

Submitted papers will be reviewed in a double-blind process. Accepted and presented papers will be published in the Springer Open Journal Energy Informatics (https://energyinformatics.springeropen.com). The conference language is English, and papers must be written in English. We solicit full research papers (max. 18 pages of content plus 2 additional pages for references) as well as short papers (max. 10 pages of content plus 2 additional pages for references). Templates and instructions will be made available at http://www.energy-informatics.eu/. Further information on the submission of posters and demos is also available on the website. The Open Access fee for the journal article is included in the registration fee.

Important dates

Apr 09, 2023:                     Submission of papers

May 16, 2023:                     Decision acceptance (assignment of shepherds) / rejection

May – Aug                          Incremental revision process between author and shepherd

Jul 02, 2023:                        Camera-ready deadline for poster abstracts for accepted contributions

Oct 04 2023:                      14th Doctoral Workshop Energy Informatics

Oct 05-06, 2023:                12th DACH+ Conference on Energy Informatics

Energy to train AI tools, wasted?

Energy used to make and provide online services is an important consideration for many reasons. Production and delivery of online services require energy, and that energy has a direct impact on the environment. The energy used to create and provide online services often comes from burning fossil fuels, such as coal, natural gas, and oil. This burning releases carbon dioxide (CO2) and other pollutants into the atmosphere, contributing to global warming. Burning fossil fuels also releases other harmful pollutants, such as particulate matter, sulfur dioxide, and nitrogen oxides, contributing to air pollution and can cause serious health problems. Increased energy consumption also has a direct effect on our environment. As energy consumption increases, so does the demand for resources such as coal, natural gas, and oil. This can lead to the destruction of ecosystems and habitats, as well as the displacement of communities. Additionally, burning these resources to produce energy contributes to climate change, causing a shift in weather patterns, rising sea levels, and an increase in extreme weather events. The energy used to provide online services also has an impact on the cost of providing these services. The more energy used to power the servers and networks, the more expensive the services become. Additionally, higher energy costs can lead to higher consumer prices, as companies must pass on the extra costs to their customers. Finally, suppose energy used to provide online services is generated from non-renewable sources, such as coal and oil. In that case, it means that the energy used to power these online services will eventually run out, which could negatively impact the availability of these services in the future. Overall, it is essential to consider the energy used to make and provide online services. Burning fossil fuels to power these services contributes to air pollution and global warming while also increasing costs. Additionally, the use of non-renewable resources to generate energy could lead to a decrease in the availability of these services in the future. 

A prominent example of online services is AI chatbots that can provide the user with answers to almost any topic. Other than a search engine that only finds matches of the search text in the indexed documents, AI chatbots can compose new information by drawing connections between the vast amount of information they have been trained with. AI programs like ChatGPT are a highly relevant development because they significantly improve the user experience and enable people from all domains to access sophisticated AI technology. Open AI programs make AI more accessible, allowing developers to share and collaborate on AI models. It also helps reduce development costs and makes integrating AI into existing applications easier. By allowing developers to access and build upon existing models, they can create new and innovative applications that can benefit everyone. Developing AI models helps automate tedious tasks and reduce the time spent on manual labor. By using AI models, businesses can automate mundane tasks and improve their workflow. AI models can also help to improve customer support and increase customer satisfaction. AI models are also important for predicting future trends and predicting customer behavior.

But, despite the fact that users of AI often get free access or a generous free trial, developing and training an AI model does not come for free when we consider the energy budget. The Carbon footprint of training ChatGPT has been estimated to be 1287 MWh [1], in addition to running the services. Are 1287 MWh a number to be concerned with? Probably yes. Is it a number so high that we immediately need to banish AI training for the sake of the environment? I don't think so.

When relating 1287 MWh to a single person, it is a lot. It would mean driving an average European car on fossil fuels for 4,5 Mio km. That is enough to travel the whole road network of the United States or equivalent to the carbon footprint of a flight passenger going form London to New York 320 times.

Nevertheless, ChatGPT has more than one user. In fact, it is one of the fastest-growing online platforms in the world, with around 100 Million users at the time of writing. Dividing the development costs by the users, it amounts to 0.01287 kWh or roughly 1% of the energy required to print a book. 

In other words, if users can utilize the AI system to automate mundane tasks and improve their workflow, the energy spent on creating the AI is probably well-invested. Many usages are recreational, and sometimes the AI provides more fiction than facts, but so is the case with books.

However, we need to keep our eyes open on two issues:

• The operational cost of running the system: "Cost" would mean here energy cost as well as financial cost. If the system does not work here efficiently, we could end up in a much higher energy waste than 1287 MWh
• Further developments in training new AIs: competitors might train their own AIs, no matter the (energy) cost. And models are expected to grow in complexity and capabilities, probably also significantly raising the energy required for training a single model.

So let's keep an eye on further developments.

[1] Patterson, D., Gonzalez, J., Hölzle, U., Le, Q., Liang, C., Munguia, L.-M., … Dean, J. (4 2022). The Carbon Footprint of Machine Learning Training Will Plateau, Then Shrink. Computer, 55, 18–28. Retrieved from http://arxiv.org/abs/2204.05149

Energy Informatics 2022 -- Call for Papers

Countries worldwide have strengthened their commitment to decarbonize the energy system at COP26 in Glasgow. This intent necessitates a massive increase in renewable power generation and the electrification of energy demand through sector coupling (e.g., heat and mobility). Over the last year, for example, the DACH countries have created roadmaps to establish hydrogen as an additional sustainable energy carrier. Energy informatics contributes to solving many of the challenges of this energy transition, by connecting various decentralized resources and by operating them intelligently.

The objective of the DACH+ conference series on Energy Informatics is to promote research, development, and implementation of information and communication technologies in the energy domain and to foster the exchange between academia, industry, and service providers in the German-Austrian-Swiss region and its neighbouring countries (DACH+).

We seek high-quality original contributions addressing the design, adoption, operation and management of smart energy systems, the integration of intermittent renewable generation and energy efficiency gains through ICT, market approaches and mechanisms for ICT-enabled energy systems, and research on associated (decentralised) data-driven decisions. We welcome theoretical contributions as well as publications addressing system design, implementation, and experimentation. The list of topics of interest to the conference includes, but is not limited to:

• ICT for future energy systems, sector coupling and the integration of intermittent renewable generation
• Information and decision support systems for future energy markets and mechanisms
• Energy system modelling and (open) energy system data
  
• Protocols and architectures for IT systems in the energy sector
• Data analytics and machine learning for smart energy systems and decentralised decision making, as well as platforms for data analysis
• Open data and software for energy research
• Management of distributed generation and demand side management
• ICT for (multi-) energy networks and micro-grids
• Energy-efficient mobility, charging management for electric vehicles, energy-aware traffic control, and smart grid integration of mobile storage
• Smart buildings, digital metering, occupant comfort, and user interaction
• Adoption of ICT in the energy sector
• Cross-cutting issues including cyber security and privacy protection, interoperability, verification of networked smart grid systems

Important Date

• Paper, poster & demo submission: Apr 8, 2022
• Notification: Jun 6, 2022
• Camera-ready paper due: Jun 24, 2022
• Doctoral Workshop: Sep 13-14, 2022
• Conference: Sep 15-16, 2022

Posters, Demos and Workshop

 
Submissions for posters, demos, and workshop suggestions are welcome, too. Details can be found on the conference website.

Submission and Publication

 
Submitted papers will be reviewed in a double-blind process. Accepted and presented papers will be published in the Springer Open Journal Energy Informatics https://energyinformatics.springeropen.com. The conference language is English, and papers must be written in English. We solicit full research papers (max. 18 pages of content plus 2 additional pages for references) as well as short papers (max. 10 pages of content plus 2 additional pages for references). Templates and instructions will be made available at https://www.energy-informatics.eu/. Further information on the submission of posters and demos is also available on the website. The Open Access fee for the journal article is included in the registration fee.

Stop! Exploring Bayesian Surprise for Load Disaggregation

In our latest paper, which is the result of the ongoing collaboration between our lab and SFU's Computational Sustainability Lab, we bring the concept of Bayesian Surprise to NILM. When has enough prior training been done? When has a NILM algorithm encountered new, unseen data? We apply the notion of Bayesian surprise to answer these important questions for both, supervised and unsupervised algorithms.

"Bayesian surprise quantifies how data affects natural or artificial observers, by measuring differences between posterior and prior beliefs of the observers" - ilab.usc.edu

Bayesian Surprise is measured in "wow"

We compare the performance of several NILM algorithms to establish a suggested threshold on two combined measures of surprise: postdictive surprise and transitional surprise.

We provide preliminary insights and clear evidence showing a point of diminishing returns for model performance with respect to dataset size, which can have implications for future model development, dataset acquisition, as well as aiding in model flexibility during deployment.

The paper is to appear at the 5th International Workshop on Non-Intrusive Load Monitoring (NILM'20): 

Richard Jones, Christoph Klemenjak, Stephen Makonin, and Ivan V. Bajić. 2020. Stop! Exploring Bayesian Surprise to Better Train NILM. In The 5th International Workshop on Non-Intrusive Load Monitoring (NILM ’20), November 18, 2020, Virtual Event, Japan.

An author's copy can be obtained from Christoph's personal website

We are looking forward to discussing this novel approach for NILM.

Should I drive with my car to turn off forgotten lights?

I forgot to turn off the lights in my office today. True story. And it's Friday, so unless the cleaning personel turns them off, the lights there will burn unnecessarily for 60 hours until Monday morning. This is a bit embarassing when you are doing research[1] and teaching[2] in sustainability and energy management.
So the question is, should I go there immediately and turn them off? Normally I would use my bike, but it's dark and cold outside so I consider using the car.

Let's crunch the numbers first. My car consumes about 5,5l Diesel per 100 km, so using it for a single person trip is far from contributing to a sustainable future. But the trip will save the energy that would be consumed by the office lights. The trip there and back is 11km, so this would use 0.6 l of Diesel. 1 liter of diesel contains chemical energy worth 9.85 kWh, weighs 835 g, and contains 86% carbon. This 720 g carbon would be mostly burned to CO₂, resulting in 2640 g of CO₂ [3].

Burning 0,6 l Diesel would thus generate about 1,5 kg of CO₂ and waste 5,9 kWh of energy.

What if I let the lights burn? Unfortunately the office lights are not LED-based, but they are fluorescent tubes. I would guess all together the lighting has a power consumption of 100 W. Letting them burn for 60 h would thus waste 6 kWh, basically the same value that we calculated for the used fuel.

About 3/4 of Austria's "Strom-Mix" come from hydropower, wind, waste and solar sources, the remaining part from fossil fuels like gas, oil and coal. I'm lucky that Austria has no nuclear power, first because it is a dangerous technology and second because the effective CO₂ emissions of nuclear power are hard to estimate :-).

Coal is the worst source, it comes with 882 g CO₂ per kWh[4]. All together Austria's electric energy comes with emissions of 181 g/kWh[5]. So the 6 kWh of electrical energy from the "let's the lights burn" scenario are a bit more than 1kg - less than the scenario where I drive with the car to turn the lights off.

So I should feel bad about the environment, but at least I have my lazyness supported. I might go there by bike tomorrow :-)

Research Scholarship in the Field of Energy Management and Technology

The scholarship will support a scientific project to be done at the Alpen-Adria-Universität Klagenfurt (for example as part of a dissertation).

Applicants must

• have a completed master or diploma degree
• Austrian citizenship or analogous according to § 4 StudFG (EU citizenship)
• the average monthly additional income during the scholarship may not exceed the amount of € 679, - (net)
• not have at an active employment contract with Alpen-Adria-Universität Klagenfurt during the scholarship
• target a scientific project within the topics of the research cluster energy management and technology (e.g., smart grids) to be done at the Alpen-Adria-Universität Klagenfurt

How to apply

submit a single PDF document no later than August 16 2015 to wilfried.elmenreich@aau.at with

• project description (English, max. 3 pages)
• research methodology
• time plan
• CV publication list
• Support letter from supervisor
• Leaving certificate of the respective field of study (eg Master certificate)
• Proof of citizenship
• Affidavit that the specified income level is not exceeded

For detailed information, visit https://energy.aau.at/