PhD Position (Research and Teaching Assistant) in Smart Grids

The Smart Grids Group at the Institute of Networked and Embedded Systems of Alpen-Adria-Universität Klagenfurt has an opening for a research and teaching staff member position (“Universitätsassistent/in”). The start of employment is soonest with a contract duration of four years.

Your work will comprise:

• Research in the field of energy informatics with emphasis on state-of-the-art methods for smart microgrids
• Independent research with the aim to submit a dissertation
• Teaching in the field of electrical and computer engineering (e.g. “Smart Grid Lab” and “Circuit Systems”)
• Participation in administrative and organizational tasks of the Institute
• Student mentoring
• Assistance in public relations activities of institute and faculty

The Smart Grids Group led by Professor Wilfried Elmenreich works on the design, modeling, and analysis of solutions for future energy applications. Big challenges like the transition of our energy system to a smart, low-carbon emitting approach require an interdisciplinary research approach. The group, composed of engineers, computer scientists, and physicists is engaged in research on self-organizing systems, complex systems, communication networks and computational intelligence for this purpose.

Our team is very international and dedicated to quality research and teaching. The offices and laboratories are located in the well-equipped Lakeside Science & Technology Park. Working language is English. The Institute cooperates with national and international partners in research and industry. It is part of the research cluster Lakeside Labs (self-organizing networked systems) and the European Erasmus-Mundus Doctoral College (interactive and cognitive systems).

Required Qualifications:

• A university degree (Master or Diplom-Ingenieur) in the field of electrical engineering, computer engineering, communications engineering, power engineering, or physics graded with “good” or better
• Fluent in written and spoken English
• Experience in two or more of the following fields: energy informatics, power engineering, communication protocols, artificial intelligence, renewable energy generation, complex systems
• Good programing skills in C, Java or Python

Additional Qualifications

• Good social and communicative competences
• Basic knowledge of German
• First relevant scientific publications
• Relevant international experience

This position serves to enhance the expertise and scientific education of graduates of a Master or Diploma study program and aims at completing a PhD in Technical Sciences. Applications of people who already have a respective PhD cannot be considered.
The university strives at raising the number of female scientific staff members and therefore specifically invites women to apply. In case of equal qualifications, women will receive priority consideration.

Handicapped persons or persons with chronic illnesses who comply with the qualification criteria mentioned are specifically invited to apply.

The annual gross salary is € 2.022,40 (30 hours weekly according to Uni-KV: B1). It is intended to complement this with a 10 hours project contract depending on availability of funds.

Your application has to be uploaded before August 10 with the Human Resource Department at the University of Klagenfurt, reference 448/16. Please take the time to complete the online application form carefully, providing as much detail as possible. Once you have completed the form, please upload your application documents (cover letter, curriculum vitae, written documents, certificates, official records).

Further information can be obtained from Professor Wilfried Elmenreich (Tel.: +43-463-2700-3649).

Travel expenses in connection with the application procedure cannot be reimbursed.
The call for applicants is conformable to § 107 Abs. 1 Universitätsgesetz 2002. The official announcement in German language can be found in the Mitteilungsblatt 23_2015_2016.

Interoperability Between Smart and Legacy Devices in Energy Management Systems

Energy management systems can help to decrease energy consumption by giving user feedback or by directly controlling devices. Smart appliances create a network of devices that can be addressed and controlled via a defined network interface. However, legacy devices will establish a significant portion of a system’s power consumption and, therefore, need to be included into the management system. We propose an open architecture to integrate smart and non-smart devices by using smart plugs and non-intrusive load monitoring methods. Devices are connected either as (i) smart appliances via a fieldbus or wireless network, (ii) legacy devices connected to a smart plug, or (iii) other legacy devices being detected from a time sequence of power consumption values, which are disaggregated into the power draws of different devices. At a service layer, device properties are presented in a unified way including a machine-readable description of their features and properties. The data layer provides an abstract representation of data and functionalities. It connects to the application layer where different applications can access the data. The system supports mechanism for service discovery, service coordination, and service and resource description.

Paper:
D. Egarter, A. Monacchi, T. Khatib, and W. Elmenreich. Integration of legacy appliances into home energy management systems. Journal of Ambient Intelligence and Humanized Computing, 2015.

My talk at Workshop Energieinformatik 45. GI-Jahrestagung "Informatik, Energie und Umwelt":

Slides from Wilfried Elmenreich

Evolving a Self-organizing Energy Market for Microgrids

Graphical user interface of the FREVO plugin

Andrea Monacchi and Wilfried Elmenreich went to Zurich to present their paper about a home energy market simulator at Energieinformatik '2014.
In the presented work, self-organizing behavior between prosumers is implemented at device level via market-based energy allocation solutions. The approach is implemented in a simulator extension to the open framework FREVO, which is released for open use. With the help of FREVO, artificial neural network controllers for energy prosumers are designed using an evolutionary algorithm. Minimizing individual and overall running costs enables a better use of local energy production from renewable sources, while considering residents' necessities to minimize discomfort.

• Andrea Monacchi, Sergii Zhevzhyk, Wilfried Elmenreich. HEMS: A Home Energy Market Simulator. Energieinformatik. Zurich, November 2014.

HEMS: A Home Energy Market Simulator from Andrea Monacchi

Quick intro to the Open Source Renewables Alternative Power System Simulation (RAPSim)

In a previous blogpost, we introduced RAPSim, a free open source power system simulator with a graphical interface. RAPSim was developed at the Alpen-Adria-Universität Klagenfurt within the Lakeside Labs project Smart Microgrid. The main architect of RAPSim, Manfred Rabl-Pöchacker now produced video giving an ultra-fast introduction to the tool. Got three minutes? Here is the video:



Interested? RAPSim can be freely downloaded at rapsim.sourceforge.net.
If you want to learn more about RAPSim, here is a paper about RAPSim:

M. Pöchacker, T. Khatib, and W. Elmenreich. The microgrid simulation tool RAPSim: Description and case study. In Proceedings of the IEEE Innovative Smart Grid Technologies Asia (ISGT-ASIA'14), Kuala Lumpur, Malaysia, 2014. IEEE.

The Renewable Alternative Power System Simulator - RAPSim

An open simulation software for Micro Grids

It is not necessary to stress all the challenges that come allong with wide range integration of renewables into the power grid at this article. You easily find this somewhere else, in this blog or at another source in the web. But I want to focus your attention on a tool that can help to deal with this challenges and work torwards solutions. It is a lot on matching climate dependent production with the personal demand which is currently noticed only in average. The various influences on residential load profiles are diverse and include weather conditions, availability of other resources, personal habits and also social phenomenas. This variaty is a reason why Marija Ilic speaks of just-in-time and just-in-place services in the conntext of Smart Micro Grids. 

Developing of or researching on such services requires a flexible simulation tool with possibly high usability. This is exactly what RAPSim is aiming at. RAPSim has been developed at the Alpen-Adria-Universität Klagenfurt within the Lakeside Labs project Smart Microgrid and was presented in front of interested audience at the ISGT Asia - 2014 conference in Kuala Lumpur in May 2014. Since then the software project is downloadable for free at Sourceforge.net. 

Connected Smart Grid Objects 

The simulation field is a lattice where the user designs a scenario by placing different "grid objects", e.g., houses, wind turbines, PV panels, etc. Each of the objects can have a model which does all the inner-object calculations. Algorithms handle grid-wide interactions. User-defined models can extend  algorithms for the grid and/or models for the grid objects. RAPSim provides the interface with following functions:

• A graphical interface to create the intended scenarios and to control the simulator functions.
• Functions to save and load simulation scenarios in a generic xml format.
• A time thread that models time of day and day of the year and handles up to minute resolution.
• Generation of output files in csv-format. Object parameters can be selected to be written into a file at each time step.
• Weather simulation which can be done via stochastic models or simulated by measured data.
• Topological grid analysis that collects objects of the same bus in a list and aggregates their parameter values.
• Administration of algorithms for grid-wide calculations.
• Administration of object specific models that can be easily implemented by the user.

The software is written in Java and provided with the source code so that it can be imported into a Java IDE such as eclipse. The development of the software is still ongoing. Try it out and give us feedback by adding a comment or sending a ticket to helps us to further improve it. Please spread the news about the tool, while we will do the best on our part so that onces RAPSim may become a synonym for rapid simulation in the field of mirco grids.
Once more here the link to the sourceforge page.

Publications on RAPSim (with links to fulltext PDF):

M. Pöchacker, T. Khatib, and W. Elmenreich. The microgrid simulation tool RAPSim: Description and case study. In Proceedings of the IEEE Innovative Smart Grid Technologies Asia (ISGT-ASIA'14), Kuala Lumpur, Malaysia, 2014. IEEE.

 

Energiewende - the Game

"Energiewende" is a computer game about the transition of our energy system from fossil fuels to renewable and sustainable energy sources. The game was developed by Manuel Herold, Matija Kucko, Andrea Monacchi, John N. A. Brown, and Wilfried Elmenreich as contribution to the CROSMOS GameJam. At this event teams had to develop a computer game to a topic just revealed at the contest in just two days - 2014 the topic was related to the services of Stadtwerke Klagenfurt. 

The game Energiewende let's you try out the strategic and tactical aspects of an electrical energy system that is mostly powered by renewable energy sources. Unlike a coal power plant, photovoltaic or wind power plants cannot save fuel in times of low load for using it later. Therefore, it is necessary to plan the distribution and placement of power plants well according to the expected power demands of their users - in the game they are modeled as houses with an energy consumption behavior of typical households. After placing power plants and transmission lines, the game features a real-time mode, where your system is simulated throughout three phases of a day (night/morning, daytime, evening). In case there is not enough energy in one phase, you must prevent a blackout (otherwise you loose the game) by balancing the grid. This is done by turning off devices in the houses. But be aware - user might not like this, especially if you turn off a device the user was about to use right now. A "complain-o-meter" is showing the aggregated dislikings of the users - once the complain-o-meter runs over, the game is lost.
Thus, one learns also about the typical consumption of devices and their potential for balancing the grid. The method shown in the game called demand response is currently a frequently discussed method for the future smart grid.

Got everything? Try out the game by clicking the image above. Have fun!

Wind power or photovoltaics?

Wind power is an interesting option for producing renewable energy. In contrast to Photovoltaics, wind generated energy costs less but it requires transmission infracstructure between wind parks and the consumers.Germany has more than 32 GW of installed wind power capacity and is now building transmission lines to transport the energy to the south.

How predictable is wind in comparison to PV output? The yield of both depend on some meterological factors which are hard to predict. However there is one big difference: you can easily calculate the maximum amount of solar intensity that your PV system has to cope with. With wind speed, it is hard to define a maximum possible wind speed, since on rare occasions wind speed can be significantly higher than the expected value.

Which could be dangerous: If the generator spins faster and faster, large forces produced could cause a wind turbine to self destruct:

Luckily, todays wind turbines have an overspeed control (a braking or featherin mechanism) and a cut-out mode. Still, I don't want them in my garden :-)

Open position for an Associate Professor at the Faculty of Electrical Engineering and Information Technology at Vienna University of Technology

The Faculty of Electrical Engineering and Information Technology of Vienna University of Technology invites applications at the Institute of Energy Systems and Electrical Drives for a Tenure track position with qualification agreement for associate professor in the area of Electrical Energy Distribution Systems in form of a initially fixed-term (6 years) tenure track position starting from 01.04.2014. Research areas to be independently covered are automated distribution system operation including information and communication technologies (Smart Grids), integration of renewable and distributed energy resources into the energy system, electro-mobility, Microgrids as well as protection technology. The successful candidate is expected to initiate independent, creative research programs and to establish an own research group.
A strong emphasis is placed on the broad fields of planning, modeling, simulating and analyzing electrical energy distribution systems as well as the integration of decentralized renewable energy resources, hybrid energy storage systems and application of information and communication technologies for automated distribution system operation.
The following requirements for applications to this position exist. The successful candidate is expected to be an internationally recognized scientist with a PhD relevant to the field and perennial experience in one or several of the following research areas:
- Impact of distributed energy resources on distribution system operation and protection
- Integration of decentralized renewable energy resources and distributed storage into the energy system
- Integration of electro-mobility into the energy system
- Application of information and communication technology in energy distribution systems
- Reliability, resilience and island capability of energy distribution systems
- Real time simulation of energy distribution systems and Microgrids
and experience and commitment to excellence in teaching and supervision of undergraduate, graduate and PhD students.
The successful candidate is expected to participate in teaching according to the curricula of the faculty of electrical engineering and information technology and to establish an own research group.
Salaries and benefits of the tenure track position are according to collective labor agreement for employees at universities, salary group B1, based on 40 hours per week, and a monthly minimum salary of currently € 3.411,70 (14 times per year). After signature of the qualification agreement salaries and benefits are raised to salary group A2 and thus monthly € 4.034,70 (14 times per year).
Applications should include curriculum vitae, list of publications, copies of 5 most relevant publications, list of successful grant applications, and list of teaching experience. Applications should be directed to the Dean of the Faculty of Electrical Engineering and Information Technology of Vienna University of Technology, Erzherzog Johann Platz 1, 1040 Wien, Austria. Applications should include a CD-ROM with an electronic version of the complete application documents. Candidate evaluation will begin on 04.01.2014.
Candidates are not eligible for a refund of expenses for travelling and lodging related to the application process.

EvoENERGY - Evolutionary Algorithms in Energy Applications @EvoStar 2013, Vienna

EvoStar comprises several co-located conferences on the topic of evolutionary computing. The track of EvoENERGY contained five paper presentations of interesting ideas for the Smart Grid.

Ana Soares from the University of Coimbra presented her work on "Domestic Load Scheduling Using Genetic Algorithms" where a Genetic Algorithm is used to optimize for an objective function considering energy consumption, end user preferences, peak power, and presently available energy. Encoding of solutions was done as string of integers where the recombination was done by a bit mask over the integer string (so no typical crossover). The evolved results define scheduling of loads from household appliances in order to fulfill the above defined objectives.

Stephan Hutterer from FH Hagenberg approached the optimal power flow problem with an evolutionary algorithm. Optimal control policies are learned offline for a given power grid resulting in general abstract rules for optimal power flow.

"Prediction is difficult, especially of the future" (Nils Bohr) - the prediction of power load profiles can be improved with the approach presented by Frédéric Krüger from the Université de Strasbourg. They show how a genetic algorithm generated with the EAsy Specification of Evolutionary Algorithms (EASEA) language can be applied to solve a noisy blind source separation problem and create accurate power load profiles using real world data.

Another approach for forecasting electrical consumption was presented by Martina Friese and Oliver Flasch from FH Köln in his talk on "Comparing Ensemble-Based Forecasting Methods for Smart-Metering Data". They apply state-of-the-art time-series forecasting methods to electrical energy consumption data recorded by smart meters and show that genetic programming is an attractive alternative to custom-built approaches for electrical energy consumption forecasting.

Dominik Egarter from Alpen-Adria-Universität Klagenfurt presented the paper "Evolving Non-Intrusive Load Monitoring" [PDF]. Here, an evolutionary algorithm is used to determine a set of devices for a given load curve - in other words, your smart meter knows what devices you have on even if they are not smart. The work on evolving non-intrusive load monitoring shows the capabilities of the approach but also its limits. The latter basically tell you how much you have to masquerade your power profile so that it does not give away information about the devices that constituted it. See also this blog article on Dominik's work.

Open-Source Energy Monitoring Hardware

OpenEnergyMonitor hardware: raspberry pi, emonTX
 and emonGLCD

In our smart microgrid laboratory at the Alpen-Adria-Universität Klagenfurt we need to be able to measure energy flows at different places in the network. Our criteria had been to be able to measure power, current, and voltage with adjustable measurement time intervals. The meters should be networked wirelessly with a visualisation possibility via an embedded device or a web page. In order to implement appropriate measurement strategies (for example measuring with a time-triggered architecture) the system should be fully programmable, in other words open-source. 

emonCMS web-app visualization tool

To meet this requirements we decided to use the OpenEnergyMonitor. It provides a metering board emonTx, which is based on Arduino and communicates to some base station. This can be either a own-built base station emonBase from OpenEnergyMonitor or the nowadays trendy Raspberry Pi. All necessary software is provided and easy to use. The OpenEnergyMonitor also provides an energy visualisation tool called emonCMS, which can be installed on the Raspberry Pi. It can be used for processing, logging and visualizing energy. Like the other software also the emonCMS is open source.

Links:

• Raspberry Pi, a credit-card-sized embedded computer running Linux
• OpenEnergyMonitor, open-source energy monitoring tools
• A. Monacchi, D. Egarter, W. Elmenreich. Integrating Households into the Smart Grid. Workshop on Modeling and Simulation of Cyber-Physical Energy Systems, Berkeley, CA, May 2013.
• W. Elmenreich, G. Bauer, and H. Kopetz. The time-triggered paradigm. In Proceedings of the Workshop on Time-Triggered and Real-Time Communication Systems, 2003.