University of Technology (TU/e, https://www.tue.nl/en/) is one of Europe’s top technological universities, situated at the heart of a most innovative high-tech region, with a wealth of collaborations with industry and academic institutes. In 2017, TU/e was ranked 15th in Europe in the Times Higher Educational World University ranking for Engineering and Technology. TU/e has around 3,000 employees and 2,300 PhD students (half of which international, representing about 70 nationalities).
Research Programme Description
The envisioned research is part of the research programme Intelligent Energy Systems (IES) performed within the Electrical Energy Systems (EES) group of TU/e. Within the IES programme, research is conducted into operation and planning of future sustainable energy systems, with an emphasis on electricity systems, markets and systems integration. This research is performed in two research labs: the Digital power and energy systems lab (EES DigiPES lab) and the Electricity markets and power system optimization lab (EES EMPDO lab). The former focuses on intelligent energy network research, including: demand management and flexibility, digital twinning, data analytics, smart grid ICT architectures and systems integration in multi energy systems. The latter specializes in electricity market design (centralized & decentralized), market products & system services to integrate new technologies, forecasting, market participation strategies and risk management, large-scale, distributed, multi-objective optimization techniques applied to energy markets and power systems and AI for optimization and control in power and energy systems. The EES group has strong ties with industry both nationally and internationally, with several part-time industry researchers working in the group and a large group of strategic collaboration partners.
Recently, the Electrical Energy Systems group received grants for four nationally-funded projects in Intelligent Electricity Systems. Therefore, this group calls for applications for five PhD positions and one Postdoctoral position. The focus of the work will be on the application of intelligent software approaches (distributed control systems, machine learning, (distributed) optimization, market mechanisms, data science, modelling & Simulation etc.), in electrical power systems (energy network planning, power systems state estimation, energy system flexibility coordination, local energy markets, capacity & congestion management, etc.).
PhD position 1: Data-driven modelling for distribution network operations
This PhD research will focus on advanced deep and reinforcement learning techniques to correlate multiple energy flexibility resources, taking geographical and physical constraints into account. Data from the energy grid and from connected devices and installations will serve as input. Classification and predictive methodologies based on federated learning and joint action learning will be developed to accurately capture dynamic behaviour of the local energy grid environment. The OPAL-RT real-time digital simulator and other parts of the TU/e digiPES Lab will be used for validation. The researcher will engage in an interdisciplinary cooperation with researchers at other universities and with key industry partners covering the full electricity value chain. This position is part of the MegaMind Research Program.
The position is supervised by dr. P.H. Nguyen, prof.dr. ir. J.G. Slootweg and dr.ir. D.C. Mocanu.
PhD position 2: Detecting & averting the abuse of market power in local electricity markets
Local electricity markets are emerging as a scalable means to integrate the increasing number of distributed assets that are connected at the MV and LV distribution systems. As a consequence, this topic has attracted a lot of attention recently and various market designs that allow direct interaction between prosumers have been proposed (e.g., local auction-based mechanisms and peer-to-peer trading schemes). Nonetheless, questions related to one of the most important aspects of electricity market design and operation have not been answered satisfactorily for the case of local electricity markets: the possibility of participants to exercise market power, allowing for market gaming and manipulation. This researcher will work on the development of a new framework based on multi-agent reinforcement learning with the purpose of stress-testing different designs of local energy markets. Extensive simulations that allow different forms of interactions among agents may reveal and prevent potentially undesirable market design exploits. The researcher will engage in an interdisciplinary cooperation with researchers at other universities and with key industry partners covering the full electricity value chain. This position is part of the MegaMind Research Program.
The position is supervised by prof.dr. B. Claessens, prof.dr. J.K. Kok and dr. N. Paterakis.
PhD position 3: Digital control coordination at the electricity grid edges
This PhD research is investigating the application of data-sharing, distributed decision making and edge computing technologies in electricity-grid-edge control, specifically through local market interactions in the context of future sustainable energy systems use cases. Data sharing technologies such as ontologies and multi-party computation (MPC) are being investigated. This research develops interaction models and edge-computing algorithms for three different settings: (1) investigate how edge computing can be used to feasibly operate market algorithms that are either computationally intensive or needing fast response times, (2) develop and compare interaction models for local markets incorporating participant-specific info such as time-dependencies in flexibility constraints and uncertainty, and (3) investigate advanced data sharing technology (such as multi-party computation, MPC) used between multiple actors mutually and with the market platform, allowing parties to shield off sensitive information while cooperating or negotiating with each other. The researcher will engage in an interdisciplinary cooperation with researchers at other universities and with key industry partners covering the full electricity value chain. This position is part of the MegaMind Research Program.
The position is supervised by prof.dr. J.K. Kok, dr. H.P. Nguyen.
PhD position 4: Digital twin models to enable optimal interactions between the electricity grids and local energy communities
The PhD candidate is expected to conduct research into the development of a virtual testing environment (for design) and digital twins (for operation) for assessing the value and profitability of communities, optimizing (system) design and developing control strategies. Based on specification of Internet-of-Energy models, integration of community and grid models will be developed to yield synchronized relevant data and scenarios for decision-making. It focuses on possible clusters of energy communities to realize viable business models by taking possible energy and market values into account. The Digi-PES lab is currently hosting a real-time digital simulator (OPAL-RT) with a power electronic interface which are an essential component to enable the digital twin platform. The additional (controllable) components, including EV charging, battery, and heat pump units, will be integrated in such hardware-in-the-loop setting. This position is part of the TROEF project.
The position is supervised by dr. H.P. Nguyen.
PhD position 5: Modelling and analysis of future flexibility coordination mechanisms in urban sustainable energy systems
In order to keep the electricity distribution grids stable, reliable and resilient while the energy transition unfolds, distribution system operators (DSOs) are expected to make use of local flexibility services (e.g. from local batteries and/or electricity producing/consuming devices) in the future. Although, it is expected that in urban environments flexibility will be utilized for local network management (congestion management, voltage regulation, etc.) from the second half of this decade and onwards, the DSOs are lacking the decision tools to make well-substantiated decisions when, where and how to use locally sourced flexibility. As a PhD researcher, you will
(1) detail realistic scenarios for use of flexibility in archetypical urban areas, (2) design and implement relevant flexibility models and flexibility coordination mechanisms in their full context, building forth on existing co-simulation tools, (3) perform an extensive simulation study to analyse and compare the merits of the implemented flex-mechanisms. For this position good communication skills in the Dutch language are required. This position will be part of the GO-E project.
The position is supervised by prof. dr. J.K. Kok and dr. ir. J.G. Slootweg.
PostDoc position: Research methods and simulation tooling for urban sustainable energy systems operation and planning
The postdoc will actively collaborate with the PhD candidate of PhD Position 6 as listed above and with external project partners in an integrating role. Goal of this postdoctoral project is to develop a research methodology to investigate both the operation and planning of future urban sustainable energy systems based on simulation tooling. Further development of co-simulation knowledge, models and tooling to support the methodology is part of the research. The demonstration and validation of the methodology will be done in cooperation with the PhD researcher (for systems operation) and external industry and knowledge partners (for systems planning). For this position good communication skills in the Dutch language are required. This position will be part of the GO-E project.
The position is supervised by prof.dr. J.K. Kok and dr.ir. J.G. Slootweg.
All PhD researchers and the Postdoc will work in close collaboration with experts and researchers from external industry and knowledge institutes, including the three main Dutch Distribution System Operators, energy sector service and technology providers, consultancy firms, applied research institutes and (technical) universities. All projects strive to make tangible steps in the energy transition for maximum societal impact. The projects are interdisciplinary in nature, combining the state-of-the-art in power systems engineering, computer science, mathematics and/or energy law and regulation.
We are looking for highly motivated and pro-active candidates with very good English proficiency. PhD candidates need to have obtained a relevant master degree (Electrical Engineering, Computer Engineering, Informatics or Applied Mathematics, - ideally with a focus on Intelligent Energy Systems) with excellent grades. Postdoc candidates must have a relevant PhD degree and excellent communicative skills. For PhD Position 5 and the Postdoc position good communication skills in the Dutch language are required. Candidates must have strong analytical skills, affinity for formal and simulation models, algorithmic solutions, as well as software engineering practices and good programming skills. Candidates must be keen to work with external industrial and academic partners.
Specific for a PhD position:
Specific for a Postdoc position:
Do you recognize yourself in this profile and would you like to know more? For more information about the advertised positions, please contact:
Prof.dr. J.K. Kok, j.k.kok[at]tue.nl
Dr. H.P. Nguyen, P.Nguyen.Hong[at]tue.nl
Dr. N. Paterakis, N.Paterakis[at]tue.nl
For information concerning employment conditions click here.
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