PhD Position on Unlocking Flexibility in Electricity Markets via Model-Predictive Control

Do you want to work on next generation decision-support tools for battery operators? Do you have solid quantitative and analytical skills that you want to develop further in an international setting?

PhD Position on Unlocking Flexibility in Electricity Markets via Model-Predictive Control

Battery storage systems form a pivotal complement to wind and solar power in climate-neutral power systems. They can deliver a range of services, ranging from arbitrage (charging the system during low-price periods and discharging during high price periods) to congestion management and system services. Extracting all benefits from these assets, which becomes ever more important as more batteries enter the power system, requires state-of-the-art decision support tools. These mathematical models help battery owners make strategic decisions, such as when to charge and discharge or on which electricity markets to focus.

In this PhD trajectory, we focus on a key challenge in this domain: the design of next generation decision support tools for battery operators, focusing on the participation in multiple consecutive short-term electricity markets and congestion management. To address this question, you will develop state-of-the-art model predictive control tools to guide market participation decisions. Starting from existing models, you will first focus on hedging decisions with respect to the uncertainty on the battery model itself. To this end, you will explore concepts such as distributionally robust chance constrained optimization. Second, you will explore how data-driven models capturing the state-of-health and degradation can be integrated in the battery model. You will develop these machine learning-based proxies together with a postdoctoral researcher working in this project, leveraging data from experiments in our project. Third, you will explore how local connection capacity markets and novel connection agreements can be integrated in the decision support tool and how these affect the battery owner’s business case.

This PhD position is funded under the BATT-AI project, funded by NWO. You will work closely together with other researchers at TU Delft (supervised by Pedro Vergara and Zian Qin) and the University of Twente (supervised by Nataly Banol Arias), as well as our industrial partners: Stedin, Entrnce, Eneco, Kyos Energy Consulting and Alfen. Your daily supervisor and promotor will be Kenneth Bruninx. You will build on existing expertise and models on battery modelling and short-term electricity market participation. You will join a lively community of internationally renowned interdisciplinary energy researchers in the Department of Engineering Systems and Services at TU Delft. Our faculty hosts a diverse group of people from different countries and disciplines, and we welcome candidates that contribute to and enjoy this diversity.

Job Requirements

You must be able to demonstrate:

• Master’s degree in science, engineering or economics (must have been awarded by the agreed-upon starting date of the PhD).
• Strong quantitative and analytical skills.
• Very good written and spoken communication skills in English (Dutch is not required).

Bonus points if you have:

• Programming experience in Julia, Python or a similar language.
• Taken courses in Operations Research or Model Predictive Control.
• Prior research experience, especially in energy system/market modelling or other energy-related research.

About TU Delft (Delft University of Technology)

Delft University of Technology is built on strong foundations. As creators of the world-famous Dutch waterworks and pioneers in biotech, TU Delft is a top international university combining science, engineering and design. It delivers world class results in education, research and innovation to address challenges in the areas of energy, climate, mobility, health and digital society. For generations, our engineers have proven to be entrepreneurial problem-solvers, both in business and in a social context.

Faculty Technology, Policy & Management

The Faculty of TPM provides an important contribution to solving complex technical-social issues, such as energy transition, mobility, digitalisation, water management and (cyber) security. TPM does this with its excellent education and research at the intersection of technology, society and policy. We combine insights from both engineering and social sciences as well as the humanities. TPM develops robust models and designs, is internationally oriented and has an extensive network of knowledge institutions, companies, social organisations and governments.

Conditions of Employment

Doctoral candidates will be offered a 4-year period of employment in principle, but in the form of 2 employment contracts. An initial 1.5 year contract with an official go/no go progress assessment within 15 months, followed by an additional contract for the remaining 2.5 years assuming everything goes well and performance requirements are met. Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from €3059 per month in the first year to €3881 in the fourth year.

As a PhD candidate you will be enrolled in the TU Delft Graduate School. The TU Delft Graduate School provides an inspiring research environment with an excellent team of supervisors, academic staff and a mentor. The Doctoral Education Programme is aimed at developing your transferable, discipline-related and research skills. The TU Delft offers a customisable compensation package, discounts on health insurance, and a monthly work costs contribution. Flexible work schedules can be arranged.

If you need to relocate to the Netherlands for this job, TU Delft is committed to making your move as smooth as possible! The HR unit offers information to help you prepare your relocation. In addition, events are organised to help you settle in the Netherlands, and expand your (social) network in Delft. A Dual Career Programme is available, to support your accompanying partner with their job search in the Netherlands.

Additional Information

For more information about this vacancy, please contact Kenneth Bruninx (k.bruninx@tudelft.nl). No applications by email.

Doing a PhD at TU Delft requires English proficiency at a certain level to ensure that the candidate is able to communicate and interact well, participate in English-taught Doctoral Education courses, and write scientific articles and a final thesis. For more details please check the Graduate Schools Admission Requirements.

Please note:

• A pre-employment screening can be part of the selection procedure.
• As part of knowledge security, TU Delft conducts a risk assessment during the recruitment of personnel. We do this, among other things, to prevent the unwanted transfer of sensitive knowledge and technology. The assessment is based on information provided by the candidates themselves, such as their motivation letter and CV, and takes place at the final stages of the selection process. When the outcome of the assessment is negative, the candidate will be informed. The processing of personal data in the context of the risk assessment is carried out on the legal basis of the GDPR: performing a public task in the public interest.
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