Market Organization of Future Energy Systems

Abstract

In collaboration with the Dutch energy grid operator Stedin, our team focuses on establishing a robust data layer within the evolving energy ecosystem. Our research explores how current trends in data collection, storage, and sharing can effectively respond to the growing needs of energy digitalization. A crucial aspect of our work evaluates the use of this data in terms of fairness, privacy, security, ethical values, and regulatory compliance. We also investigate strategies to enhance data availability and usage to meet these objectives, aiming to foster a secure, fair, and efficient energy ecosystem that aligns with both industry standards and societal values. Through these inquiries, we aim to contribute to the foundational data layer essential for a resilient and transparent energy market transition.

Keywords

Energy market, Energy Informatics, Energy Data Layer, Value of data, Mechanism design

Topic

The MODES project addresses fundamental questions surrounding the organization of the Dutch energy market to support and sustain the transition to a CO2-neutral system. A unique feature of this transition is that it involves not just re-engineering physical infrastructure and energy sources but also creating a robust data ecosystem that can enhance the energy system's flexibility, security, and accessibility. To achieve this, MODES brings together a diverse, interdisciplinary team that includes stakeholders from government, industry, network companies, energy cooperatives, and consumer groups. This collaboration ensures that the project's insights and proposed solutions are both practical and sensitive to the needs and values of all participants in the energy ecosystem.

The project’s main data-focused goal, specifically within Work Package 7 (WP7), is to design and implement a data layer within the energy ecosystem that enhances digitalization, optimizes data sharing, and aligns with evolving market and regulatory needs. Data is essential to realizing a flexible and resilient energy market, particularly as the transition increases demand for real-time insights and adaptive management. WP7 will thus address two central questions:

1. Current Data Landscape: How can current trends in data collection, storage, and sharing meet the rising demands of energy digitalization? Moreover, is this data being handled with adequate consideration for fairness, privacy, security, and regulatory compliance?
2. Optimizing Data Use: How can data availability and usage be improved to meet these objectives effectively?

Research Problem

Digitalization in the energy sector has accelerated with the growing integration of renewable energy sources, energy storage solutions, and decentralized energy generation. This evolution requires not only advanced technology but also a coherent data ecosystem that ensures the right data is available to the right stakeholders, under conditions that protect privacy and ensure regulatory compliance. However, several critical challenges stand in the way of achieving this goal:

1. Data Governance and Privacy: Ensuring fair and transparent data handling that respects user privacy while promoting the accessibility of key data to various stakeholders. Today, consumer data and network information are underutilized, with many regulatory and ethical questions remaining unresolved.
2. Data Quality and Interoperability: The fragmented nature of data sources and systems leads to challenges in integrating data across platforms. This lack of interoperability can hinder market efficiency and innovation, as system operators, consumers, and policymakers struggle to access unified, actionable data.
3. Incentive Structures for Data Sharing: There is limited motivation for consumers and companies to share data, particularly when there are perceived risks related to privacy or competitive advantage. Developing incentive mechanisms that encourage voluntary, beneficial data sharing is essential for a well-functioning digital energy market.
4. Data Prioritization: Not all data is of equal value to the energy system, so understanding which types of data provide the most significant benefits is crucial. Prioritizing data based on system impact can guide the development of a streamlined, cost-effective data-sharing framework.

These challenges underscore the research problem that WP7 addresses: how to establish an effective data governance framework that meets the operational needs of a climate-neutral energy system while ensuring that data handling aligns with values like privacy, fairness, and security.

Research Question

Building on the research problem, WP7 seeks to answer the following main research question:

How can an optimized data layer be designed to balance accessibility, privacy, and consumer engagement within the energy market, fostering a robust and adaptive data ecosystem for the Dutch energy transition?

To tackle this question comprehensively, WP7 will also address specific sub-questions:

• Data Governance: What policies and frameworks are necessary to ensure data privacy, ownership, and security while allowing seamless data flow across the energy system?
• Data Valuation and Prioritization: Which data types yield the highest value for system flexibility and consumer interaction, and how can these types be prioritized in collection and integration efforts?
• Incentives for Data Sharing: What mechanisms can be developed to encourage data sharing, both from consumers and businesses, to support system stability and inclusivity?

These questions are critical to ensuring the long-term functionality of the energy data ecosystem. Answering them will provide insights into designing a data layer that enhances the performance of the Dutch energy system, supports fair access to data, and aligns with the values of all participants in the energy transition.

Approach

Optimization, mechanism design, cooperative and non-cooperative game theory, simulation

Required profile

• The candidates should have an interest in energy systems.
• Preferred background: MSc. in Information Systems, Data Analytics, Computer Science, Economics, Operations Research, Industrial engineering, Supply Chain Management, Econometrics, Applied Mathematics, Electrical or Computer Engineering
• Excellent study record; Programming experience;
• International orientation and the capacity to speak and write in English fluently;
• Background in data science, economics, machine learning and optimization is advantageous.
• Commitment and drive to execute excellent PhD Research.

Additionally, all applicants must satisfy the school-level (ERIM) requirements that can be found here.

We encourage applicants to submit as early as possible.

If you have any questions about the formal admission requirements, please contact the ERIM doctoral office: phdadmissions@erim.eur.nl or contact Dr. Yashar Ghiassi-Farrokhfal (y.ghiassi@rsm.nl) or Dr Sameer Mehta (mehta@rsm.nl).

Expected output

Scholar publications. The project aims to publish the results of the research in the top journals in information systems and operations management.You will develop research papers that can be published in top-tier information systems and management journals, such as Management Science, MIS Quarterly, and Information Systems Research. BIM faculty at RSM has a strong publication record in these journals. The final results of the Ph.D. are also published in a Ph.D. dissertation. Most BIM Ph.D. students will be able to publish multiple papers in these top journals.

Project deliverables: There are some project deliverables that are mostly aligned with the scholary publications but still need to be submitted to the project.

Cooperation

The consortium includes stakeholders from government, industry, network companies, energy cooperatives, and consumer groups. This collaboration ensures that the project's insights and proposed solutions are both practical and sensitive to the needs and values of all participants in the energy ecosystem. In particular, the PhD student working in WP7 will cooperate closely with the local grid operator (StedIn) and additionally will strengthen his/her academic expertise with interdisciplinary research collaborations with other university partners such as TUDelft, Utrecht, and TUEindhoven.

Additionally, we closely collaborate with world-class energy researchers from top schools such as London Business School, U of Cambridge, U of Texas-Dallas, Hong-kong business school, KIT, KTH, etc. We are also part of three energy institutes: Erasmus Center for Energy Transition (ECET), Center for Energy System Intelligence (CESI) -a coalition between Eramus Uni and TUDelft) and Smart and Sustainable Energy at Erasmus Center for Data Analytics (ECDA). Each of these gives us great exposure and opportunities. Furthermore, to strengthen your international profile, we strongly encourage our Ph.D. students to go abroad for a research visit during their third or fourth year at one of the top universities for 3 to 6 months. Past destinations include MIT, London Business School, University of Maryland, University of Minnesota, Carnegie Mellon University, and University of California, Berkeley.

Societal relevance

Our work package explores the use of data and digitalization to enhance energy systems, focusing on social implications like data accessibility, privacy, and consumer engagement in data sharing. By addressing how data can improve energy efficiency and support consumer empowerment, the package directly tackles issues pertinent to energy transitions in society. These include creating a balance between effective data usage and maintaining consumer privacy, thereby fostering transparency and inclusiveness in the evolving energy landscape. This societal relevance is further highlighted by our focus on data prioritization, where essential types of data are identified for public availability, benefiting consumers and stakeholders during the energy transition​.

Scientific relevance

Our work package adds to the field of energy data management by developing models that assess data utility across various phases of the energy transition. This involves pioneering mechanism design and information modeling that optimizes data accessibility while maintaining system robustness and consumer privacy. The analytical framework and simulations will offer scientific insights into designing incentive mechanisms for data-sharing models that are fair and interoperable, thus contributing to broader research on sustainable data governance and digital infrastructure in the energy sector.

Literature references & data sources

European Commission (2022) Digitalising the energy system - EU action plan URL : https://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:52022DC0552

European Comission (2022) Comssion staff working document. URL: https://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:52022SC0341

Jianxiao Wang, et al. (2023) Data sharing in energy systems, Advances in Applied Energy,

Volume 10,100132, URL: https://doi.org/10.1016/j.adapen.2023.100132.

Employment conditions

ERIM offers fully-funded and salaried PhD positions, which means that accepted PhD candidates become employees (promovendi) of Erasmus University Rotterdam. Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities (CAO).

Erasmus University Rotterdam aspires to be an equitable and inclusive community. We nurture an open culture, where everyone is supported to fulfil their full potential. We see inclusivity of talent as the basis of our successes, and the diversity of perspectives and people as a highly valued outcome. EUR provides equal opportunities to all employees and applicants regardless of gender identity or expression, sexual orientation, religion, ethnicity, age, neurodiversity, functional impairment, citizenship, or any other aspect which makes them unique. We look forward to welcoming you to our community.

Contact information

For questions regarding the PhD application and selection procedure, please check the Admissions or send us an e-mail via phdadmissions@erim.eur.nl.