Local energy systems

Sustainable energy transition aims to develop low-carbon, reliable, secure and affordable energy systems. Local energy systems (LESs) are a promising solution. LES can take advantage of decentralised renewable resources and can lead to, e.g., increased reliability, flexibility, resilience, and security of supply of the energy system. Moreover new business models emerge around peer-to-peer energy services. However, there are also some technical challenges concerning the design of LES, development, retrofit of existing buildings within a LES, management and regulation. One of the main challenges from the social perspective are the large number of different stakeholders and the complex interactions between these stakeholders when cooperating and competing in a LES. Dynamic pricing strategies and incentive policies are crucial to facilitate the collaboration.
This project focuses on revealing several cooperation and competition mechanisms among the stakeholders through literature review and theoretical analysis. Game theory is introduced to optimise the dynamic pricing and incentive policies according to the revealed behavior mechanisms. From the technical perspective, both social and energyrelated characteristics of stakeholders need to be considered for design optimization of buildings (including retrofits) and energy systems, and for operational optimization of LES. Effective modelling methods will be developed to describe the social and energy-related characteristics of stakeholders in LESs. The following two methods, among others, are proposed: automated machine learning-based data-driven models for energy demand/production prediction, and automated calibration-based first-principle models for component simulation of LESs. In order to capture the interactions between the stakeholders the project will develop a cyberspace for the behavior simulation of the stakeholders based on multi-agent systems. Finally, a cloud-based simulation and optimisation platform will be built, which is demonstrated for three case studies in the Netherlands and China.
Keywords: Local energy systems, Social and technical research, Energy flexibility, Low carbon, Actor integration, Actor engagement.

Project will start in mid 2022. Project duration is 4 years.

Dr. Xiao Peng
Researcher
I have completed my PhD at Rotterdam School of Management, in Erasmus University, where I practiced research methods like economic modelling and statistical analytics to support decision making for governance structure in business and management.