Xiaoming Kan

Bio

Country of origin: China 
Host University: Chalmers University of Technology
Main supervisor: Frederik Hedenus
Industry partners: Engie (Netherlands), Europa-Universität Flensburg (Germany)

Abstract

The overall aim of this ESR project is to develop a power system model that can represent and accurately analyze a power system dominated by variable renewables. The model will be adopted to assess what investment and variation management strategies would be cost-effective to use for a renewable power system in the North Sea Region. The model will be developed by primarily using an optimization approach to analyze the power system. The first case study will focus on hydro storage in the Nordic Region and deployment of wind resources for a smoother production. The second case study will investigate the role of demand side management and power to fuel to fulfill the objective of variation management. On the second stage of the research, both optimization approach and agent-based modelling will be used to conduct comparison study on the optimal investments for the future renewable power system. In the industry partner Engie, I will learn the investment models and analysis tools used by companies and work together with industry experts to compare modelling tools from applied perspective.

Project objective: expected results and contribution to society

In this project, a general framework and modelling tool with high temporal and spatial resolution to assess renewable power system for the North Sea Region will be designed. The following key research questions will be investigated in detail. 

1. How will social acceptance and geographical limits of transmission capacity expansion affect the renewable power system;
2. How will hydro storage in Nordic Region contribute to balancing the variability in the North Sea Region if it is possible to add pumps and turbines to the existing reservoirs;
3. What is the potential role of power to hydrogen in a renewable power system.

The outcome of the research will contribute to better understanding of optimal investment and variation management strategies that are robust for a cost-effective power system based on variable renewables in the North Sea Region given large uncertainty of future costs and performance.