Planning and Operation of Demand-Side Flexibility
Time: Wed 2019-11-06 10.00
Subject area: Electrical Engineering
Doctoral student: Meng Song , Elkraftteknik
Opponent: Doctor Alessandra Parisio, The University of Manchester
Supervisor: Mikael Amelin, Elkraftteknik, Signaler, sensorer och system, Elektrotekniska system, Elkraftteknik
Power systems are changing with growing penetration of non-dispatchable renewable generation and increased demand of electric energy. More generation, transmission or distribution capacities are needed to balance the varying production and higher consumption. Demand-side flexibility is a potential solutionto tackle those challenges. By shifting the consumption time and temporarily increase or decrease the power demand, the demand-side flexibility can help to integrate more wind and solar energy in the system, alleviate network congestion and postpone the investment for grid reinforcement. Therefore, technical and regulatory measures are undergoing in many countries to encourage demand response and engage customers.
On the other hand, unlocking the flexibility will introduce more complexityand uncertainty on demand side. This would result in difficulties for different actors in power systems and power markets to make optimal decisionsin their planning and operation. The thesis addresses the problem by proposing methods to support the decision making of actors on demand side. Firstly, it develops models to facilitate residential customers and commercial electric vehicle fleet operators scheduling their shiftable appliances for reducing electricity cost. The willingness of households for responding to time-varying price is taken into account. Results from Stockholm Royal Seaport project are analysed to demonstrate such willingness. Secondly, the thesis develops models for the short-term planning of retailers and balance responsible players. Different approaches are deployed under price-taker and price-maker assumptions respectively. The planning concerns the price sensitivityof end customers and the risk related with certain bidding strategies.Thirdly, the thesis proposes models to coordinate and aggregate the flexible charging power of electric vehicles to provide regulation service on the balancing market. The models encompass the decision process from day-aheadplanning to real-time operation management. The proposed models in the thesis are based on the rules of Nordic electricity market and could be further developed for adapting to other market frameworks. Stochastic programmingis applied to address the uncertainties about consumption and market behaviours.In addition, the thesis discusses the impacts of demand response interms of generation cost, system reliability and market price. It shows that a widely implemented demand response can reduce the total generation cost, improve the reliability of supply and decrease the market price.