Multi-objective Clearing of Reactive Power Market Including Plug-in Hybrid Electric Vehicle

Abstract

In this article, a multi-objective framework is proposed for reactive power market clearing with the presence of plug-in hybrid electric vehicles. The proposed multi-objective framework can concurrently optimize competing objective functions, including the total payment function of plug-in hybrid electric vehicles and generators and total grid losses. The total payment function is the payment paid to the plug-in hybrid electric vehicles and generators for their reactive power compensation. To calculate the vehicle's payment, the capability curve of the plug-in hybrid electric vehicle is first extracted, and after that, the expected payment function of the vehicle is proposed based on its capability curve. The problem of reactive power market clearing is solved by implementing multi-objective particle swarm optimization. The best compromise solution is chosen according to the specific preference among various non-dominated (Pareto optimal) solutions on a fuzzy approach basis. The effectiveness of the proposed method is examined based on a typical 17-node microgrid test system.

Keywords:

• plug-in hybrid electric vehicle
• reactive power market
• total payment function
• multi-objective particle swarm optimization
• plug-in hybrid electric vehicle capability curve