Scheduling of virtual power plant with high penetration of distributed generation

Abstract

The Virtual Power Plant (VPP) is eyed as a solution to the complexities and drawbacks caused by the accelerating penetration of DGs. To actualize the concept of the VPP coordinating the smaller and diverse energy resources, sophisticated planning and scheduling is required. With a large amount of information to take into account, the possible number of solutions and the complex strategies for the dispatch of generation will be very hard to conceive. In this research, a cooperative coevolution genetic algorithm was used for an optimized electrical and thermal day-ahead hourly scheduling of a Virtual Power Plant that consists of distributed generators including CHPs, solar power plants, energy storages and dispatchable loads. The algorithm allows the handling of a VPP with diverse resources and provides very good decision support to the VPP operator.