A pricing game strategy with virtual prosumer guidance in community grid

Abstract

The peer‐to‐peer (P2P) energy trading model is considered to be one of the appropriate models for managing local energy trading in community grids. But free pricing mechanisms can lead to energy wastage and long response times. In order to facilitate the local consumption of renewable energy within the community, this paper proposes a pricing game strategy with virtual prosumer (VP) guidance on a P2P energy market model in community grid. To prevent market disruption caused by free pricing strategies in the P2P market and ensure the overall social benefit of the community, a VP controlled by the community microgrid manager is introduced to regulate the energy trading of the entire community. A novel and efficient prosumer trading model is proposed where the VP changes its pricing strategy to guide other prosumers to achieve Nash equilibrium and improve the internal consumption rate of new energy in the community. The proposed strategy's rationality and effectiveness are verified through case studies.

Estimation of future hydropower generation of reservoir systems used for different purposes in different regions

“…Stochastic optimization is used in developing reservoir operation models and in dealing with the uncertainties in streamflow estimation. In this process, such deterministic optimization methods as genetic programming, particle swarm optimization and discrete differential dynamic programming for extracting the reservoir operation rules by using the linear regression [15][16][17][18][19][20][21][22][23][24][25]. The reservoir inflow is considered as a stochastic process described by probability distributions, and the streamflow uncertainty is integrated into the reservoir operation model [26][27][28].…”