A novel real-time pricing for optimal DRP, considering price elasticity, and charging control methods of PHEV integrated with smart grids, using GMO algorithm

Abstract

With the development of smart grids, optimizing the performance of response programs in the distribution system in operation and development, held special importance. This paper proposes an optimized method for demand response management in smart grids using real-time pricing. The method involves defining an acceptable consumption pattern and energy price through consumer-utility interaction. For more evaluation, six scenarios are defined that considered different states of energy pricing with and without the Plug-In Electric Vehicles (PHEVs) The first step establishes the demand response with real-time pricing, determining hourly load and energy prices. Price elasticity of demand is employed to gauge consumer load response to energy prices. The second step utilizes the Geometric Mean Optimizer (GMO) to optimize Demand Response Programs (DRPs) for consumers with smart programmable meters. The proposed method is tested on the IEEE-69 bus distribution network under various scenarios, demonstrating its effectiveness under 48 h. Additionally, the study investigates the impact of PHEVs and their controlled charging using the integrated three-tariff method and real-time electricity pricing. The results of the GMO algorithm are also compared with other methods to validate its advantages. The results indicate enhanced voltage profiles and reduced reactive power consumption during peak hours about 4.5% and 23%, respectively. in addition, the load factor by applying the proposed method is increased by about 18%. Moreover, the proposed method by combining the three-tariff method enables the transformer to supply approximately 60% of EVs without overloading, which is 40% more than that case without the three-tariff method.