Prosumer Energy Management for Optimal Utilization of Bid Fulfillment With EV Uncertainty Modeling

Abstract

This article emphasizes the operation of a microgrid for optimal utilization of its resources. A microgrid system with photovoltaic (PV) generators, electric vehicles (EVs), electrical loads, and energy storage system is considered for the present study. Bidirectional power flow from the prosumer to the grid is proposed to provide flexibility for excess energy generated/stored at the prosumer. To address the EV uncertainty, the Markov chain model is used to predict EV availability based on historical travel data of the user. EV prediction uncertainty and the PV power uncertainty are considered in the modeling of the algorithm. The aggregator moderates on behalf of prosumers as a single entity between prosumers and the grid. The aggregator takes part in energy trading by submitting bids of specific energy volume to supply or consume in the day-ahead market. The bids are made to purchase energy at minimum prices and sell energy at maximum price. If the committed bid volumes are violated, the grid utility penalizes the aggregator and restricts their participation in energy transactions. The proposed strategy considers the energy bids made by the aggregator to regulate the rate of charging/discharging of EV. The charging/discharging schedule to fulfill the energy commitments while minimizing the operational cost for optimal microgrid operation has been optimized using a novel hybrid ant colony optimization and cuckoo search technique. A comparative analysis of the proposed technique with other popular meta-heuristic techniques to validate the efficacy of the proposed technique.