Two-stage stochastic micro-market model for isolated microgrids considering PEVs traffic flow

Abstract

The growing adoption of plug-in electric vehicles (PEVs) and developments of renewable energy resources (RES) in isolated microgrids (IMGs) pose various challenges to these networks. To cope with the operational problems of IMGs in the presence of PEVs, this paper proposes a comprehensive market-based energy management system (EMS), called micro-market (μM), incorporating different participants and PEVs traffic flow. The proposed model considers both vehicle-to-grid (V2G) and grid-to-vehicle (G2V) modes with different traffic behavior of parking lots (PLs) and charging stations (CSs) in an IMG market environment (including uniform electricity pricing and unit commitment). Establishing a bidirectional linearized AC (BLAC) power flow enables the μM to efficiently schedule the joint active-reactive power of all participants and provide local energy trading conditions. Moreover, the developed μM schedules the cost of joint up/downward active-reactive reserve power effectively, ensuring the IMG will be operated securely. The suggested model is a two-stage stochastic mixed integer linear programming (MILP), with the objective of maximizing social welfare (SW) for the upcoming day. The introduced model's efficacy is assessed by testing the μM in an IMG on the CIGRE medium-voltage benchmark, considering three different operational cases. The results reveal that incorporating PEVs traffic flow into the μM model increases SW by 3.7 %. However, adding battery degradation costs, while causing a 3 % reduction in the objective function, significantly enhances the model's practicality by meeting IMGs real-world operational requirements. Overall, the results verified the ability of the proposed model to address different operational challenges while the PEV owners' preferences are satisfied and secure operation is ensured.