Optimal scheduling of isolated microgrid with an electric vehicle battery swapping station in multi-stakeholder scenarios: a bi-level programming approach via real-time pricing

TL;DR

This paper presents a bi-level scheduling model for isolated microgrids with EV battery swapping stations, optimizing costs and profits through a hybrid algorithm to enhance multi-stakeholder coordination.

Contribution

It introduces a novel bi-level optimization framework and a hybrid JAYA-BBA algorithm for efficient scheduling in microgrids with EV stations under real-time pricing.

Findings

The proposed method effectively reduces microgrid net costs.

The model maximizes BSS profits under demand response.

Simulation verifies the approach's effectiveness and superiority.

Abstract

In order to coordinate the scheduling problem between an isolated microgrid (IMG) and electric vehicle battery swapping stations (BSSs) in multi-stakeholder scenarios, a new bi-level optimal scheduling model is proposed for promoting the participation of BSSs in regulating the IMG economic operation. In this model, the upper-level sub-problem is formulated to minimize the IMG net costs, while the lower-level aims to maximize the profits of the BSS under real-time pricing environments determined by demand responses in the upper-level decision. To solve the model, a hybrid algorithm, called JAYA-BBA, is put forward by combining a real/integer-coded JAYA algorithm and the branch and bound algorithm (BBA), in which the JAYA and BBA are respectively employed to address the upper- and lower- level sub-problems, and the bi-level model is eventually solved through alternate iterations between the two levels. The simulation results on a microgrid test system verify the effectiveness and superiority of the presented approach.