A Stackelberg Game Based Optimization Method for Heterogeneous Building Aggregations in Local Energy Markets

Abstract

This paper proposes an optimal operational method and a customized pricing strategy for a Microgrid (MG) incorporating heterogeneous buildings from different communities in a local energy market (LEM). A customized pricing strategy in the LEM for the heterogeneous building aggregations (BAs) is proposed considering their heterogeneous insulation performances. In this regard, a hierarchical framework with two levels for optimal decision-making of the MG as the price maker and BAs as the price takers in the LEM are presented. At the upper level, the MG aims to maximize its profit by optimizing the customized prices and its energy schedules. At the lower level, a detailed physical model of the building with adjustable heating, ventilation, and air conditioning (HVAC) systems is developed while considering the building's thermal dynamics. The objective of each BA in each community is to minimize its operating cost while ensuring the users' thermal comfort according to MG's prices. The Stackelberg game is used to model the interactions between the MG (leader) as the price maker and multiple heterogeneous BAs (followers) as the price takers in the LEM. Then, the proposed optimization model is converted into a mixed integer linear programming using the Karush-Kuhn-Tucker conditions and strong duality theorem. Numerical results show that the hierarchical method benefits both the MG and heterogeneous BAs with customized pricing schemes. The HVAC of the building with good thermal insulation performance can make more adjustments to indoor temperature to reduce its operating costs. Moreover, it has a more significant impact on MG's electricity prices.