Optimized scheduling of ensemble home energy resources for effective utilization under demand response program

Abstract

Demand Response (DR) Programs have demonstrated promising results in minimizing operational expenses and reducing peak demand by altering the consumption pattern through various incentive and price-based strategies. This article presents an optimal scheduling framework for efficient energy management in a smart home, employing an Ensembled Home Energy Management System (EHEMS). The EHEMS is responsible for managing a set of resources, including a Battery Energy Storage System (BESS), thermostatically controllable loads such as Air conditioners (AC) and Ceiling Fans (CF), Electric Vehicles (EV) and Lighting Systems (LS). The solution aims to minimize the operation cost and maximize energy savings while managing the peak demand by jointly determining optimal operating settings for the AC and the CF, and the other home energy resources for effective utilization considering Real Time Pricing strategy. The problem is formulated as a mixed-integer linear programming problem to minimize the operating cost and peak demand and maximize energy savings. Results demonstrate that users have contributed towards more energy savings without curtailing or shifting their loads when operating in the ensembled mode.