Optimal battery utilization for energy management and load scheduling in smart residence under demand response scheme

Abstract

Smart residences that could optimally integrate the actions of all their components are essential in the smart grid architecture. This paper proposes a mixed-integer linear programming (MILP) based model of a single residence that optimally operates the residential appliances and manages the energy received from the Distributed Energy Resources (DERs) apart from the utility grid according to the day-head Time of Use prices. To achieve this, an Energy Management and Load Scheduling System (EMLSS) has been incorporated into the residence. Further, the user thermal comfort was maintained by optimally operating the air conditioner in coordination with a dehumidifier to keep the indoor temperature and relative humidity within the desired limits. For observing the EMLSS’s operation under the intermittent weather conditions, the simulation of the MILP model was conducted for 26 different days of the year. Using these days’ results, an annual study was conducted whose results were input into the Rainflow Cycle Counting algorithm for assessing the capacity degradation of the residential Battery Energy Storage System (BESS) until its End of Life (EoL). The energy expenditure evaluation conducted until the BESS’s EoL, confirmed the effectiveness of the EMLSS in reducing the replacement costs of the old BESS battery. • Residential expenditure over multiple years evaluated until the battery’s End of Life. • Capacity degradation of the battery assessed using Rainflow Cycle Counting algorithm. • EMLSS optimally manages the DERs and loads in a single residence. • EMLSS found effective in reducing the replacement costs of the old BESS battery.