Stochastic multi-objective optimal sizing of battery energy storage system for a residential home

Abstract

The deployment of renewable local generation sources at home can help reduce emission contributions within residential homes. Furthermore, the adoption of the residential PV system is increasing as the economics of installation continues to decrease. An optimally sized battery energy storage system can help maximise the benefits of the power generated from the PV systems while being economical. In this paper, a stochastic optimisation problem is formulated to determine the optimal size of the energy storage system and investigate the benefits of uncertainty consideration in the formulation of the sizing optimisation problem. A multi-objective problem is formulated consisting of two objectives: minimise the cost of purchasing the battery energy storage system, and minimise the amount of energy imported from the grid within the period. The stochastic problem is formulated as a two-stage scenario stochastic problem. The optimal sizing and operation problem was formulated as a mixed-integer linear programming problem and solved using the CPLEX solver. This work also utilises a Monte Carlo approach to deal with the uncertainty in load forecasting. Simulation results show that the proposed approach can estimate an optimal battery energy storage system at the current cost of BESS and clearly indicate the benefit of a stochastic approach.