Planning Energy Storage and Photovoltaic Panels for Demand Response With Heating Ventilation and Air Conditioning Systems

The objective of this engineering problem is to determine the size of a battery energy storage system and number of photovoltaic (PV) panels to be installed in a building with Heating Ventilation and Air Conditioning systems (HVACs) as the main load. The building is connected to the power grid where electricity price is varying at different hours. This engineering problem is formulated as an optimization problem with a goal to achieve minimum installation cost and operation cost while satisfying room temperature requirements. Stochastic PV outputs are taken into consideration as well. The mathematical problem formulated is a large-scale mixed integer linear programming (MILP) problem. To improve the solving speed, two Benders decomposition strategies are applied to solve this stochastic MILP problem. The optimization problem will lead to the battery energy capacity, power limit, number of PV to be installed, as well as the on/off status of HVACs over 8 h. The contribution of this paper is the implementation of Benders decomposition methods to reduce the computation complexity. Parallel computing structure and maximum feasible subsystem cut generation strategy have been exploited and implemented in this research.