SMART METER DATA TO OPTIMIZE COMBINED ROOF-TOP SOLAR AND BATTERY SYSTEMS USING A STOCHASTIC MIXED INTEGER PROGRAMMING MODEL

Emon Chatterji and Payne Institute Director Morgan Bazilian presents the design and results of a model that uses household smart meter data, electric vehicle (EV) travel load and charging options, and multiple solar resource profiles, to make decisions on optimal combinations of photovoltaics (PV), battery energy storage systems (BESS) and EV charging strategies. The least-cost planning model is formulated as a stochastic mixed integer programming (MIP) problem that makes first stage decisions on PV/BESS investments, and recourse decisions on purchase/sell from/to the grid to minimize expected household electricity costs. July 21, 2020.