A probabilistic-based PV and energy storage sizing tool for residential loads

Abstract

This paper presents a probabilistic-based sizing tool for residential home owners, load serving entities, and utilities to select energy storage (ES) and photovoltaic (PV) based on historical load characteristics and load management options. The inputs of the tool include historical residential load profiles and solar radiation data. The outputs of the tool include ensembles of the net load profiles (load minus solar), with and without applying load energy management for different PV and ES installation capacities. The operation statistics of the ES is used to determine the confidence levels of meeting selected performance criterion. In the simulation, a set of 1-year, 15-minute data collected from 50 actual residential homes is used as the load inputs. A set of 1-year, 5-minute actual solar radiation data is used as the solar inputs. Managing load consumptions for reducing the size of ES is investigated by controlling air conditioning loads. Simulation results show that the probabilistic-based sizing method can give the users a clear comparison of the tradeoffs among different options and assist them make more informed decisions.