An optimization-based approach to scheduling residential battery storage with solar PV: Assessing customer benefit

• Published in: Renewable energy 2015-03, Vol.75, p.123-134
• Main Authors: Ratnam, Elizabeth L., Weller, Steven R., Kellett, Christopher M.
• Format: Article
• Language: English
• Subjects: Algorithms; Battery scheduling; Electric batteries; Electric potential; Feed-in tariffs; Peak-load reduction; Photovoltaic cells; Photovoltaics; Residential; Scheduling; Solar cells; Time-of-use pricing; Voltage
• ISSN: 0960-1481; 1879-0682
• DOI: 10.1016/j.renene.2014.09.008

Several studies have suggested that battery storage co-located with solar photovoltaics (PV) benefits electricity distributors in maintaining system voltages within acceptable limits. However, without careful coordination, these potential benefits might not be realized. In this paper we propose an optimization-based algorithm for the scheduling of residential battery storage co-located with solar PV, in the context of PV incentives such as feed-in tariffs. Our objective is to maximize the daily operational savings that accrue to customers, while penalizing large voltage swings stemming from reverse power flow and peak load. To achieve this objective we present a quadratic program (QP)-based algorithm. To complete our assessment of the customer benefit, the QP-based scheduling algorithm is applied to measured load and generation data from 145 residential customers located in an Australian distribution network. The results of this case study confirm the QP-based scheduling algorithm significantly penalizes reverse power flow and peak loads corresponding to peak time-of-use billing. In the context of feed-in tariffs, the majority of customers exhibited operational savings when QP energy-shifting. •Optimization-based approach to schedule a residential battery co-located with PV.•Increases daily operational savings to customers.•Penalizes large voltage swings stemming from reverse power flow and peak load.•Applied to measured load and generation data from 145 Australian LV customers.•The majority of customers exhibited annual savings in the context of feed-in tariffs.