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

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  • Ratnam, Elizabeth L.
  • Weller, Steven R.
  • Kellett, Christopher M.

Abstract

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.

Suggested Citation

  • Ratnam, Elizabeth L. & Weller, Steven R. & Kellett, Christopher M., 2015. "An optimization-based approach to scheduling residential battery storage with solar PV: Assessing customer benefit," Renewable Energy, Elsevier, vol. 75(C), pages 123-134.
  • Handle: RePEc:eee:renene:v:75:y:2015:i:c:p:123-134
    DOI: 10.1016/j.renene.2014.09.008
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    References listed on IDEAS

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    1. Brown, Stephen & Pyke, David & Steenhof, Paul, 2010. "Electric vehicles: The role and importance of standards in an emerging market," Energy Policy, Elsevier, vol. 38(7), pages 3797-3806, July.
    2. Darghouth, Naïm R. & Barbose, Galen & Wiser, Ryan H., 2014. "Customer-economics of residential photovoltaic systems (Part 1): The impact of high renewable energy penetrations on electricity bill savings with net metering," Energy Policy, Elsevier, vol. 67(C), pages 290-300.
    3. Hirth, Lion & Ueckerdt, Falko, 2013. "Redistribution effects of energy and climate policy: The electricity market," Energy Policy, Elsevier, vol. 62(C), pages 934-947.
    4. Candelise, Chiara & Winskel, Mark & Gross, Robert J.K., 2013. "The dynamics of solar PV costs and prices as a challenge for technology forecasting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 26(C), pages 96-107.
    5. Nottrott, A. & Kleissl, J. & Washom, B., 2013. "Energy dispatch schedule optimization and cost benefit analysis for grid-connected, photovoltaic-battery storage systems," Renewable Energy, Elsevier, vol. 55(C), pages 230-240.
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