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Leveraging smart meter data for economic optimization of residential photovoltaics under existing tariff structures and incentive schemes

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  • Every, Jeremy
  • Li, Li
  • Dorrell, David G.

Abstract

The introduction of smart grid technologies and the impending removal of incentive schemes is likely to complicate the cost-effective selection and integration of residential PV systems in the future. With the widespread integration of smart meters, consumers can leverage the high temporal resolution of energy consumption data to optimize a PV system based on their individual circumstances. In this article, such an optimization strategy is developed to enable the optimal selection of size, tilt, azimuth and retail electricity plan for a residential PV system based on hourly consumption data. Hourly solar insolation and PV array generation models are presented as the principal components of the underlying objective function. A net present value analysis of the potential monetary savings is considered and set as the optimization objective. A particle swarm optimization algorithm is utilized, modified to include a penalty function in order to handle associated constraints. The optimization problem is applied to real-world Australian consumption data to establish the economic performance and characteristics of the optimized systems. For all customers assessed, an optimized PV system producing a positive economic benefit could be found. However not all investment options were found to be desirable with at most 77.5% of customers yielding an acceptable rate of return. For the customers assessed, the mean PV system size was found to be 2kW less than the mean size of actual systems installed in the assessed locations during 2015 and 2016. Over-sizing of systems was found to significantly reduce the potential net benefit of residential PV from an investor’s perspective. The results presented in this article highlight the necessity for economic performance optimization to be routinely implemented for small-scale residential PV under current regulatory and future smart grid operating environments.

Suggested Citation

  • Every, Jeremy & Li, Li & Dorrell, David G., 2017. "Leveraging smart meter data for economic optimization of residential photovoltaics under existing tariff structures and incentive schemes," Applied Energy, Elsevier, vol. 201(C), pages 158-173.
    • Handle: RePEc:eee:appene:v:201:y:2017:i:c:p:158-173
    DOI: 10.1016/j.apenergy.2017.05.021
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    References listed on IDEAS

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    1. Pillai, Gobind G. & Putrus, Ghanim A. & Georgitsioti, Tatiani & Pearsall, Nicola M., 2014. "Near-term economic benefits from grid-connected residential PV (photovoltaic) systems," Energy, Elsevier, vol. 68(C), pages 832-843.
    2. Han, Xiaojuan & Zhang, Hua & Yu, Xiaoling & Wang, Lina, 2016. "Economic evaluation of grid-connected micro-grid system with photovoltaic and energy storage under different investment and financing models," Applied Energy, Elsevier, vol. 184(C), pages 103-118.
    3. Chang, Ying-Pin, 2010. "Optimal the tilt angles for photovoltaic modules using PSO method with nonlinear time-varying evolution," Energy, Elsevier, vol. 35(5), pages 1954-1963.
    4. Noorian, Ali Mohammad & Moradi, Isaac & Kamali, Gholam Ali, 2008. "Evaluation of 12 models to estimate hourly diffuse irradiation on inclined surfaces," Renewable Energy, Elsevier, vol. 33(6), pages 1406-1412.
    5. Numbi, B.P. & Malinga, S.J., 2017. "Optimal energy cost and economic analysis of a residential grid-interactive solar PV system- case of eThekwini municipality in South Africa," Applied Energy, Elsevier, vol. 186(P1), pages 28-45.
    6. Koo, Choongwan & Hong, Taehoon & Lee, Minhyun & Kim, Jimin, 2016. "An integrated multi-objective optimization model for determining the optimal solution in implementing the rooftop photovoltaic system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 822-837.
    7. Kim, Jimin & Hong, Taehoon & Jeong, Jaemin & Lee, Myeonghwi & Koo, Choongwan & Lee, Minhyun & Ji, Changyoon & Jeong, Jaewook, 2016. "An integrated multi-objective optimization model for determining the optimal solution in the solar thermal energy system," Energy, Elsevier, vol. 102(C), pages 416-426.
    8. Chen, Jun & Garcia, Humberto E., 2016. "Economic optimization of operations for hybrid energy systems under variable markets," Applied Energy, Elsevier, vol. 177(C), pages 11-24.
    9. Mulder, Grietus & Six, Daan & Claessens, Bert & Broes, Thijs & Omar, Noshin & Mierlo, Joeri Van, 2013. "The dimensioning of PV-battery systems depending on the incentive and selling price conditions," Applied Energy, Elsevier, vol. 111(C), pages 1126-1135.
    10. Zhao, Bo & Zhang, Xuesong & Li, Peng & Wang, Ke & Xue, Meidong & Wang, Caisheng, 2014. "Optimal sizing, operating strategy and operational experience of a stand-alone microgrid on Dongfushan Island," Applied Energy, Elsevier, vol. 113(C), pages 1656-1666.
    11. Yadav, Amit Kumar & Chandel, S.S., 2013. "Tilt angle optimization to maximize incident solar radiation: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 23(C), pages 503-513.
    12. Beck, T. & Kondziella, H. & Huard, G. & Bruckner, T., 2016. "Assessing the influence of the temporal resolution of electrical load and PV generation profiles on self-consumption and sizing of PV-battery systems," Applied Energy, Elsevier, vol. 173(C), pages 331-342.
    13. González, Arnau & Riba, Jordi-Roger & Rius, Antoni & Puig, Rita, 2015. "Optimal sizing of a hybrid grid-connected photovoltaic and wind power system," Applied Energy, Elsevier, vol. 154(C), pages 752-762.
    14. Bakhshi, Reza & Sadeh, Javad, 2016. "A comprehensive economic analysis method for selecting the PV array structure in grid–connected photovoltaic systems," Renewable Energy, Elsevier, vol. 94(C), pages 524-536.
    15. of England, Bank, 2016. "Markets and operations," Bank of England Quarterly Bulletin, Bank of England, vol. 56(4), pages 212-221.
    16. Arnau González & Jordi-Roger Riba & Antoni Rius, 2015. "Optimal Sizing of a Hybrid Grid-Connected Photovoltaic–Wind–Biomass Power System," Sustainability, MDPI, vol. 7(9), pages 1-20, September.
    17. Merei, Ghada & Moshövel, Janina & Magnor, Dirk & Sauer, Dirk Uwe, 2016. "Optimization of self-consumption and techno-economic analysis of PV-battery systems in commercial applications," Applied Energy, Elsevier, vol. 168(C), pages 171-178.
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    1. Avilés A., Camilo & Oliva H., Sebastian & Watts, David, 2019. "Single-dwelling and community renewable microgrids: Optimal sizing and energy management for new business models," Applied Energy, Elsevier, vol. 254(C).
    2. Wen, Lulu & Zhou, Kaile & Yang, Shanlin & Li, Lanlan, 2018. "Compression of smart meter big data: A survey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 91(C), pages 59-69.

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