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Optimal sizing and comparative analysis of rooftop PV and battery for grid-connected households with all-electric and gas-electricity utility

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  • Khezri, Rahmat
  • Mahmoudi, Amin
  • Whaley, David

Abstract

This study evaluates the optimal sizing and economic analysis of the rooftop solar photovoltaic (PV) and lithium-ion battery energy storage system (BESS) for grid-connected households. Two types of households are investigated, i.e., all-electric homes and those supplied with both gas and electricity. Each type of household is investigated under three system configurations: (i) without PV and BESS, (ii) with PV only, and (iii) with PV and BESS (PV-BESS) system. The objective is to minimize the net present value (NPV) of operating each type of house and examine the impact of the generation and storage technologies on these. For the all-electric household, gas demand is converted to electricity demand based on the gas and electric cooking and water heating appliance efficiencies used in this study. The houses NPVs are calculated using real monitored gas and electricity usage data, along with measured, solar irradiation and ambient air temperatures. It is found that the NPV varies for the all-electric and the gas and electric house, and is more prominent for the customers with gas and electric when no PV and BESS are installed. However, the key finding of this study highlights that the PV-BESS system is more economic for the all-electric houses.

Suggested Citation

  • Khezri, Rahmat & Mahmoudi, Amin & Whaley, David, 2022. "Optimal sizing and comparative analysis of rooftop PV and battery for grid-connected households with all-electric and gas-electricity utility," Energy, Elsevier, vol. 251(C).
    • Handle: RePEc:eee:energy:v:251:y:2022:i:c:s0360544222007794
    DOI: 10.1016/j.energy.2022.123876
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    Cited by:

    1. Shaojie Li & Tao Zhang & Xiaochen Liu & Xiaohua Liu, 2023. "A Battery Capacity Configuration Method of a Photovoltaic and Battery System Applied in a Building Complex for Increased Self-Sufficiency and Self-Consumption," Energies, MDPI, vol. 16(5), pages 1-18, February.
    2. Gelchu, Milky Ali & Ehnberg, Jimmy & Shiferaw, Dereje & Ahlgren, Erik O., 2023. "Impact of demand-side management on the sizing of autonomous solar PV-based mini-grids," Energy, Elsevier, vol. 278(PA).
    3. Nicola Blasuttigh & Simone Negri & Alessandro Massi Pavan & Enrico Tironi, 2023. "Optimal Sizing and Environ-Economic Analysis of PV-BESS Systems for Jointly Acting Renewable Self-Consumers," Energies, MDPI, vol. 16(3), pages 1-25, January.
    4. Zhi, Yuan & Yang, Xudong, 2023. "Scenario-based multi-objective optimization strategy for rural PV-battery systems," Applied Energy, Elsevier, vol. 345(C).
    5. Zou, Wenke & Sun, Yongjun & Gao, Dian-ce & Zhang, Xu & Liu, Junyao, 2023. "A review on integration of surging plug-in electric vehicles charging in energy-flexible buildings: Impacts analysis, collaborative management technologies, and future perspective," Applied Energy, Elsevier, vol. 331(C).
    6. Ren, Haoshan & Sun, Yongjun & Norman Tse, Chung Fai & Fan, Cheng, 2023. "Optimal packing and planning for large-scale distributed rooftop photovoltaic systems under complex shading effects and rooftop availabilities," Energy, Elsevier, vol. 274(C).
    7. Zhang, Jianhua & Ballas, Dimitris & Liu, Xiaolong, 2023. "Neighbourhood-level spatial determinants of residential solar photovoltaic adoption in the Netherlands," Renewable Energy, Elsevier, vol. 206(C), pages 1239-1248.
    8. Tanoto, Yusak, 2023. "Cost-reliability trade-offs for grid-connected rooftop PV in emerging economies: A case of Indonesia's urban residential households," Energy, Elsevier, vol. 285(C).

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