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Impacts of the co-adoption of electric vehicles and solar panel systems: Empirical evidence of changes in electricity demand and consumer behaviors from household smart meter data

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  • Liang, Jing
  • Qiu, Yueming (Lucy)
  • Xing, Bo

Abstract

During the electrification of household energy consumption, there is an increasing number of consumers that purchase both electric vehicles (EV) and distributed solar photovoltaics (PV) systems. This study aims to examine the change in electricity demand from the power grid for EV owners when they add distributed solar panels to their homes. The impacts of the two technologies combined are different from the sum of two individual impacts because they may not be additive and EV consumers' behaviors may be subject to change. We apply a difference-in-differences model and compare consumers with or without EVs and also EV consumers with and without additional PVs. We use the hourly electricity demand data for 13,190 households in the Phoenix metropolitan area in Arizona. Our results show that EV consumers, without PV panels, use more electricity compared to non-EV consumers, and their average hourly demand is higher by 0.4 kWh. After adding PVs, EV consumers decrease the average hourly demand from the electric grid by 1.1 kWh. The co-adoption of PVs with EVs helps reduce the system peak hour loads. Besides, we also find evidence of behavior changes when EV consumers shift some of their EV charging from night to day so that they are charging their EVs with more cleaner electricity. The annual monetary savings for consumers after adding PVs are estimated to be ~$930, and the total social savings are estimated to be ~$925. Given the positive co-adoption effects, a policy implication is that incentives should be provided to promote the co-adoption of PVs with EVs.

Suggested Citation

  • Liang, Jing & Qiu, Yueming (Lucy) & Xing, Bo, 2022. "Impacts of the co-adoption of electric vehicles and solar panel systems: Empirical evidence of changes in electricity demand and consumer behaviors from household smart meter data," Energy Economics, Elsevier, vol. 112(C).
    • Handle: RePEc:eee:eneeco:v:112:y:2022:i:c:s0140988322003231
    DOI: 10.1016/j.eneco.2022.106170
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