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The impact of scheduling appliances and rate structure on bill savings for net-zero energy communities: Application to West Village

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  • Gaiser, Kyle
  • Stroeve, Pieter

Abstract

This paper investigates the financial incentives of load shifting under a time-of-use rate and Net Energy Metering pertaining to the solar net-zero energy apartment community, West Village in Davis, California. By “smart-scheduling” the electricity and domestic hot water demand of the dishwasher, clothes washer, dryer, sinks and showers solely to off-peak periods, the peak demand is reduced by 18%, the part-peak demand by 32% and the off-peak demand increased by 12%. With this shifted schedule customers accrue twice as many credits as they would receive under a non-shifted schedule with the same time-of-use rate, totaling to $2975 of “free” electricity per year for one 12unit building. But, under current rates smart-scheduling is found to be worthwhile only during the months from May through October, when 96% of the credits are accumulated. If the rate schedule is altered to include peak-periods during the winter months, the credit savings will double again in value. These comparisons are prepared using two photovoltaic simulation programs (PolySun by Vela Solaris and System Advisory Model by the National Renewable Energy Laboratory) and for apartments using an electric heater and a heat pump for domestic hot water. By quantifying these savings, PV generating customers are informed that a time-of-use rate can benefit them significantly, especially if the surplus generation is maximized and sold to the grid during peak day time hours. With this information, housing developers can create effective incentives for residents, and utility companies, policy makers and designers of smart-scheduling household appliances can encourage a more reliable, clean and economical national grid.

Suggested Citation

  • Gaiser, Kyle & Stroeve, Pieter, 2014. "The impact of scheduling appliances and rate structure on bill savings for net-zero energy communities: Application to West Village," Applied Energy, Elsevier, vol. 113(C), pages 1586-1595.
    • Handle: RePEc:eee:appene:v:113:y:2014:i:c:p:1586-1595
    DOI: 10.1016/j.apenergy.2013.08.075
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    3. Di Giorgio, Alessandro & Liberati, Francesco, 2014. "Near real time load shifting control for residential electricity prosumers under designed and market indexed pricing models," Applied Energy, Elsevier, vol. 128(C), pages 119-132.
    4. Villa-Arrieta, Manuel & Sumper, Andreas, 2019. "Economic evaluation of Nearly Zero Energy Cities," Applied Energy, Elsevier, vol. 237(C), pages 404-416.
    5. Fernández, David & Pozo, Carlos & Folgado, Rubén & Guillén-Gosálbez, Gonzalo & Jiménez, Laureano, 2017. "Multiperiod model for the optimal production planning in the industrial gases sector," Applied Energy, Elsevier, vol. 206(C), pages 667-682.
    6. Charani Shandiz, Saeid & Rismanchi, Behzad & Foliente, Greg, 2021. "Energy master planning for net-zero emission communities: State of the art and research challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 137(C).
    7. Cominola, A. & Giuliani, M. & Piga, D. & Castelletti, A. & Rizzoli, A.E., 2017. "A Hybrid Signature-based Iterative Disaggregation algorithm for Non-Intrusive Load Monitoring," Applied Energy, Elsevier, vol. 185(P1), pages 331-344.
    8. Tian, Shuai & Lu, Yuxin & Zhou, Xin & Zhang, Lun & An, Jingjing & Yan, Da & Shi, Xing & Jin, Xing, 2023. "A new perspective of solar hot water system operation optimization: Supply and demand matching," Renewable Energy, Elsevier, vol. 207(C), pages 89-104.
    9. Sharma, A. & Bhakar, R. & Tiwari, H.P. & Li, R. & Li, F., 2017. "A novel hierarchical contribution factor based model for distribution use-of-system charges," Applied Energy, Elsevier, vol. 208(C), pages 996-1006.
    10. Damilola A. Asaleye & Michael Breen & Michael D. Murphy, 2017. "A Decision Support Tool for Building Integrated Renewable Energy Microgrids Connected to a Smart Grid," Energies, MDPI, vol. 10(11), pages 1-29, November.
    11. Wong, Pui Ting & Rau, Henrike, 2023. "Time of Use tariffs, childcare and everyday temporalities in the US and China: Evidence from time-use and sequence-network analysis," Energy Policy, Elsevier, vol. 172(C).
    12. Luca Brunelli & Emiliano Borri & Anna Laura Pisello & Andrea Nicolini & Carles Mateu & Luisa F. Cabeza, 2024. "Thermal Energy Storage in Energy Communities: A Perspective Overview through a Bibliometric Analysis," Sustainability, MDPI, vol. 16(14), pages 1-27, July.
    13. Klaassen, E.A.M. & Kobus, C.B.A. & Frunt, J. & Slootweg, J.G., 2016. "Responsiveness of residential electricity demand to dynamic tariffs: Experiences from a large field test in the Netherlands," Applied Energy, Elsevier, vol. 183(C), pages 1065-1074.
    14. Kobus, Charlotte B.A. & Klaassen, Elke A.M. & Mugge, Ruth & Schoormans, Jan P.L., 2015. "A real-life assessment on the effect of smart appliances for shifting households’ electricity demand," Applied Energy, Elsevier, vol. 147(C), pages 335-343.
    15. Ren, Zhengen & Grozev, George & Higgins, Andrew, 2016. "Modelling impact of PV battery systems on energy consumption and bill savings of Australian houses under alternative tariff structures," Renewable Energy, Elsevier, vol. 89(C), pages 317-330.

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