IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v290y2021ics0306261921002579.html
   My bibliography  Save this article

Solar panels and smart thermostats: The power duo of the residential sector?

Author

Listed:
  • Bandyopadhyay, Arkasama
  • Leibowicz, Benjamin D.
  • Webber, Michael E.

Abstract

Rising peak demand is a major cause for high emissions from the electricity sector. In this study, we investigate how different combinations of distributed energy technologies affect peak grid load, energy consumption from the grid, and emissions in the residential sector under time-varying prices. To do so, we develop an optimization framework in which households with varied amalgamations of distributed energy technologies minimize electricity costs, amortized capital, and operational costs over a year, with marginally increasing penalties for deviating from room temperature set-points. The four technologies we consider are: solar panels, lithium-ion batteries, ice cold thermal energy storage, and smart thermostats. The study also incorporates a one-parameter thermal model of the home, so that the discomfort penalties can apply to the room temperature rather than the total appliance load. Based on empirical energy consumption profiles and solar generation data from 25 homes in Austin, we find that residential customers would keep overall annual expenditure and environmental footprint low by investing in solar panels and smart thermostats. The capital costs of both storage systems are still too high to make them economically profitable investments for typical residential customers. Additionally, the Value of Solar policy disincentivizes solar customer investment in storage systems. The study also shows that, while the energetic effect of the two storage systems can be favorable or detrimental depending upon the pricing structure and the household load profile, lithium-ion batteries are the main instruments to avoid high demand charges. Thus, we recommend that, as an effective peak load control mechanism, electric utilities should offer significant rebates to encourage residential customer investment in storage systems in addition to subjecting them to demand charges.

Suggested Citation

  • Bandyopadhyay, Arkasama & Leibowicz, Benjamin D. & Webber, Michael E., 2021. "Solar panels and smart thermostats: The power duo of the residential sector?," Applied Energy, Elsevier, vol. 290(C).
  • Handle: RePEc:eee:appene:v:290:y:2021:i:c:s0306261921002579
    DOI: 10.1016/j.apenergy.2021.116747
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261921002579
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.apenergy.2021.116747?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Carvallo, Juan Pablo & Zhang, Nan & Murphy, Sean P. & Leibowicz, Benjamin D. & Larsen, Peter H., 2020. "The economic value of a centralized approach to distributed resource investment and operation," Applied Energy, Elsevier, vol. 269(C).
    2. Deane, J.P. & Chiodi, Alessandro & Gargiulo, Maurizio & Ó Gallachóir, Brian P., 2012. "Soft-linking of a power systems model to an energy systems model," Energy, Elsevier, vol. 42(1), pages 303-312.
    3. Robert L. Fares & Michael E. Webber, 2017. "The impacts of storing solar energy in the home to reduce reliance on the utility," Nature Energy, Nature, vol. 2(2), pages 1-10, February.
    4. O'Shaughnessy, Eric & Cutler, Dylan & Ardani, Kristen & Margolis, Robert, 2018. "Solar plus: Optimization of distributed solar PV through battery storage and dispatchable load in residential buildings," Applied Energy, Elsevier, vol. 213(C), pages 11-21.
    5. Babacan, Oytun & Ratnam, Elizabeth L. & Disfani, Vahid R. & Kleissl, Jan, 2017. "Distributed energy storage system scheduling considering tariff structure, energy arbitrage and solar PV penetration," Applied Energy, Elsevier, vol. 205(C), pages 1384-1393.
    6. Deane, J.P. & Drayton, G. & Ó Gallachóir, B.P., 2014. "The impact of sub-hourly modelling in power systems with significant levels of renewable generation," Applied Energy, Elsevier, vol. 113(C), pages 152-158.
    7. Andrew Izawa & Matthias Fripp, 2018. "Multi-Objective Control of Air Conditioning Improves Cost, Comfort and System Energy Balance," Energies, MDPI, vol. 11(9), pages 1-18, September.
    8. Stenner, Karen & Frederiks, Elisha R. & Hobman, Elizabeth V. & Cook, Stephanie, 2017. "Willingness to participate in direct load control: The role of consumer distrust," Applied Energy, Elsevier, vol. 189(C), pages 76-88.
    9. Frew, Bethany A. & Jacobson, Mark Z., 2016. "Temporal and spatial tradeoffs in power system modeling with assumptions about storage: An application of the POWER model," Energy, Elsevier, vol. 117(P1), pages 198-213.
    10. 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.
    11. Mallapragada, Dharik S. & Papageorgiou, Dimitri J. & Venkatesh, Aranya & Lara, Cristiana L. & Grossmann, Ignacio E., 2018. "Impact of model resolution on scenario outcomes for electricity sector system expansion," Energy, Elsevier, vol. 163(C), pages 1231-1244.
    12. Rhodes, Joshua D. & Cole, Wesley J. & Upshaw, Charles R. & Edgar, Thomas F. & Webber, Michael E., 2014. "Clustering analysis of residential electricity demand profiles," Applied Energy, Elsevier, vol. 135(C), pages 461-471.
    13. Merrick, James H., 2016. "On representation of temporal variability in electricity capacity planning models," Energy Economics, Elsevier, vol. 59(C), pages 261-274.
    14. Deetjen, Thomas A. & Vitter, J. Scott & Reimers, Andrew S. & Webber, Michael E., 2018. "Optimal dispatch and equipment sizing of a residential central utility plant for improving rooftop solar integration," Energy, Elsevier, vol. 147(C), pages 1044-1059.
    15. Uddin, Kotub & Gough, Rebecca & Radcliffe, Jonathan & Marco, James & Jennings, Paul, 2017. "Techno-economic analysis of the viability of residential photovoltaic systems using lithium-ion batteries for energy storage in the United Kingdom," Applied Energy, Elsevier, vol. 206(C), pages 12-21.
    16. Lorenzi, Guido & Silva, Carlos Augusto Santos, 2016. "Comparing demand response and battery storage to optimize self-consumption in PV systems," Applied Energy, Elsevier, vol. 180(C), pages 524-535.
    17. Leibowicz, Benjamin D. & Lanham, Christopher M. & Brozynski, Max T. & Vázquez-Canteli, José R. & Castejón, Nicolás Castillo & Nagy, Zoltan, 2018. "Optimal decarbonization pathways for urban residential building energy services," Applied Energy, Elsevier, vol. 230(C), pages 1311-1325.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Muhammad Irfan & Sara Deilami & Shujuan Huang & Binesh Puthen Veettil, 2023. "Rooftop Solar and Electric Vehicle Integration for Smart, Sustainable Homes: A Comprehensive Review," Energies, MDPI, vol. 16(21), pages 1-29, October.
    2. Syrodoy, S.V. & Kuznetsov, G.V. & Nigay, N.A. & Purin, M.V. & Kostoreva, Zh.A., 2023. "The effect of compaction of the dispersed wood biomass layer on its drying efficiency," Renewable Energy, Elsevier, vol. 211(C), pages 64-75.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Maximilian Hoffmann & Leander Kotzur & Detlef Stolten & Martin Robinius, 2020. "A Review on Time Series Aggregation Methods for Energy System Models," Energies, MDPI, vol. 13(3), pages 1-61, February.
    2. Scott, Ian J. & Carvalho, Pedro M.S. & Botterud, Audun & Silva, Carlos A., 2019. "Clustering representative days for power systems generation expansion planning: Capturing the effects of variable renewables and energy storage," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    3. Merrick, James H. & Bistline, John E.T. & Blanford, Geoffrey J., 2024. "On representation of energy storage in electricity planning models," Energy Economics, Elsevier, vol. 136(C).
    4. Niina Helistö & Juha Kiviluoma & Hannele Holttinen & Jose Daniel Lara & Bri‐Mathias Hodge, 2019. "Including operational aspects in the planning of power systems with large amounts of variable generation: A review of modeling approaches," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 8(5), September.
    5. Heine, Karl & Thatte, Amogh & Tabares-Velasco, Paulo Cesar, 2019. "A simulation approach to sizing batteries for integration with net-zero energy residential buildings," Renewable Energy, Elsevier, vol. 139(C), pages 176-185.
    6. Heggarty, Thomas & Bourmaud, Jean-Yves & Girard, Robin & Kariniotakis, Georges, 2024. "Assessing the relative impacts of maximum investment rate and temporal detail in capacity expansion models applied to power systems," Energy, Elsevier, vol. 290(C).
    7. Thomas Heggarty & Jean-Yves Bourmaud & Robin Girard & Georges Kariniotakis, 2024. "Assessing the relative impacts of maximum investment rate and temporal detail in capacity expansion models applied to power systems," Post-Print hal-04383397, HAL.
    8. Mertens, Tim & Poncelet, Kris & Duerinck, Jan & Delarue, Erik, 2020. "Representing cross-border trade of electricity in long-term energy-system optimization models with a limited geographical scope," Applied Energy, Elsevier, vol. 261(C).
    9. Azuatalam, Donald & Paridari, Kaveh & Ma, Yiju & Förstl, Markus & Chapman, Archie C. & Verbič, Gregor, 2019. "Energy management of small-scale PV-battery systems: A systematic review considering practical implementation, computational requirements, quality of input data and battery degradation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 112(C), pages 555-570.
    10. Tervo, Eric & Agbim, Kenechi & DeAngelis, Freddy & Hernandez, Jeffrey & Kim, Hye Kyung & Odukomaiya, Adewale, 2018. "An economic analysis of residential photovoltaic systems with lithium ion battery storage in the United States," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 1057-1066.
    11. Teichgraeber, Holger & Brandt, Adam R., 2022. "Time-series aggregation for the optimization of energy systems: Goals, challenges, approaches, and opportunities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 157(C).
    12. O'Shaughnessy, Eric & Cutler, Dylan & Ardani, Kristen & Margolis, Robert, 2018. "Solar plus: A review of the end-user economics of solar PV integration with storage and load control in residential buildings," Applied Energy, Elsevier, vol. 228(C), pages 2165-2175.
    13. Bistline, John & Blanford, Geoffrey & Mai, Trieu & Merrick, James, 2021. "Modeling variable renewable energy and storage in the power sector," Energy Policy, Elsevier, vol. 156(C).
    14. Göke, Leonard & Kendziorski, Mario, 2022. "Adequacy of time-series reduction for renewable energy systems," Energy, Elsevier, vol. 238(PA).
    15. Alimou, Yacine & Maïzi, Nadia & Bourmaud, Jean-Yves & Li, Marion, 2020. "Assessing the security of electricity supply through multi-scale modeling: The TIMES-ANTARES linking approach," Applied Energy, Elsevier, vol. 279(C).
    16. 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).
    17. Ahsan, Syed M. & Khan, Hassan A. & Hassan, Naveed-ul & Arif, Syed M. & Lie, Tek-Tjing, 2020. "Optimized power dispatch for solar photovoltaic-storage system with multiple buildings in bilateral contracts," Applied Energy, Elsevier, vol. 273(C).
    18. Zhou, Hou Sheng & Passey, Rob & Bruce, Anna & Sproul, Alistair B., 2021. "A case study on the behaviour of residential battery energy storage systems during network demand peaks," Renewable Energy, Elsevier, vol. 180(C), pages 712-724.
    19. Reichenberg, Lina & Hedenus, Fredrik & Odenberger, Mikael & Johnsson, Filip, 2018. "The marginal system LCOE of variable renewables – Evaluating high penetration levels of wind and solar in Europe," Energy, Elsevier, vol. 152(C), pages 914-924.
    20. Alsagri, Ali Sulaiman & Alrobaian, Abdulrahman A. & Nejlaoui, Mohamed, 2021. "Techno-economic evaluation of an off-grid health clinic considering the current and future energy challenges: A rural case study," Renewable Energy, Elsevier, vol. 169(C), pages 34-52.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:appene:v:290:y:2021:i:c:s0306261921002579. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.