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The impact of energy-efficiency upgrades and other distributed energy resources on a residential neighborhood-scale electrification retrofit

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  • Earle, Lieko
  • Maguire, Jeff
  • Munankarmi, Prateek
  • Roberts, David

Abstract

Ambitious targets for carbon emissions reductions are highlighting new challenges for electrification strategies, leading to an increased focus on building load flexibility and energy management to complement the variability inherent in renewable energy generation. Over the next decade millions of existing homes could undergo electrification retrofits, and there is an urgent need to understand the potential impacts of electrifying major residential loads such as water and space heating on community load characteristics, resident energy bills, and the utility’s distribution system. Behind-the-meter distributed energy resources (DERs), including efficiency measures, photovoltaics (PV), battery storage, managed electric vehicle (EV) charging, and controls such as home energy management systems (HEMS), can significantly alter a neighborhood’s load profile and provide benefits to both the residents and the grid. We present a novel approach to characterizing the impact of a hypothetical neighborhood-scale residential retrofit program on individual homes’ energy use profiles, associated utility bills, and the local distribution system. We modeled a mixed-fuel community of 30 single-family homes in Denver, Colorado, and compared the effects of retrofit scenarios ranging from conventional energy-efficiency upgrades to full electrification with and without more advanced DER technologies. We analyzed which packages of DERs most reliably enable demand flexibility in response to a time-of-use (TOU) rate for this and similar neighborhoods. Our buildings-to-grid co-simulation framework includes a generic secondary distribution feeder model to capture voltage profiles, transformer loading, and other grid impacts in each case. We also calculated the carbon emissions associated with energy use in the community. The methodology developed here can be broadly applied to community-scale beneficial electrification studies in other regions, climates, utility infrastructures, and building typologies to make specific, targeted recommendations based on quantified projections of energy demand in any given community. Our findings indicate that residential electrification can be achieved without negatively impacting the monthly utility bill, and that a combination of conventional energy-efficiency measures, PV, battery, controls, and managed EV charging to maximize a community’s demand flexibility is a promising strategy. Adding DERs (especially PV) as part of efficient electrification produces much bigger savings than efficient electrification without DERs. A key barrier is that upgrades require upfront costs, and modest utility bill savings result in long payback periods.

Suggested Citation

  • Earle, Lieko & Maguire, Jeff & Munankarmi, Prateek & Roberts, David, 2023. "The impact of energy-efficiency upgrades and other distributed energy resources on a residential neighborhood-scale electrification retrofit," Applied Energy, Elsevier, vol. 329(C).
  • Handle: RePEc:eee:appene:v:329:y:2023:i:c:s0306261922015136
    DOI: 10.1016/j.apenergy.2022.120256
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    References listed on IDEAS

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    1. Blonsky, Michael & Maguire, Jeff & McKenna, Killian & Cutler, Dylan & Balamurugan, Sivasathya Pradha & Jin, Xin, 2021. "OCHRE: The Object-oriented, Controllable, High-resolution Residential Energy Model for Dynamic Integration Studies," Applied Energy, Elsevier, vol. 290(C).
    2. Francesco Mancini & Benedetto Nastasi, 2019. "Energy Retrofitting Effects on the Energy Flexibility of Dwellings," Energies, MDPI, vol. 12(14), pages 1-19, July.
    3. White, Philip R. & Rhodes, Joshua D. & Wilson, Eric J.H. & Webber, Michael E., 2021. "Quantifying the impact of residential space heating electrification on the Texas electric grid," Applied Energy, Elsevier, vol. 298(C).
    4. Jin, Xin & Baker, Kyri & Christensen, Dane & Isley, Steven, 2017. "Foresee: A user-centric home energy management system for energy efficiency and demand response," Applied Energy, Elsevier, vol. 205(C), pages 1583-1595.
    5. 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.
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    1. Johari, F. & Lindberg, O. & Ramadhani, U.H. & Shadram, F. & Munkhammar, J. & Widén, J., 2024. "Analysis of large-scale energy retrofit of residential buildings and their impact on the electricity grid using a validated UBEM," Applied Energy, Elsevier, vol. 361(C).
    2. Luo, Jianing & Yuan, Yanping & Joybari, Mahmood Mastani & Cao, Xiaoling, 2024. "Development of a prediction-based scheduling control strategy with V2B mode for PV-building-EV integrated systems," Renewable Energy, Elsevier, vol. 224(C).
    3. Riccardo Fraboni & Gianluca Grazieschi & Simon Pezzutto & Benjamin Mitterrutzner & Eric Wilczynski, 2023. "Environmental Assessment of Residential Space Heating and Cooling Technologies in Europe: A Review of 11 European Member States," Sustainability, MDPI, vol. 15(5), pages 1-22, February.
    4. Marco Noro & Filippo Busato, 2023. "Energy Saving, Energy Efficiency or Renewable Energy: Which Is Better for the Decarbonization of the Residential Sector in Italy?," Energies, MDPI, vol. 16(8), pages 1-21, April.

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