Optimizing Equity in Energy Policy Interventions: A Quantitative Decision-Support Framework for Energy Justice: Article No. 119771

Miguel Heleno; Benjamin Sigrin; Natalie Popovich; Jenny Heeter; Michael Reiner; Tony Reames

doi:10.1016/j.apenergy.2022.119771

Optimizing Equity in Energy Policy Interventions: A Quantitative Decision-Support Framework for Energy Justice: Article No. 119771

Miguel Heleno
, Benjamin Sigrin
, Natalie Popovich
, Jenny Heeter
, Michael Reiner
, Tony Reames

Accelerated Deployment and Decision Support

Lawrence Berkeley National Laboratory
National Renewable Energy Laboratory
United States Department of Energy

Research output: Contribution to journal › Article › peer-review

54 Scopus Citations

Abstract

This paper presents a quantitative framework to support policy decision-making around equitable energy interventions. By combining sociodemographic and techno-economic models in the energy space, we propose a linear programming model to calculate the optimal portfolio of energy investments that explicitly minimizes the energy burden of a given population of energy insecure households. The model is formulated as a multi-objective optimization suitable to support the decisions on weatherization and deployment of distributed energy resources. We illustrate our methodology with a case study involving a population of 14,043 energy insecure households in Wayne County, Detroit, United States.

Original language	American English
Number of pages	11
Journal	Applied Energy
Volume	325
DOIs	https://doi.org/10.1016/j.apenergy.2022.119771
State	Published - 2022

NLR Publication Number

NREL/JA-7A40-83854

Keywords

DER deployment
energy burden
energy justice
equity
weatherization

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10.1016/j.apenergy.2022.119771

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title = "Optimizing Equity in Energy Policy Interventions: A Quantitative Decision-Support Framework for Energy Justice: Article No. 119771",

abstract = "This paper presents a quantitative framework to support policy decision-making around equitable energy interventions. By combining sociodemographic and techno-economic models in the energy space, we propose a linear programming model to calculate the optimal portfolio of energy investments that explicitly minimizes the energy burden of a given population of energy insecure households. The model is formulated as a multi-objective optimization suitable to support the decisions on weatherization and deployment of distributed energy resources. We illustrate our methodology with a case study involving a population of 14,043 energy insecure households in Wayne County, Detroit, United States.",

keywords = "DER deployment, energy burden, energy justice, equity, weatherization",

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doi = "10.1016/j.apenergy.2022.119771",

language = "American English",

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T1 - Optimizing Equity in Energy Policy Interventions: A Quantitative Decision-Support Framework for Energy Justice

T2 - Article No. 119771

AU - Heleno, Miguel

AU - Sigrin, Benjamin

AU - Popovich, Natalie

AU - Heeter, Jenny

AU - Reiner, Michael

AU - Reames, Tony

PY - 2022

Y1 - 2022

N2 - This paper presents a quantitative framework to support policy decision-making around equitable energy interventions. By combining sociodemographic and techno-economic models in the energy space, we propose a linear programming model to calculate the optimal portfolio of energy investments that explicitly minimizes the energy burden of a given population of energy insecure households. The model is formulated as a multi-objective optimization suitable to support the decisions on weatherization and deployment of distributed energy resources. We illustrate our methodology with a case study involving a population of 14,043 energy insecure households in Wayne County, Detroit, United States.

AB - This paper presents a quantitative framework to support policy decision-making around equitable energy interventions. By combining sociodemographic and techno-economic models in the energy space, we propose a linear programming model to calculate the optimal portfolio of energy investments that explicitly minimizes the energy burden of a given population of energy insecure households. The model is formulated as a multi-objective optimization suitable to support the decisions on weatherization and deployment of distributed energy resources. We illustrate our methodology with a case study involving a population of 14,043 energy insecure households in Wayne County, Detroit, United States.

KW - DER deployment

KW - energy burden

KW - energy justice

KW - equity

KW - weatherization

U2 - 10.1016/j.apenergy.2022.119771

DO - 10.1016/j.apenergy.2022.119771

M3 - Article

SN - 0306-2619

VL - 325

JO - Applied Energy

JF - Applied Energy

ER -

Optimizing Equity in Energy Policy Interventions: A Quantitative Decision-Support Framework for Energy Justice: Article No. 119771

Abstract

NLR Publication Number

Keywords

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