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A Metamodeling Framework for Quantifying Health Damages of Power Grid Expansion Plans.
Rodgers, Mark D; Coit, David W; Felder, Frank A; Carlton, Annmarie G.
Afiliação
  • Rodgers MD; Department of Supply Chain Management, Rutgers Business School, Newark, NJ 07102, USA. mrodgers@business.rutgers.edu.
  • Coit DW; Department of Industrial & Systems Engineering, Rutgers University, Piscataway, NJ 07102, USA. coit@soe.rutgers.edu.
  • Felder FA; Department of Industrial Engineering, Tsinghua University, 30 Shuangqing Rd, Haidian District, Beijing 10084, China. coit@soe.rutgers.edu.
  • Carlton AG; Center for Energy, Economic & Environmental Policy, Rutgers University, New Brunswick, NJ 07102, USA. ffelder@rutgers.edu.
Article em En | MEDLINE | ID: mdl-31130686
ABSTRACT
In this paper, we present an analytical framework to establish a closed-form relationship between electricity generation expansion planning decisions and the resulting negative health externalities. Typical electricity generation expansion planning models determine the optimal technology-capacity-investment strategy that minimizes total investment costs as well as fixed and variable operation and maintenance costs. However, the relationship between these long-term planning decisions and the associated health externalities is highly stochastic and nonlinear, and it is computationally expensive to evaluate. Thus, we developed a closed-form metamodel by executing computer-based experiments of a generation expansion planning model, and we analyzed the resulting model outputs in a United States Environmental Protection Agency (EPA) screening tool that approximates the associated human health externalities. Procedural guidance to verify the accuracy and to select key metamodel parameters to enhance its prediction capability is presented. Specifically, the metamodel presented in this paper can predict the resulting health damages of long-term power grid expansion decisions, thus, enabling researchers and policy makers to quickly assess the health implications of power grid expansion decisions with a high degree of certainty.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Eletricidade / Modelos Teóricos Tipo de estudo: Prognostic_studies Limite: Humans País/Região como assunto: America do norte Idioma: En Revista: Int J Environ Res Public Health Ano de publicação: 2019 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Eletricidade / Modelos Teóricos Tipo de estudo: Prognostic_studies Limite: Humans País/Região como assunto: America do norte Idioma: En Revista: Int J Environ Res Public Health Ano de publicação: 2019 Tipo de documento: Article