TY - JOUR
T1 - Assessing the effects of power grid expansion on human health externalities
AU - Rodgers, Mark
AU - Coit, David
AU - Felder, Frank
AU - Carlton, Annmarie
N1 - Funding Information:
Dr. Rodgers is an Assistant Professor in the Supply Chain Management Department of the Rutgers Business School, where he currently teaches Demand Planning. His research interests include power grid expansion planning, simulation-based optimization, and quantitative methods to assess the impact of supply chain disruptions and risk on operational performance. Dr. Rodgers holds a PhD in Industrial & Systems Engineering from Rutgers University, MS degrees in Statistics and Industrial & Systems Engineering from Rutgers University, a MEng in Pharmaceutical Manufacturing Practices from Stevens Institute of Technology, and a BS in Ceramics and Materials Science Engineering from Rutgers University. Additionally, he has presented his research at many academic conferences, and was also awarded an NSF Fellowship via the Integrative Graduate Education and Research Traineeship (IGERT) program. Prior to joining the Rutgers Business School's faculty, Dr. Rodgers worked in various roles in the telecommunications, pharmaceutical, transportation, and management consulting industries in various business process improvement and analytics roles.
Publisher Copyright:
© 2018 Elsevier Ltd
Copyright:
Copyright 2019 Elsevier B.V., All rights reserved.
PY - 2019/6
Y1 - 2019/6
N2 - Generation expansion planning is the framework under which power grid capacity expansions are made. Under this framework, mathematical optimization tools are used to determine the type of generation technology to invest in, and when and where these investments should be made in order to minimize market costs such as investment costs, fixed and variable operating & maintenance costs, and fuel costs over a long term planning horizon. Given the current infrastructure and policies, fossil fuels (such as coal, oil, and natural gas) are among the most economical sources of electricity. Thus, under these assumptions, these energy sources dominate the resulting expansion plans. However, fossil fuel combustion creates by-products contributing to ground-level ozone, particulates, and acid rain, which have harmful health implications such as premature death, respiratory-related illnesses, cardiovascular injuries, pulmonary disorders, and autism leading to lost days at school or work on a daily basis. In this research, we formulate a linear program to solve a multi-period generation expansion planning problem minimizing market costs for a centrally dispatched power system. We can then assess the human health externalities of the resulting expansion plan by studying the model output with an Environmental Protection Agency (EPA) screening tool that determines the human health externalities from the electricity sector. Results with and without emission limits and other policies can then be evaluated and compared based on predicted societal costs including human health externalities. This research enables policy makers to directly assess the health implications of power grid expansion decisions by explicitly estimating the total societal costs by quantifying externalities as part of the investment strategy.
AB - Generation expansion planning is the framework under which power grid capacity expansions are made. Under this framework, mathematical optimization tools are used to determine the type of generation technology to invest in, and when and where these investments should be made in order to minimize market costs such as investment costs, fixed and variable operating & maintenance costs, and fuel costs over a long term planning horizon. Given the current infrastructure and policies, fossil fuels (such as coal, oil, and natural gas) are among the most economical sources of electricity. Thus, under these assumptions, these energy sources dominate the resulting expansion plans. However, fossil fuel combustion creates by-products contributing to ground-level ozone, particulates, and acid rain, which have harmful health implications such as premature death, respiratory-related illnesses, cardiovascular injuries, pulmonary disorders, and autism leading to lost days at school or work on a daily basis. In this research, we formulate a linear program to solve a multi-period generation expansion planning problem minimizing market costs for a centrally dispatched power system. We can then assess the human health externalities of the resulting expansion plan by studying the model output with an Environmental Protection Agency (EPA) screening tool that determines the human health externalities from the electricity sector. Results with and without emission limits and other policies can then be evaluated and compared based on predicted societal costs including human health externalities. This research enables policy makers to directly assess the health implications of power grid expansion decisions by explicitly estimating the total societal costs by quantifying externalities as part of the investment strategy.
KW - Applied optimization
KW - Generation expansion planning
KW - Health damages
KW - Pollutant emissions
KW - Simulation
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U2 - 10.1016/j.seps.2018.07.011
DO - 10.1016/j.seps.2018.07.011
M3 - Article
AN - SCOPUS:85050610105
VL - 66
SP - 92
EP - 104
JO - Socio-Economic Planning Sciences
JF - Socio-Economic Planning Sciences
SN - 0038-0121
ER -