Assessing the effects of power grid expansion on human health externalities

Mark Rodgers, David Coit, Frank Felder, Annmarie Carlton

Research output: Contribution to journalArticlepeer-review

12 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)92-104
Number of pages13
JournalSocio-Economic Planning Sciences
StatePublished - Jun 2019

All Science Journal Classification (ASJC) codes

  • Geography, Planning and Development
  • Economics and Econometrics
  • Strategy and Management
  • Statistics, Probability and Uncertainty
  • Management Science and Operations Research


  • Applied optimization
  • Generation expansion planning
  • Health damages
  • Pollutant emissions
  • Simulation


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