Estimating zonal electricity supply curves in transmission-constrained electricity markets

Mostafa Sahraei-Ardakani, Seth Blumsack, Andrew Kleit

Research output: Contribution to journalArticlepeer-review

10 Scopus citations


Many important electricity policy initiatives would directly affect the operation of electric power networks. This paper develops a method for estimating short-run zonal supply curves in transmission-constrained electricity markets that can be implemented quickly by policy analysts with training in statistical methods and with publicly available data. Our model enables analysis of distributional impacts of policies affecting operation of electric power grid. The method uses fuel prices and zonal electric loads to determine piecewise supply curves, identifying zonal electricity price and marginal fuel. We illustrate our methodology by estimating zonal impacts of Pennsylvania's Act 129, an energy efficiency and conservation policy. For most utilities in Pennsylvania, Act 129 would reduce the influence of natural gas on electricity price formation and increase the influence of coal. The total resulted savings would be around 267 million dollars, 82 percent of which would be enjoyed by the customers in Pennsylvania. We also analyze the impacts of imposing a $35/ton tax on carbon dioxide emissions. Our results show that the policy would increase the average prices in PJM by 47-89 percent under different fuel price scenarios in the short run, and would lead to short-run interfuel substitution between natural gas and coal.

Original languageEnglish (US)
Pages (from-to)10-19
Number of pages10
StatePublished - Feb 1 2015

All Science Journal Classification (ASJC) codes

  • Mechanical Engineering
  • Pollution
  • Energy Engineering and Power Technology
  • General Energy
  • Electrical and Electronic Engineering
  • Management, Monitoring, Policy and Law
  • Industrial and Manufacturing Engineering
  • Building and Construction
  • Fuel Technology
  • Renewable Energy, Sustainability and the Environment
  • Civil and Structural Engineering
  • Modeling and Simulation


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