Nuclear energy plays an important role in the U.S. energy mix that will likely need to be maintained or strengthened to achieve significant greenhouse gas reduction. However, maintaining the nuclear portfolio becomes increasingly challenging in the current U.S. energy market since the low price of natural gas and the penetration of subsidized and low-marginal cost variable renewable electricity (VRE) are affecting the profitability of nuclear units. Argonne has been acquiring the capability to model energy market economics in order to support decision makers and nuclear utilities. In particular, the EDGAR (Economic Dispatch Genetic AlgoRithms) code is developed at Argonne to solve the combined Unit Commitment and Economic Dispatch problems to find the optimal schedule of a fleet of generating units to meet the forecasted grid demand over the next day in deregulated markets with an hourly time resolution. This multi-laboratory effort is supported by the System Analysis and Integration campaign of the U.S. Department of Energy, Office of Nuclear Energy.
- R. Ponciroli, N. E. Stauff, J. Ramsey, F. Ganda and R. B. Vilim, “An Improved Genetic Algorithm approach to the Unit Commitment/Economic Dispatch problem,” in IEEE Transactions on Power Systems, April 2020.
- N. Stauff, G. Maronati, P. Talbot, A. Cuadra, R. Ponciroli, T. K. Kim, B. Dixon, T. A. Taiwo, “Energy Market Simulation Tools to Assess Competitiveness of Nuclear Power Plants,” proceedings of Global 2019, Seattle, WA, September 2019.
- N. Stauff, G. Maronati, R. Ponciroli, F. Ganda, T. Kim, T. Taiwo (ANL), A. Cuadra, M. Todosow (BNL), P. Talbot, C. Rabiti, B. Dixon (INL), S. Kim (PNNL), “Daily Market Analysis Capability and Results,” ANL/NSE-19/5, 2019.