Modeling Inflow Uncertainty in Electricity Markets: A Stochastic MCP Approach

Abstract

This paper proposes a new approach for addressing the long term hydrothermal coordination of a generation company operating in a competitive market, fully adapted to represent hydro-schedulingin an inflow uncertainty context. The proposed approach employs the traditional Stochastic Dynamic Programming (SDP) methodology. Since the modeling of the market behavior in these new conditions does not fits the traditional cost minimization scheme, the sub-models at each SDP stage are stated as Mixed Complementarity Problems (MCP) in order to properly represent the electricity market equilibrium. Each MCP sub-model sets up the Cournot market equilibrium by formulating the equations that express the optimal behavior of the generation companies, considering both stochastic hydraulic inflows and technical constraints that affect the scheduling of their units. The hydrothermal coordination stochastic model has been developed and implemented in GAMS. A case study is also presented to show its successful application to a large-scale electric power system such as the Spanish one.