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A two-stage stochastic model for energy contracting decisions of an industrial consumer

To encourage industrial consumers to participate more actively in deregulated energy markets, it is necessary to provide them with optimization tools to manage the risk derived from energy price uncertainty. With the risk measures selected, safety-first and value-at-risk, two bi-objective mixed-integer linear stochastic problems are implemented. These models obtain, through a risk-aversion parameter, a tradeoff between the risk measure and the expected cost of the total energy supply cost of industrial consumers. The efficient frontiers obtained with the safety-first and value-at-risk models are compared in a realistic case example. The model presented here extends the use of stochastic programming as an integrated decision support tool for industrial consumers to participate in energy markets.