An Interval-Parameter Chance-Constraint Mixed-Integer Programming for Energy Systems Planning Under Uncertainty

Abstract Energy management systems are fraught with uncertainties. Such uncertainties may be expressed by interval numbers or probability distributions. In addition, issues of capacity expansion related to timing, sizing, and siting under such uncertainties need to be addressed. In this article, an interval-parameter chance-constraint mixed-integer programming (ICCP) is developed to tackle highly uncertain problems in energy management systems through integrating interval-parameter linear programming and chance-constraint programming. The developed model is then applied to a regional energy system. The results indicate that ICCP can effectively deal with uncertain information in energy management systems.

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