ICCSIP: An Inexact Chance-Constrained Semi-infinite Programming Approach for Energy Systems Planning under Uncertainty

Abstract

This article developed an inexact chance-constrained semi-infinite programming (ICCSIP) method for the energy management system under functional interval uncertainties. The approach not only considers the left-hand interval parameters, right-hand distribution information, and the probability of violating constraint, but also deals with functional interval uncertainty, which extends the range of the uncertainties. A regional energy management system is applied to illustrate the applicability of the ICCSIP approach. In consideration of energy sources allocation, fuel prices, and environmental regulations, a systematic planning of the regional energy structure is desired to bring a significant increase of economic benefit and improvement of environmental quality. This problem can be formulated as a programming model with an objective of minimizing the overall system costs subject to a number of environmental, economic and energy sources availability constraints. The programming results indicate that reasonable and useful decision alternatives can be generated under different probabilities of violating the system constraints. The obtained results are useful for decision makers to gain an insight into the tradeoffs among environmental, economic and system reliability criteria.

Keywords:

• chance-constrained programming
• energy management system
• functional interval
• semi-infinite programming
• uncertainty

Acknowledgments

This research was supported by the Major State Basic Research Development Program of MOST (2005CB724200 and 2006CB403307) and the Natural Science and Engineering Research Council of Canada.