Integer fuzzy credibility constrained programming for power system management

In this study, an environmentally friendly model of regional power system was developed to minimize the total cost of a regional power system consisting of an independent power grid. SO2 emission is controlled and capacity expansion is scheduled. In the system, the deterministic variables represent the power supplied from different energy conversion facilities. The binary variables refer to expansions for electricity conversion facilities, with three options given to each technology. To solve this model, an integer credibility constrained programming (ICCP) is developed by incorporating the concepts of credibility based chance constrained programming and mixed integer programming within an optimization framework. ICCP can explicitly address planning problems and systematic uncertainties without unrealistic simplifications. In application, a comparative benefit motivated electricity production system is proposed without SO2 control. Results of two cases are compared which show significant effect of emission control. By setting different credibility levels in constraints, it is able to find that the higher the credibility of energy supply satisfying the needs and total SO2 emission being less than its allowance, and the higher the total energy and lower coal-fired electricity supplies, the higher the total operational costs.