An interval-parameter minimax regret programming approach for power management systems planning under uncertainty

In this study, an interval-parameter minimax regret programming (IMRP) method is developed for supporting the power management systems planning under uncertainty. This method incorporates techniques of interval linear programming (ILP) and minimax regret programming (MRP) within a general optimization framework. The developed IMRP could deal with multiple policy scenarios associated with different costs and risk levels without making any assumptions. It can analyze various economic consequences for all of the possible scenarios through minimizing the maximum cost regret values. The IMRP approach can successfully reduce the worst regrets incurred under the pre-regulated targets. Moreover, it can deal with uncertainties and complexities expressed as interval numbers. A case study of power management systems planning is then presented for demonstrating applicability of the developed approach. The results indicate that many decision alternatives are generated based on the interval solutions which can help decision makers identify the desired system designs with minimized economic cost loss and system-failure risk under uncertainty. The trade-off between system regret and security-failure risk can be handled effectively through this method. And the generated solutions can also provide multiple electric power generation patterns and capacity expansion schemes under the optimal strategy obtained through the developed IMRP method. It is indicated that the proposed method is efficient to provide the decision makers with available plans in actual operation of power management systems.