Long-term generation expansion planning employing dynamic programming and fuzzy techniques

This research proposes a new method for long-term generation expansion planning. The method adopts a multi-aspect optimal approach which considers the capital cost of the newly added units, the maintenance and fuel costs, environmental impact, reliability, etc. To accommodate the growth of power load, the generation capacity needs to expand to meet the load demand. In order to find an optimal alternative to increase the generation capacity and satisfy different constraints economically and efficiently, the optimization technique is employed. The dynamic programming (DP) as the optimization method is used in this study. Since the requirements of environmental standard and power quality are getting more and more strict, economical factors are no more the unique one to weigh for the generation expansion planning. The environmental protection and reliability are also important factors of the problem. However, types of pollution are very complicated and are not easy to incorporate into the solution model. In this research, we apply the fuzzy theory to represent the state of pollution and judge if a combination of investment is acceptable or not. Moreover by employing the fuzzy technique, we can delete a lot of unnecessary paths and states to reduce the computation burden of DP. Finally we use an example to illustrate and prove the applicability and validity of the presented approach.