Combined grey relational analysis differential dynamic programming for short-term hydro generation scheduling

In this paper, a combined grey relational analysis/differential dynamic programming approach for short-term hydro generation scheduling is proposed. The purpose of short-term hydro scheduling is to find the optimal amount of generated power for the hydro units in the system for the next N (N=24 in this study) hour. In the proposed method, the differential dynamic programming procedures are performed offline on historical load data. The results are compiled and valuable information is obtained by using grey relational analysis. Using the information obtained from the analysis, the differential dynamic programming algorithm is then performed online to give the hydro generation schedule for the forecast load. The effectiveness of the proposed approach is demonstrated by the short-term hydro generation scheduling of the Taiwan power system, which consists of ten hydro plants. It is concluded from the results that the proposed approach can significantly reduce the execution time of the conventional differential dynamic programming algorithm when determining proper hydro generation schedules.