Short-term scheduling of hybrid thermal, pumped-storage, and wind plants using firefly optimization algorithm

This paper presents a novel method based on an enhanced firefly algorithm (EFA) to solve scheduling hybrid thermal, pumped-storage, and wind plants. Since the problem is inherently discrete, basic EFA binary encoding/decoding techniques are used in proposed approach. Optimal power values of thermal pumped-storage units determined separately presence uncertainty caused by speed. The applied real plant, including four units, 34 with different characteristics, one turbine plant. In addition, dynamic constraints upstream downstream sources regarding also considered for finding optimal solution. successfully results compared those three available methods. show that has converted more cost than other