Optimal short-term hydrothermal generation scheduling using modified seeker optimisation algorithm

This paper presents a new evolutionary optimisation algorithm to solve the short-term hydrothermal generation problem with operational constraints using the modified seeker optimisation algorithm. Seeker optimisation algorithm is a recently developed empirical gradient based, meta-heuristic optimisation algorithm, which draws inspiration from the random process of human search strategy. In this paper, we improvise the step length determination strategy in the classical seeker optimisation method by considering an optimistically contracting step length calculation. The proposed methodology easily takes care of solving non-linear hydrothermal generation problem along with different constraints like power balance, capacity limits, valve-point loading and prohibited operating zones. Simulations were performed over various standard test cases and a comparative study is carried out with other existing relevant approaches. The result obtained reveals the robustness and ability of the proposed methodology over other existing techniques.