期刊名称：IAENG International Journal of Computer Science
印刷版ISSN：1819-656X
电子版ISSN：1819-9224
出版年度：2021
卷号：48
期号：4
语种：English
出版社：IAENG - International Association of Engineers
摘要：Tree seed algorithm (TSA) is a heuristic search algorithm that deals with low-dimensional issues. To overcome the deficiency of TSA in solving environmental economic power dispatch (EED) problem with high-dimensional, nonlinear, and non-convex characteristics, this article proposes a novel multiobjective tree seed algorithm (MONTSA), which possesses superior ability to obtain Pareto optimal solution (POS) sets. For expanding the search space as well as balancing the ability of exploration and exploitation about TSA, three modification strategies, including dynamic search tendency (ST), Gaussian mutation mechanism and variation mechanism of differential evolution algorithm based on Cauchy mutation strategy are adopted to constitute MONTSA. In addition, a constraint handling technique to make sure zero constraint violation and non-inferior sorting approach based on dynamic crowding distance are also put forward. The above introduced strategies allow MONTSA to obtain POS with better distribution. Eight cases, containing four objectives of fuel cost, pollution emission, power loss and fuel cost with valve point effect, are experimented on IEEE 30 bus, IEEE 57 bus and IEEE 118 bus test systems. The results reveal that, compared with MOTSA and MOPSO/MODE, MONTSA is effectively capable of addressing EED problem, which is able to obtain uniformly distributed Pareto frontiers (PFs) and better best compromise solution (BCS). Eventually, the performance indicators GD and HV show that PFs and BCS obtained by MONTSA are more outstanding than the rest of algorithms, with uniform distribution, strong convergence and powerful stability.
关键词：Environment economic power dispatch;novel multi-objective tree seed algorithm;a novel constraint handling technique
