Non-Convex Economic Dispatch with Prohibited Operating Zones through Gravitational Search Algorithm

This paper presents a new approach to the solution of optimal power generation for economic load dispatch (ELD) using gravitational search algorithm (GSA) when all the generators include valve point effects and some/all of the generators have prohibited operating zones. In this paper a gravitational search algorithm is suggested that deals with equality and inequality constraints in ELD problems. A constraint treatment mechanism is also discussed to accelerate the optimization process. To verify the robustness and superiority of the proposed GSA based approach, a practical sized 40-generators case with valve point effects and prohibited operating zones is considered. The simulation results reveal that the proposed GSA approach ensures convergence within an acceptable execution time and provides highly optimal solution as compared to the results obtained from well established heuristic optimization approaches

Fuzzy Controlled Parallel PSO to Solving Large Practical Economic Dispatch

International audienceThis paper proposes a version of fuzzy controlled parallel particle swarm optimization approach based decomposed network (FCP-PSO) to solve large nonconvex economic dispatch problems. The proposed approach combines practical experience extracted from global database formulated in fuzzy rules to adjust dynamically the three parameters associated to PSO mechanism search. The adaptive PSO executed in parallel based in decomposed network procedure as a local search to explore the search space very effectively. The robustness of the proposed modified PSO tested on 40 generating units with prohibited zones and compared with recent hybrid global optimization methods. The results show that the proposed approach can converge to the near solution and obtain a competitive solution with a reasonable time compared with recent previous approaches

Chaos-Enhanced Cuckoo Search for Economic Dispatch with Valve Point Effects

Economic dispatch determines the optimal generation outputs to minimize the toal fuel cost while satisfying the load demand and operational constraints. Modern optimization techniques fail to solve the problem in a robust manner and finding robust global optimization techniques is necessary for efficient system operation. In this study, the potentiality of introducing chaos into the standard Cuckoo Search (CS) in order to further enhance its global search ability is investigated. Deterministic chaotic maps are random-based techniques that can provide a balanced exploration and exploitation searches for the algorithm. Four different variants are generated by carefully choosing four different locations (within the standard CS) with potential adoption of a candidate chaotic map.Then detailed studies are carried out on benchmark power system problems with four different locations to find out the most efficient one. The best of all test cases generated is chosen and compared with algorithms presented in the literature. The results show that the proposed method with the proposed chaotic map outperforms standard CS. Additionally, the chaos-enhanced CS has a very good performance in comparison with QPSO and NSS

Modified moth swarm algorithm for optimal economic load dispatch problem

In this study, optimal economic load dispatch problem (OELD) is resolved by a novel improved algorithm. The proposed modified moth swarm algorithm (MMSA), is developed by proposing two modifications on the classical moth swarm algorithm (MSA). The first modification applies an effective formula to replace an ineffective formula of the mutation technique. The second modification is to cancel the crossover technique. For proving the efficient improvements of the proposed method, different systems with discontinuous objective functions as well as complicated constraints are used. Experiment results on the investigated cases show that the proposed method can get less cost and achieve stable search ability than MSA. As compared to other previous methods, MMSA can archive equal or better results. From this view, it can give a conclusion that MMSA method can be valued as a useful method for OELD problem

Particle Swarm Optimization Solution for Power System Operation Problems

Application of particle swarm optimization (PSO) algorithm on power system operation is studied in this chapter. Relay protection coordination in distribution networks and economic dispatch of generators in the grid are defined as two of power system-related optimization problems where they are solved using PSO. Two case study systems are conducted. The first case study system investigates applicability of PSO on providing proper overcurrent relay settings in the grid, while in the second case study system, the economic dispatch of a 15-unit system is solved where PSO successfully provides the optimum power output of generators with minimum fuel costs to satisfy the load demands and operation constraints. The simulation results in comparison with other methods show the effectiveness of PSO against other algorithms with higher quality of solution and less fuel costs on the same test system