To solve the non-differentiable optimal power flow (OPF) problems with multiple contradictory objectives, a modified pigeon-inspired optimization algorithm (MPIO) is put forward in this paper. Combining with the commo...
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To solve the non-differentiable optimal power flow (OPF) problems with multiple contradictory objectives, a modified pigeon-inspired optimization algorithm (MPIO) is put forward in this paper. Combining with the common-used penalty function method (PFM), the MPIO-PFM algorithm is proposed and applied to optimize the active power loss, emission and fuel cost (with valve-point loadings) of power system. Eight simulation trials carried out on MATLAB software validate MPIO-PFM algorithm can obtain superior Pareto Frontier (PF) comparing with the typical NSGA-II algorithm. Nevertheless, some Pareto solutions obtained by MPIO-PFM algorithm cannot satisfy all system constraints due to the difficulty in choosing the proper penalty coefficients. Thus, an innovative approach named as constraint-objective sorting rule (COSR) is presented in this paper. The bi-objective and tri-objective trials implemented on IEEE 30-node, 57-node and 118-node systems demonstrate that the Pareto optimal set (POS) obtained by MPIO-COSR algorithm realizes zero-violation of various system constraints. Furthermore, the generational-distance and hyper-volume indexes quantitatively illustrate that in contrast to NSGA-II and MPIO-PFM methods, the MPIO-COSR algorithm can determine the evenly-distributed PFs with satisfactory-diversity. The intelligent MPIO-COSR algorithm provides an effective way to handle the non-convex MOOPF problems. (C) 2020 Elsevier B.V. All rights reserved.
作者：
Ran HaoDelin LuoHaibin DuanSchool of Reliability and Systems Engineering
Beihang UniversityBeijing100191 China Department of AutomationXiamen UniversityXiamenChina Science and Technology on Aircraft Control LaboratorySchool of Automation Science and Electrical EngineeringBeihang UniversityBeijingChina
Unmanned aerial vehicles (UAVs) have shown their superiority for applications in performing military and civilian *** which,multiple UAVs mission assignment is becoming more important for today's military *** ...
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ISBN:
(纸本)9781479946983
Unmanned aerial vehicles (UAVs) have shown their superiority for applications in performing military and civilian *** which,multiple UAVs mission assignment is becoming more important for today's military *** far,there have been many bio-inspired computation algorithms for solving multiple UAVs mission assignment problems,including particle swarm optimization (PSO),differential evolution algorithm (DE) and so ***,deficiencies of these approaches exist inevitably,which cannot satisfy the requirements of dynamic mission *** this paper,a new UAV assignment model focusing on the energy consumption of UAV is brought up which can be easily applied to intelligence ***,we propose a new approach by applying the modifiedpigeon-inspiredoptimization (PIO) algorithm to sovle the multiple UAVs mission assignment *** simulation results show that the modified PIO algorithm is more effective when compared with other state-of-the-art algorithms in addressing mission assignment problem for multiple UAVs.
In order to solve the problem that PI controller has difficulty in parameter setting in PMSM, a PI parameter setting method for PMSM speed control system based on modified pigeon-inspired optimization algorithm is pro...
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ISBN:
(数字)9781665458641
ISBN:
(纸本)9781665458641
In order to solve the problem that PI controller has difficulty in parameter setting in PMSM, a PI parameter setting method for PMSM speed control system based on modified pigeon-inspired optimization algorithm is proposed. The algorithm of pigeon-inspiredoptimization was combined with Powell search algorithm, so that the convergence speed was improved by using the direct search characteristic of Powell algorithm. The PI controller parameters are taken as the output of the algorithm, and the optimal PI control parameters can be obtained after several iterations. Simulation results show that the PI controller optimized by the modified pigeon-inspired optimization algorithm has good *** proposed method greatly reduces overshoot and shortens response time.
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