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Application of DSAPSO Algorithm in Distribution network Reconfiguration with Distributed Generation

Energy Engineering 2024年第1期121卷 187-201页

作者： Caixia Tao Shize Yang Taiguo Li School of Automation and Electrical Engineering Lanzhou Jiaotong UniversityLanzhou730070China

With the current integration of distributed energy resources into the grid,the structure of distribution networks is becoming more *** complexity significantly expands the solution space in the optimization process for network reconstruction using intelligent ***,traditional intelligent algorithms frequently encounter insufficient search accuracy and become trapped in local *** tackle this issue,a more advanced particle swarm optimization algorithm is *** address the varying emphases at different stages of the optimization process,a dynamic strategy is implemented to regulate the social and self-learning *** Metropolis criterion is introduced into the simulated annealing algorithm to occasionally accept suboptimal solutions,thereby mitigating premature convergence in the population optimization *** inertia weight is adjusted using the logistic mapping technique to maintain a balance between the algorithm’s global and local search *** incorporation of the Pareto principle involves the consideration of network losses and voltage deviations as objective functions.A fuzzy membership function is employed for selecting the *** analysis is carried out on the restructuring of the distribution network,using the IEEE-33 node system and the IEEE-69 node system as examples,in conjunction with the integration of distributed energy *** findings demonstrate that,in comparison to other intelligent optimization algorithms,the proposed enhanced algorithm demonstrates a shorter convergence time and effectively reduces active power losses within the ***,it enhances the amplitude of node voltages,thereby improving the stability of distribution network operations and power supply ***,the algorithm exhibits a high level of generality and applicability.

关键词： Reconfiguration of distribution network distributed generation particle swarm optimization algorithm simulated annealing algorithm active network loss

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Research On Multi-Objective Reactive Power Optimization Based on Modified Particle Swarm Optimization Algorithm

Research On Multi-Objective Reactive Power Optimization Base...

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2010 Chinese Control and Decision Conference

作者： Jianhua Wu,Nan Li,Lihong He,Bin Yin,Jianhua Guo,Yaqiong Liu School of Information Science and Engineering,Northeastern University,Shenyang,110004

＜正＞This paper proposes modified Multi-Objective Particle Swarm Optimization（MPSO） algorithm based on Pareto solution to overcome the conventional MPSO algorithm can easily fall into its local maximum value and improve the diversity of solution *** algorithm is composition of a modified Tabu Search with Multi-Objective Particle Swarm Optimization（TSMPSO）.With this algorithm Establishing the memory devices- taboo list of global optimal solution,Store the history of the particle that is selected to be the optimal *** through this approach to strengthen performance of particle swarm optimization in global and local *** is simple and easy to *** results of IEEE 30-bus system show that this algorithm can enhance power system voltage stability,meanwhile economic operation of power system is also implemented,thus the effectiveness and superiority of TSMPSO algorithm are verified.

关键词： Multi-Objective Reactive Power Optimization TABU voltage stability active network loss PSO MPSO

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