To research the problem on the multi-objective reactive power optimization, to utilize the theory of multi-objective fuzzy optimization to change the multi-objectiveoptimization into the single-objectiveoptimization...
详细信息
ISBN:
(纸本)9781627485654
To research the problem on the multi-objective reactive power optimization, to utilize the theory of multi-objective fuzzy optimization to change the multi-objectiveoptimization into the single-objectiveoptimization and to adopt the fuzzy adaptive particle swarm algorithm to carry out solutions. Comprehensively considering the security and economical efficiency of the system, as well as the condition of the operation constraints, to propose a comprehensive and practical multi-objective reactive power optimization model. To consider the multi-objective reactive power optimization model of the voltage stability index can optimize the economic benefit and safety benefit of the system. Applying the theory of multi-objective fuzzy optimization combined with the adaptive particle swarm optimization algorithm to the problem of the multi-objective reactive power optimization could solve the problem of the different dimensional multi-objectiveoptimization in a better way. After adopting the fuzzy adaptive particle swarm algorithm, the superiorities, such as achieving the global optimal solution, reducing the computational complexity, and improving the computational efficiency, are displayed. (c) 2010 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of Society for Automobile, power and Energy Engineering
To research the problem on the multi-objective reactive power optimization, to utilize the theory of multiobjective fuzzy optimization to change the multi-objectiveoptimization into the single-objectiveoptimization,...
详细信息
To research the problem on the multi-objective reactive power optimization, to utilize the theory of multiobjective fuzzy optimization to change the multi-objectiveoptimization into the single-objectiveoptimization, and to adopt the fuzzy adaptive particle swarm algorithm to carry out solutions. Comprehensively considering the security and economical efficiency of the system, as well as the condition of the operation constraints, to propose a comprehensive and practical multi-objective reactive power optimization model. To consider the multi-objective reactive power optimization model of the voltage stability index can optimize the economic benefit and safety benefit of the system. Applying the theory of multi-objective fuzzy optimization combined with the adaptive particle swarm optimization algorithm to the problem of the multi-objective reactive power optimization could solve the problem of the different dimensional multi-objectiveoptimization in a better way. After adopting the fuzzy adaptive particle swarm algorithm, the superiorities, such as achieving the global optimal solution, reducing the computational complexity, and improving the computational efficiency,are displayed.
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 t...
详细信息
ISBN:
(纸本)9781424451821
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 set. This 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 global. And through this approach to strengthen performance of particle swarm optimization in global and local searching. TSMPSO is simple and easy to implement. Simulation 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.
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 th...
详细信息
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.
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 t...
详细信息
ISBN:
(纸本)9781424451814;9781424451821
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 set. This 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 global. And through this approach to strengthen performance of particle swarm optimization in global and local searching. TSMPSO is simple and easy to implement. Simulation 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.
This paper presents a novel algorithm, multi-objective oriented search algorithm (MOOSA), to deal with the problem of multi-objective reactive power optimization in power system. The multi-objective oriented search al...
详细信息
ISBN:
(纸本)9783642040191
This paper presents a novel algorithm, multi-objective oriented search algorithm (MOOSA), to deal with the problem of multi-objective reactive power optimization in power system. The multi-objective oriented search algorithm has strong ability to search optimal solutions and well-distributed solutions in Pareto front. The results show that the proposed algorithm is able to balance the multi objects in multi-objective reactive power optimization through the simulations on IEEE 30-bus testing system. The paper concludes that MOOSA is an effective tool to handle the problem of multi-objective reactive power optimization.
暂无评论