Optimal operation of microgrid based on chaotic simulated annealing particle swarm algorithm

2016 ◽  
Author(s):  
Chun Wang ◽  
Junrong Xia ◽  
Wenyi Yan
Keyword(s):  
Simulated Annealing ◽  
Particle Swarm ◽  
Optimal Operation ◽  
Particle Swarm Algorithm ◽  
Swarm Algorithm ◽  
Chaotic Simulated Annealing

scholarly journals Application of Strongly Constrained Space Particle Swarm Optimization to Optimal Operation of a Reservoir System

2018 ◽  
Vol 10 (12) ◽  
pp. 4445 ◽  
Author(s):  
Lejun Ma ◽  
Huan Wang ◽  
Baohong Lu ◽  
Changjun Qi
Keyword(s):  
Particle Swarm Optimization ◽  
Computational Efficiency ◽  
Particle Swarm ◽  
Pso Algorithm ◽  
Optimal Operation ◽  
Computational Time ◽  
Particle Swarm Algorithm ◽  
Swarm Optimization ◽  
Swarm Algorithm ◽  
Low Efficiency

In view of the low efficiency of the particle swarm algorithm under multiple constraints of reservoir optimal operation, this paper introduces a particle swarm algorithm based on strongly constrained space. In the process of particle optimization, the algorithm eliminates the infeasible region that violates the water balance in order to reduce the influence of the unfeasible region on the particle evolution. In order to verify the effectiveness of the algorithm, it is applied to the calculation of reservoir optimal operation. Finally, this method is compared with the calculation results of the dynamic programming (DP) and particle swarm optimization (PSO) algorithm. The results show that: (1) the average computational time of strongly constrained particle swarm optimization (SCPSO) can be thought of as the same as the PSO algorithm and lesser than the DP algorithm under similar optimal value; and (2) the SCPSO algorithm has good performance in terms of finding near-optimal solutions, computational efficiency, and stability of optimization results. SCPSO not only improves the efficiency of particle evolution, but also avoids excessive improvement and affects the computational efficiency of the algorithm, which provides a convenient way for particle swarm optimization in reservoir optimal operation.

scholarly journals Modified particle swarm algorithm for the optimal water allocation of reservoir

2020 ◽  
Vol 20 (7) ◽  
pp. 2875-2883
Author(s):  
Zhihao Gong ◽  
Jilin Cheng ◽  
Yi Gong ◽  
Liang Wang ◽  
Cong Wei
Keyword(s):  
Heuristic Algorithms ◽  
Direct Method ◽  
Particle Swarm ◽  
Optimal Operation ◽  
Water Levels ◽  
Particle Swarm Algorithm ◽  
Probability Of Exceedance ◽  
Modified Method ◽  
Operation Rule ◽  
Swarm Algorithm

Abstract At present, meta-heuristic algorithms are the most popular methods for the optimization of the operations of reservoirs. In order to avoid inappropriate solutions, i.e. spills occurring when the reservoir is not full, a modified method is proposed that can adjust the trajectories of the particles, using the particle swarm algorithm, according to the operation rule of the reservoir. The method was tested in a case study, and was compared to two commonly used methods for generating particle position vectors. These included the direct method, which uses water supply and water spills as the iteration variables, and the indirect method, which uses water storages (water levels) as the iteration variables. The results showed that the three methods could achieve similar solutions at the 75% probability of exceedance. There was no difference in the convergence speeds or the final objective function values of the three models. However, at the 50% probability of exceedance, the modified method produced results that followed the operation rule of the reservoir, whereas the other two methods could lead to inappropriate water spills. This new method may provide a reference for other meta-heuristic algorithms in models of the optimal operation of reservoirs.

The Solution of the Structural Reliability Index Based on SAPSO

2011 ◽  
Vol 138-139 ◽  
pp. 410-415
Author(s):  
Ke Tong Liu ◽  
Ai Ping Tang
Keyword(s):  
Simulated Annealing ◽  
Optimization Algorithm ◽  
Reliability Index ◽  
Structural Reliability ◽  
Complex Structure ◽  
Particle Swarm ◽  
Particle Swarm Algorithm ◽  
Local Optimum ◽  
Reliability Method ◽  
Swarm Algorithm

In view of the shortcoming of the existing structural reliability calculation method, this paper establishes optimization model of the structural reliability index from the geometric meaning of the structural reliability index. Then, the authors propose a method based on improved particle swarm optimization algorithm for solving the reliability method. Particle swarm algorithm is easy to fall into local optimum. So, the authors construct simulated annealing particle swarm algorithm which has the strong local search ability .simulated annealing particle swarm algorithm is a global optimization algorithm. Using it to solve the reliability index can avoid doing partial derivatives to the structural performance function and the deficiency of traditional method is effectively overcomed which is easily being trapped in local optima. Therefore, it is a very effective method to solving the structural reliability index of the complex structure. In the end, some examples demonstrate the validity of this method.

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