In this paper, we presented the performance of forecasting model and error correction will affect the accuracy of short-term load forecasting. Least squares support vector machines (LS-SVM) based on improved particle swarm optimization is selected as load forecasting model. Forecasting accuracy and generalization performance of LS-SVM depend on selection of its parameters greatly. Adaptive part...

This paper proposes a novel hybrid algorithm namely APSO-BFO which combines merits of Bacterial Foraging Optimization (BFO) algorithm and Adaptive Particle Swarm Optimization (APSO) algorithm to determine the optimal PID parameters for control of nonlinear systems. To balance between exploration and exploitation, the proposed hybrid algorithm accomplishes global search over the whole search spa...

This paper presents swarm intelligence based Adaptive Particle Swarm Optimization (APSO) technique to determine optimum design of Switched Reluctance Machine (SRM). In APSO technique, the inertia weight factor is made adaptive on the basis of objective functions of the current and best solutions to avoid premature convergence. The SRM design is treated as nonlinear multivariable constrained opt...

In the proposed work, authors have applied swarm intelligence based algorithms for the effective Co-ordination of Flexible AC transmission system (FACTS) devices with other existing Var sources present in the network. IEEE 30 and IEEE 57 bus systems are taken as standard test systems. SPSO (Simple Particle Swarm Optimization) and other two swarm based intelligence approaches like APSO (Adaptive...

Bilinear models can approximate a large class of nonlinear systems adequately and usually with considerable parsimony in the number of coefficients required. This paper presents the application of Particle Swarm Optimization (PSO) algorithm to solve both offline and online parameter estimation problem for bilinear systems. First, an Adaptive Particle Swarm Optimization (APSO) is proposed to inc...

This paper proposes a novel hybrid algorithm namely APSO-BFO which combines merits of Bacterial Foraging Optimization (BFO) algorithm and Adaptive Particle Swarm Optimization (APSO) algorithm to determine the optimal PID parameters for control of nonlinear systems. To balance between exploration and exploitation, the proposed hybrid algorithm accomplishes global search over the whole search spa...

A computationally efficient global optimization method, the adaptive particle swarm optimization (APSO), is proposed for the synthesis of uniform and Gaussian amplitude arrays of two cases, i.e., the prior constraint in the synthesis of the element positions for both the cases is dmin = 0.5 λ, where dmin is the minimum distance between two adjacent elements. The upper limit in the distance betw...

This paper describes a new stochastic heuristic algorithm in engineering problem optimization especially in power system applications. An improved particle swarm optimization (PSO), called Adaptive particle swarm optimization (APSO), mixed with simulated annealing (SA) that will be named APSO-SA is introduced. This algorithm uses a novel PSO algorithm (APSO) to increase convergence rate and inc...

Optimization algorithms are very important for the Optimal Power Flow (OPF). They could be divided into two classes: traditional local search methods and heuristic global ones. Interior point (IP) algorithm has been known as one of the most prominent and fastest method, but its local exploitation characteristic leads to the fact that it could be easily trapped by local optimum. However, heurist...

This paper describes a new stochastic heuristic algorithm in engineering problem optimization especially in power system applications. An improved particle swarm optimization (PSO) called adaptive particle swarm optimization (APSO), mixed with simulated annealing (SA), is introduced and referred to as APSO-SA. This algorithm uses a novel PSO algorithm (APSO) to increase the convergence rate and...