In recent years, the increasing application of nonlinear and unbalanced electronic equipment and large single phase loads have made voltage imbalance a serious problem in power distribution systems. A novel approach h...In recent years, the increasing application of nonlinear and unbalanced electronic equipment and large single phase loads have made voltage imbalance a serious problem in power distribution systems. A novel approach has been proposed to eliminate voltage imbalance and disturbances. The main strategy of this scheme is based on series active filter. By improving control circuit toward existing schemes and proposing a new strategy to control the voltage amplitude, simultaneous elimination of voltage imbalance, faults, voltage harmonics and also compensation of voltage drop in transmission lines become possible. Eventually, the voltage on the load side is a perfectly balanced three phase voltage with specific proper amplitude. The proposed scheme has been simulated in a test network and the results show high capability of this scheme for the complete elimination of imbalance without phase shift.展开更多
The K-means algorithm is one of the most popular techniques in clustering. Nevertheless, the performance of the Kmeans algorithm depends highly on initial cluster centers and converges to local minima. This paper prop...The K-means algorithm is one of the most popular techniques in clustering. Nevertheless, the performance of the Kmeans algorithm depends highly on initial cluster centers and converges to local minima. This paper proposes a hybrid evolutionary programming based clustering algorithm, called PSO-SA, by combining particle swarm optimization (PSO) and simulated annealing (SA). The basic idea is to search around the global solution by SA and to increase the information exchange among particles using a mutation operator to escape local optima. Three datasets, Iris, Wisconsin Breast Cancer, and Ripley's Glass, have been considered to show the effectiveness of the proposed clustering algorithm in providing optimal clusters. The simulation results show that the PSO-SA clustering algorithm not only has a better response but also converges more quickly than the K-means, PSO, and SA algorithms.展开更多
文摘In recent years, the increasing application of nonlinear and unbalanced electronic equipment and large single phase loads have made voltage imbalance a serious problem in power distribution systems. A novel approach has been proposed to eliminate voltage imbalance and disturbances. The main strategy of this scheme is based on series active filter. By improving control circuit toward existing schemes and proposing a new strategy to control the voltage amplitude, simultaneous elimination of voltage imbalance, faults, voltage harmonics and also compensation of voltage drop in transmission lines become possible. Eventually, the voltage on the load side is a perfectly balanced three phase voltage with specific proper amplitude. The proposed scheme has been simulated in a test network and the results show high capability of this scheme for the complete elimination of imbalance without phase shift.
文摘The K-means algorithm is one of the most popular techniques in clustering. Nevertheless, the performance of the Kmeans algorithm depends highly on initial cluster centers and converges to local minima. This paper proposes a hybrid evolutionary programming based clustering algorithm, called PSO-SA, by combining particle swarm optimization (PSO) and simulated annealing (SA). The basic idea is to search around the global solution by SA and to increase the information exchange among particles using a mutation operator to escape local optima. Three datasets, Iris, Wisconsin Breast Cancer, and Ripley's Glass, have been considered to show the effectiveness of the proposed clustering algorithm in providing optimal clusters. The simulation results show that the PSO-SA clustering algorithm not only has a better response but also converges more quickly than the K-means, PSO, and SA algorithms.
