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Distribution Feeder Reconfiguration (DFR) is an important technique to improve the performance of distribution networks. The common objectives considered in the DFR problem are power loss and voltage deviation which are important objectives for traditional distribution systems. Security issues cause by Distributed Generations (DGs) in modern distribution systems which can potentially jeopardize power system security has almost neglected in power system operation problem. Toward this end, this study considers the power loss, Voltage Stability Index (VSI), and number of switching as objective functions which can satisfy both operation and security expectations. The Backward-Forward Sweep (BFS) method known for easy convergence has been employed for power flow calculations. Because of the increase in DG penetration in distributed systems, the impacts of these units are investigated. A powerful optimization algorithm based on hybridization of Shuffled Frog Leaping Algorithm (SFLA) and Particle Swarm Optimization (PSO) is proposed to solve the proposed problem. The proposed algorithm is a combination of strong mutation operator, original SFLA and original PSO algorithms which has high population diversity and search ability. The proposed algorithm has been applied to a complex multimodal benchmark function and also two different distribution networks including 33- and 95-bus test systems. [ABSTRACT FROM AUTHOR]

Economic dispatch seeks for the most economical combination of generation units in power system while satisfying bunch of physical and operational constraints. Finding the most economical generation strategy in power markets with several generation zones is crucial for power system operation. Conventional economic dispatch models cannot find the most economical generation schedule in power system with different generation zones. Moreover, the most economical schedule of generation cannot satisfy the environmental expectations. Therefore, compromising between generation cost and environmental issues is unavoidable. In this connection, total emission produces by generation units is taken into consideration as an objective function in concert with generation cost function. Furthermore, different operational constraints including valve-point effect, prohibited operating zones and multi-fuel operation are considered to make the proposed approach more realistic. Considering all these restrictions necessitate solving the proposed problem, i.e. multi-objective multi-area economic dispatch problem, by a reliable and strong optimization algorithm. In this regard, a hybrid evolutionary algorithm based on the shuffle frog leaping algorithm and the particle swarm optimization is proposed to solve the proposed problem. Effectiveness of the proposed hybrid algorithm is verified on different test systems. [ABSTRACT FROM AUTHOR]

Abstract: Distribution feeders and substations need to provide additional capacity to serve the growing electrical demand of customers without compromising the reliability of the electrical networks. Also, more control devices, such as DG (Distributed Generation) units are being integrated into distribution feeders. Distribution networks were not planned to host these intermittent generation units before construction of the systems. Therefore, additional distribution facilities are needed to be planned and prepared for the future growth of the electrical demand as well as the increase of network hosting capacity by DG units. This paper presents a multiobjective optimization algorithm for the MDEP (Multi-Stage Distribution Expansion Planning) in the presence of DGs using nonlinear formulations. The objective functions of the MDEP consist of minimization of costs, END (Energy-Not-Distributed), active power losses and voltage stability index based on SCC (Short Circuit Capacity). A MPSO (modified Particle Swarm Optimization) algorithm is developed and used for this multiobjective MDEP optimization. In the proposed MPSO algorithm, a new mutation method is implemented to improve the global searching ability and restrain the premature convergence to local minima. The effectiveness of the proposed method is tested on a typical 33-bus test system and results are presented. [Copyright &y& Elsevier]