Optimal placement and sizing of DG in distribution network is an optimization problem with continuous and discrete variables. Many researchers have used evolutionary methods for finding the optimal DG placement. This paper proposes a shuffled frog leaping algorithm (SFLA) for optimal placement and sizing of distributed generation (DG) in radial distribution system to minimize the total real power loss and to improve the voltage profile. The SFLA is a meta-heuristic search method inspired from the memetic evolution of a group of frogs when seeking for food. It consists of a frog leaping rule for local search and a memetic shuffling rule for global information exchange. The proposed SFL algorithm is used to determine optimal sizes and locations of multi-DGs. Test results indicate that SFLA method can obtain better results than the simple heuristic search method on the 33-bus radial distribution systems. Moreover, voltage profile improvement and branch current reduction are obtained.

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SUMMARYSince large power transformers belong to the most valuable assets in electrical power networks, it is suitable to pay higher attention to these operating resources. Thermal impact leads not only to long-term oil/paper-insulation degradation; it is also a limiting factor for the transformer operation. Therefore, the knowledge of the temperature, especially the hot-spot temperature (HST), is of high interest. The calculation of current thermal stress helps to avoid unexpected outages. This paper presents the temperature distribution in windings of the oil power transformers. In this paper, energy (thermal) equation is solved until temperature is obtained. Oil in the transformer is assumed nearly incompressible and oil parameters such as thermal conductivity, special heat, viscosity, and density vary with temperature. For numerical solution of above equation, finite element method is used. The selected models for simulation are 300 KVA and 22.5 MVA ONAN transformers.

Optimal placement and sizing of DG in distribution network is an optimization problem with continuous and discrete variables. Many researchers have used evolutionary methods for finding the optimal DG p lacement and sizing. This paper proposes a hybrid algorith m PSO&HBMO for optimal placement and sizing of distributed generation (DG) in radial d istribution system to minimize the total power loss and improve the voltage profile. The proposed method is tested on a standard 13 bus radial distribution system and simulat ion results carried out using MATLAB software. The simulation results indicate that PSO&HBM O method can obtain better results than the simp le heuristic search method and PSO algorithm. The method has a potential to be a tool for identifying the best location and rating of a DG to be installed for improving voltage profile and line losses reduction in an electrical power system. Moreover, current reduction is obtained in distribution system.

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