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With increasing annual energy demand and significant growth in the use of distributed generation (DG), distribution companies are exploring ways to improve the technical specifications of the distribution networks such as power losses, customer interruption costs, and voltage stability and on the other hand to increase the penetration level of DGs. In this paper, a multi-objective optimization model is proposed for distribution network reconfiguration (DNR) to decrease the total costs of energy losses and energy not supplied (ENS) and increase the voltage stability and DG penetration level. Seasonal hourly load curves are applied, and best configuration is determined for each loading condition. Uncertainties regarding the load variations and volatile power production of wind turbine are modeled using a 2-point estimate method, and a benefit-cost analysis is used to assess the effects of depreciation cost in DNR problem. The proposed model is applied on 2 typical test systems. [ABSTRACT FROM AUTHOR]

Summary: This paper presents a multiobjective method for obtaining optimal size and site of distributed generation (DG), to reduce loss, and DG investment cost while improving the voltage profile in primary distribution networks. To solve the multiobjective problem, a classical technique known as global criterion method is implemented to form a novel objective function equation, which is custom‐built for a distribution system. The application of the global criterion method is explained using a DG that is capable of injecting real power, ie, unity power factor DG, and then extended to DGs capable of injecting reactive power. The method is validated for 2 distribution systems. Results show that the proposed method satisfies the individual objectives simultaneously. The proposed method is also compared with existing methods to exhibit its effectiveness. [ABSTRACT FROM AUTHOR]

This paper presents an application of the chaotic artificial bee colony (CABC) algorithm to identify the optimal location and sizing of the distributed generation (DG) units in order to improve the voltage stability margin in the radial distribution system. Artificial bee colony algorithm is an optimization algorithm based on the intelligent foraging behavior of honey bee swarm. To improve the searching ability of an artificial bee colony algorithm, chaos theory is united with artificial bee colony, called the CABC algorithm. The various impact indices are used to evaluate the multi-objective performance index aimed to identify the optimal location and sizing of combined real and reactive power-based DGs on the distribution systems. The presence of DG in the distribution system has been potential to improve voltage stability of the system. The effect of DG on the weakest bus is analyzed by constructing the PV curve. The effectiveness of the proposed method is tested on 38-node and 69-node radial distribution systems. [ABSTRACT FROM AUTHOR]

This paper proposes an approach to evaluate the effects of renewable and non-renewable distributed generations (DGs) on distribution network expansion planning from the reliability, uncertainty, and operational viewpoints. This methodology aims to determine the optimal capacity reinforcement of distribution network to meet the load growth in the planning horizon subject to the technical and operational constraints in the presence of utility-owned DG units. The capacity reinforcement includes determining 'the expanded capacity of existing medium voltage (MV) lines as well as high voltage/medium voltage (HV/MV) substations', 'the capacity of new MV lines (feeders) and HV/MV substations', and 'the site, capacity and generation schedule of DGs'. To precisely calculate the operational and interruption costs, the variation of load is regarded using the annual load duration curve. Also, the uncertainty of the load, energy price, and the power generated by renewable DGs have been considered. The possibility of islanding and also the load transferring through the reserve feeders have been regarded in the problem to improve the reliability of network. The proposed approach has been formulated as an optimization problem where a hybrid genetic algorithm and optimal power flow is employed to solve it. Finally, the proposed method is applied to the 54-bus test system in different scenarios and the results are discussed. The simulation results show the effectiveness of the presented method. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Distributed generation (DG) sources have recently become more significant in the distribution system due to the increasing demand of electricity energy. Choosing the most suitable size of DG is an essential step to ensure tremendous effect on its operation and power system control. An optimal DG size will result in the reduction of electrical power loss as well as the cost of operation. Power loss reduction can also be achieved through optimal network reconfiguration. By considering optimal network reconfiguration and DG sizing, the effectiveness and efficiency of the system can be improved while having lower power loss in the power system. Therefore, this paper presents the simultaneous method to identify the optimal network reconfiguration and DG sizing using evolutionary programming. The main goal of this work was to reduce the power loss and increase the voltage profile, while at the same time fulfill the operating constraints. The developed method was tested on 33-bus and 69-bus system with different operating conditions. The test results showed a great improvement of power loss reduction and overall voltage profile of the system. The implementation of reconfiguration and DG technique in 33-bus and 69-bus systems which were operated simultaneously had shown tremendous improvement in terms of the number of iterations to reach the optimal value of power losses and DG sizing. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

It is expected that the use of distributed generation (DG) will increase sharply in distribution systems, especially with the realization of smart grids. In spite of the benefits of DG in distribution systems, high penetration level of DGs could cause some challenges for the network. Therefore, the optimal sizing and siting of DGs should be identified carefully. In addition, different operating conditions have to be taken into account in this process. The DGs are usually installed depending on optimal siting and sizing techniques considering normal operating periods. During repairing fault periods, different locations and capacities of DGs may be preferable. In this paper, 2 scenarios of switching strategies are presented for attaining the optimal sizing and siting of DGs during repairing fault period starting from the optimal allocation obtained for normal operating period. Genetic algorithm is used for solving the optimization problem that is implemented for an actual loop distribution system in Egypt. [ABSTRACT FROM AUTHOR]