Allocation Of Distributed Generation Units Research Articles

Impact of Distributed Generation on the Effectiveness of Electric Distribution System Reconfiguration

Distribution system reconfiguration (DSR) is an essential activity in the operation of distribution utilities, usually carried out to lower active power losses and improve reliability metrics. The insertion of distributed generation (DG) units in electric power distribution systems (EPDS) causes the rearrangement of power flows through the conductors and changes the real power losses and voltage profile; therefore, up to a certain point, the insertion of certain quantities of DG may potentially delay or change the reconfiguration strategy of EPDS. This article presents an analysis of the impact of DG, for different locations of the units and different levels of active power supplied by them, on real power losses and on the effectiveness of DSR. The article presents tests with different distribution systems with varying sizes and topologies, showing that the allocation of DG units in buses far from the substation provided the best cost–benefit results. The DSR impact changes depending on the installment location and the generation level of the DG units, corroborating that DSR must be considered and performed using certain criteria, to maximize its efficiency.

Strategic incorporation of DSTATCOM and distributed generations in balanced and unbalanced radial power distribution networks considering time varying loads

The article focuses on the optimal planning of distribution static synchronous compensator (DSTATCOM) and distributed generation (DG) to minimize power losses, and simultaneously enhance the voltage profile, and voltage stability at various nodes of the Radial Power Distribution Networks (RPDN). The study involves combinational choices in the use of the DSTATCOM and DG and it relies on heuristic algorithms namely the Enhanced artificial bee colony algorithm (EABC) which has been formulated based on a modification in the searching strategy of the traditional artificial bee colony algorithm (ABC) by integrating the particle swarm optimization (PSO). The proposed optimization model considers the multiobjective function, including the power loss reduction, branch current capacity limit violation, and node voltage deviation. In the proposed approach, the optimal rating of DG and DSTATCOM is estimated under various load steps by using the EABC algorithm. Two different test cases namely base case, and combined installation of DG and DSTATCOM units were considered to analyze the distribution network performance at different load factors. The power loss minimization, voltage profile, and voltage stability improvement of the network before and after the allocation of DG unit and DSTATCOM is depicted. The study examines the effectiveness of the proposed method through a simulation run on 33-node balanced and IEEE 13-node unbalanced RPDN under time varying load demand. Simulation results reveal that the combined installation of DG unit along with DSTATCOM at a suitable location in 33-node and 13-node distribution networks can minimize the power loss by 62% and 43% respectively under the time varying load demand considered along with significant improvement in voltage profile and voltage stability of the network.

Optimal sizing of distributed generation units and shunt capacitors in the distribution system considering uncertainty resources by the modified evolutionary algorithm

Distributed generation units (DGUs) as auxiliary sources of power generation can play an effective role in meeting the load consumption of the distribution network, also have positive effects such as reducing loss and improving voltage. Moreover, capacitors by reactive power compensation produce positive effects similar to DGUs in the distribution networks. The idea of joint operation of DGUs and shunt capacitors (SCs) in the presence of demand response program (DRP) to derive maximum benefits from their installation is proposed in this paper. The time of use (TOU) mechanism is used as one of the demand response programs (DRPs) to alter the consumption pattern of subscribers and improve the performance of the distribution system. Objective functions include minimization of energy loss, operational cost, and energy not supplied (ENS). In general, the problem of determining the optimal capacity of DGUs and SCs is complex due to the demand variation. Also, considering the effect of uncertainty sources complicate the optimization problem. Hence, a modified shuffled frog leaping algorithm (MSFLA) is proposed to overcome the complexities of this problem. The proposed approach is tested on two 95, and 136-node test networks, and the results are compared with other evolutionary algorithms. According to the obtained results, after using the proposed approach in determining the optimal capacity of DGUs and SCs in the first system, the amount of energy loss, operational cost and ENS dropped by 11, 25.5 and 5% compared to baseline values. After applying the TOU mechanism in allocation of DGUs and SCs simultaneously in the second system by proposed method, the values obtained for the mentioned objectives reduced by 29, 65 and 7% compared to initial values.

Optimal Allocation of Distributed Generation With Optimal Sizing of Fault Current Limiter to Reduce the Impact on Distribution Networks Using NSGA-II

Nowadays, the presence of distributed generation (DG) units in the distribution network is increasing due to their advantages. As well as these advantages, there are some problems, such as increasing the level of short circuits in buses and disturbing the protection operation of the network. The main objective of this paper is optimal using of fault current limiters (FCLs) in series with DG units to reduce the negative impacts of the DG units. The method of simultaneously determining the optimal location and size of DGs and the optimal size of FCLs is proposed in this paper. By appropriate allocation of DG units in the distribution network, a considerable reduction in the size of fault current limiters can be achieved. The locations of DG units are considered to be discrete variables and the sizes of FCLs and DGs to be continuous variables, and a nondominated sorting genetic algorithm (NSGA-II) is used to reduce losses and optimize the sizes of fault current limiters. The proposed method is implemented on two test networks and the results demonstrate the efficiency of the method.

Optimal Power Flow Using the Jaya Algorithm

This paper presents application of a new effective metaheuristic optimization method namely, the Jaya algorithm to deal with different optimum power flow (OPF) problems. Unlike other population-based optimization methods, no algorithm-particular controlling parameters are required for this algorithm. In this work, three goal functions are considered for the OPF solution: generation cost minimization, real power loss reduction, and voltage stability improvement. In addition, the effect of distributed generation (DG) is incorporated into the OPF problem using a modified formulation. For best allocation of DG unit(s), a sensitivity-based procedure is introduced. Simulations are carried out on the modified IEEE 30-bus and IEEE 118-bus networks to determine the effectiveness of the Jaya algorithm. The single objective optimization cases are performed both with and without DG. For all considered cases, results demonstrate that Jaya algorithm can produce an optimum solution with rapid convergence. Statistical analysis is also carried out to check the reliability of the Jaya algorithm. The optimal solution obtained by the Jaya algorithm is compared with different stochastic algorithms, and demonstrably outperforms them in terms of solution optimality and solution feasibility, proving its effectiveness and potential. Notably, optimal placement of DGs results in even better solutions.

A simple and fast approach for allocation and size evaluation of distributed generation

Penetration of distributed generation (DG) units in distribution network has increased rapidly stimulated by reduced network power loss, improved bus voltage profile, and better power quality. Appropriate size and allocation of DG units play a significant role to get beneficial effects. The objective of this study is to demonstrate a simple and fast technique to determine appropriate location and size of DG units. A voltage stability indicator (VSI) is derived which can quantify the voltage stability conditions of buses in distribution network. According to VSI, vulnerable buses of the network are arranged rank-wise to form a priority list for allocation of DG units. To determine the size of DG units, a feed forward artificial neural network is prepared in MATLAB environment (The MathWorks, Inc., Massachusetts, USA). The effectiveness of the proposed methodology has been tested on a 52-bus radial distribution network. After appropriate allocation of DG units, voltage profiles of most of the buses are increased significantly. The results also indicated that the total loss of the distribution network has reduced by nearly 76.39%, and voltage stability conditions of buses are improved considerably. Voltage stability conditions of bus-13, bus-36, and bus-44 are raised by 23.16%, 29.23%, and 37.64% respectively.