Optimal Placement Of DSTATCOM Research Articles

Enhancing radial distribution system performance by optimal placement of DSTATCOM

In this paper, A novel modified optimization method was used to find 
 the optimal location and size for placing distribution Static Compensator in the radial distribution test feeder in order to improve its performance by minimizing the total power losses of the test feeder, enhancing the voltage profile and reducing the costs. The modified grey wolf optimization algorithm is used for the first time to solve this kind of optimization problem. An objective function was developed to study the radial distribution system included total power loss of the system and costs due to power loss in system. The proposed method is applied to two different test distribution feeders (33 bus and 69 bus test systems) using different Dstatcom sizes and the acquired results were analyzed and compared to other recent optimization methods applied to the same test feeders to ensure the effectiveness of 
 the used method and its superiority over other recent optimization mehods. The major findings from obtained results that the applied technique found 
 the most minimized total power loss in system ,the best improved voltage profile and most reduction in costs due power loss compared to other methods
 .

Optimization of planning cost of radial distribution networks at different loads with the optimal placement of distribution STATCOM using differential evolution algorithm

This paper presents an optimization of planning of distribution systems with the allocation of DSTATCOM based on maximization of a net cost profit/savings analysis approach by using the differential evolution algorithm. In the proposed approach, the optimal placement of DSTATCOM, and reactive power compensation at a certain location, and the improvement of voltage profile are obtained by three objective functions: (1) minimization of the size of DSTATCOM, (2) minimization of network power loss, and (3) maximization of net cost profit/savings by minimizing the total planning cost of DSTATCOM installation scheme. Present worth factor is adopted to evaluate the net cost profit/savings of the DSTATCOM installation scheme for a certain planning horizon. The appropriate mathematical modeling of DSTATCOM is used to incorporate it suitably in the forward–backward sweep load flow algorithm of radial distribution networks to provide the reactive power compensation. The recommended method is validated on the IEEE 30-bus, 33-bus and 69-bus distribution networks.

Optimal Placement of DSTATCOM and DG using Modified SFLA based Technique for Techno-Economic and Environmental Benefits

Optimal Placement of DSTATCOM and DG using Modified SFLA based Technique for Techno-Economic and Environmental Benefits

Optimal placement of DG and DSTATCOM for loss reduction and voltage profile improvement

Due to rapid depletion of fossil fuels availability and huge environmental pollution, focus is now changing from traditional method of power generation to the non-conventional DERs located at distribution voltage level. Technological advancement and more researches in the use of DERs result in the formation of microgrids and active distribution network. Small DER units when placed in a network near to load, makes the network stable as it can work in islanding mode in case of any fault outside the network. This paper proposes a scheme for reduction in losses and improvement of bus voltages in the active distribution network. A DG in the form of small renewable energy resources such as solar PV, wind, biomass, is placed optimally for reduction of losses in the network. However, placement of DG does not result in fulfilment of reactive power needs of the network, resulting in under voltage at several buses. This under voltage problem is solved by the optimal placement of DSTATCOM. DLF technique is used in this paper for load flow calculations and LSF along with voltage deviation is used in objective function for optimal location of DG on MATLAB platform. The methodology is tested on 33-bus radial distribution system.

Optimal Placement of DSTATCOM in Radial Distribution System using Fuzzy and Penguins Search Optimization Algorithm

This paper proposes a hybrid methodology to identify the optimal location and sizing for distribution static compensator (DSTATCOM) placement as a distribution flexible ac transmission system (DFACT) device in a distribution system, by using fuzzy and Penguins search optimization algorithm (PeSOA). The main purpose is to reduce the power loss and to improve the voltage profile of distribution networks. The PeSOA is meta-heauristic search method inspired from the hunting strategy of penguins. Here fuzzy is used for finding the optimal location and PeSOA is used to find the size of DSTATCOM in radial distribution networks. The feasibility and satisfying performance of the proposed method is examined on the IEEE 33-bus and 69-bus distribution system.

Optimal placement of D-STATCOM using hybrid genetic and ant colony algorithm to losses reduction

In this work, a modern algorithm by hybrid genetic algorithm and ant colony algorithm is designed to placement and then simulated to determine the amount of reactive power by D-STATCOM. Also this method will be able to minimize the power system losses that contain power loss in transmission lines. Furthermore, in this design a IEEE 30-bus model depicted and three D-STATCOM are located in this system according to Economic Considerations. The optimal placement of each D-STATCOM is computed by the ant colony algorithm. In order to optimize placement for each D-STATCOM, two groups of ant are selected, which respectively located in near nest and far from the nest. Moreover, for every output simulation of D-STATCOM that is used to produce or absorb of reactive power, a genetic algorithm to minimizing the total network losses is applied. Finally, the result of this simulation shows net losses reduction about 150% that it verifies the new algorithm performance.

Optimal Placement of D-STATCOM Using Hybrid Genetic and Ant Colony Algorithm to Losses Reduction

Optimal Placement of D-STATCOM Using Hybrid Genetic and Ant Colony Algorithm to Losses Reduction