Vladimir N. Tulsky

Optimal shunt capacitors sittings and sizing in radial distribution systems using a novel hybrid optimization algorithm

Optimal placement and size of shunt capacitors in the distribution systems play an important role for improving voltage profile and reducing the system power losses and the cost of reactive power optimization. In this paper, a new effective and powerful optimization algorithm is introduced to solve the locations and sizing problems of capacitor banks in various distribution systems satisfying the operation constraints. A novel hybrid particle swarm (HPSO) with Quasi-Newton (QN) algorithm is proposed for this purpose. First the loss sensitivity analysis with two methods is employed to select the most appropriate candidate capacitor placement. Then a novel hybrid particle swarm optimization (HPSO) algorithm is implemented to find optimal sizing of capacitors and their sittings from the selected buses. The proposed algorithm has been tested on different test systems as 15-bus, and 34-bus IEEE standard radial distribution systems. In order to validate the proposed approach, the obtained results have been compared with other algorithms. In addition, the proposed methodology is applied on practical case study of Moscow region, which consists of 111-bus system. The numerical results have been proved the capability of the proposed approach to find the optimal solutions with system losses reduction, voltage profile improvement and power factor correction. Numerical results have been obtained by MATLAB package.

Optimal sitting and sizing of renewable distributed generations in distribution networks using a hybrid PSOGSA optimization algorithm

Integration of renewable Distributed Generation (DG) such as Photovoltaic (PV) system and wind turbine (WT) in distribution networks can be considered as brilliant and efficient solution to the growing demands. This paper introduces a new robust and effective hybrid PSOGSA optimization algorithm that proposed to detect the optimal location with convenient size of DG units for minimizing system power losses and operating cost besides improving voltage stability. This paper provides two stages. First, the Loss Sensitivity Factors (LSFs) are employed to select the most candidate buses for DG placement. In the second stage, the PSOGSA is implemented to deduce the optimal sitting and sizing of DG from the elected buses. The proposed scheme has been applied on 33-bus and 69-bus IEEE standard radial distribution systems. To insure the suggested approach validity, the evaluated results have been compared with other algorithms such as Genetic Algorithm (GA), Particle Swarm Algorithm (PSO), Novel combined Genetic Algorithm and Particle Swarm Optimization (GA/PSO), Simulation Annealing Algorithm (SA), and Bacterial Foraging Optimization Algorithm (BFOA). The numerical results have been confirmed the superiority with high performance of the proposed technique to find the optimal solutions of DG units allocation. Numerical results have been attained by MATLAB package.

VLCI approach for optimal capacitors allocation in distribution networks based on hybrid PSOGSA optimization algorithm

The use of Shunt Capacitor Banks (SCB) as a convenient compensation source of reactive power in distribution networks has an efficient role in enhancement voltage profile, correction of power factor and minimizing the network power losses. In this regard, this article investigates the enforcement of a modern robust and effective hybridization of Particle Swarm Optimization besides a Gravitational Search Algorithm (PSOGSA) as an optimization mechanism for solving the problem of optimum SCB allocation with minimizing the annual operating cost and enhancement of the system power quality. Moreover, a new Voltage-Loss-Cost Index (VLCI) has been associated with the proposed optimization technique as an efficient objective function to increase the voltage levels, minimize active power losses and the annual operating cost of the grid. Furthermore, the implemented methodology is introduced in two stages. Firstly, the most appropriate buses for locating SCB are estimated using Loss Sensitivity Factor (LSF). Then, the hybrid PSOGSA optimization algorithm is structured to detect the optimum sitings of SCB and their sizing from the elected buses based on VLCI as the main objective function. The suggested mechanism has been applied on 33-bus besides 69-bus IEEE radial distribution networks. In addition, it is applied on a practicality case study of 111-bus Moscow region radial distribution network. With a view to making certain of the validation of the suggested methodology, the acquired results have been compared with other mechanisms and techniques. The numerical results demonstrated that the suggested optimization technique has superiority with high performance to deduce the optimum decision of SCB allocation for minimizing the network power losses, enhancing the profile of voltage level, and maximizing the net savings as compared to other different techniques.

Comprehensive analysis of optimal allocation of capacitor banks in various distribution networks using different hybrid optimization algorithms

Optimal sitting and size of Capacitor Banks (CB) in electric power systems have an important role in upgrading voltage profile, power factor correction and minimizing the cost of reactive power optimization and the system power losses. This work presents two new efficient hybrid optimization algorithms as a comparison to solve the problems of CB allocations. The first PSOQN optimization is implemented with the combination of Particle Swarm Optimization (PSO) and Quazi-Newton (QN) algorithm. In the second PSOGSA optimization algorithm is constructed with the combination of PSO and Gravitational Search Algorithm (GSA). Each one of the proposed methodologies is introduced in two stages. First, the most critical buses for installing CB are estimated using Loss Sensitivity Factors (LSF). Then the optimization algorithm is proposed to deduce the optimal locations of capacitors and their sizing from the chosen buses. The validation of the proposed algorithm is tested on 33-bus, and 69-bus IEEE standard radial distribution systems and Moscow region, with 111-bus as practical case study. In order to validate the proposed methodologies, the obtained results have been compared with other techniques. The results confirmed that the proposed optimization techniques have efficiency and robust with high performance to get the optimal settlings for minimizing the system power losses, enhancing the voltage profile and maximizing the net savings as compared as other techniques. The system results have been implemented by Matlab package.