GA for enhancement of system performance by DG incorporated with D-STATCOM in distribution power networks

Singh, Bindeshwar; Yadav, Manish Kumar

doi:10.1016/j.jesit.2018.02.005

Cited by 21 publications

(14 citation statements)

References 17 publications

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“…An up to date survey of literature on optimal allocation of D-STATCOM in distribution networks presented in [9]. Now-a-days, evolutionary based algorithms such as Modified Shuffled Frog Leaping Algorithm (MSFLA) [10], Ant Colony Optimization (ACO) [11], Genetic Algorithm (GA) [12], Particle Swarm Optimization (PSO) [13], Hybrid Particle Swarm Optimization (HPSO) [14], Grey wolf optimizer [15] are used to minimize the objective function to achieve the optimal place and size of DGs and D-STATCOMs radial distribution systems (RDSs).…”

Section: Introductionmentioning

confidence: 99%

Optimal location and sizing of DG and D-STATCOM in distribution networks

Salkuti

2019

IJEECS

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<p>The main aim of this paper is to determine optimal locations and sizing of Distributed Generations (DGs) and Distribution STATic COMpensator (D-STATCOM) in the distribution network for reducing the system losses and to improve the voltage profile. In this paper, the loss sensitivity factor approach is used to determine optimal location for DG and voltage stability index is used to determine optimal location for D-STATCOM. The objective of proposed optimization problem is to minimize the total real power losses in the system while satisfying several equality and inequality constraints. Artificial fish swarm optimization algorithm (AFSOA) is used to determine the optimal size of DG and D-STATCOM. The simulations are performed on standard 33 bus and 69 bus radial distribution systems and the obtained results show the feasibility and effectiveness of proposed approach.</p>

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Section: Introductionmentioning

confidence: 99%

Optimal location and sizing of DG and D-STATCOM in distribution networks

Salkuti

2019

IJEECS

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“…The total output voltage is the sum of the output voltages of the individual H-bridge modules. Connection to the traction network is made through smoothing current filters [5][6][7]. The reactive power generated by STATCOM is determined from the following formula, kvar:…”

Section: Introductionmentioning

confidence: 99%

Method for improving performance of devices for adjustable reactive power compensation

Cheremisin

Nikonov

2019

E3S Web Conf.

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The article presents a method for selecting the parameters of the current-voltage characteristics of adjustable reactive power compensation devices used at sectioning stations of railway sections electrified by alternating current with a voltage of 27.5 kV. This technique is based on the experience of operating two types of devices in the traction power supply system. Power control of these devices is implemented by the voltage level at the switching point. Selection of the setpoint voltage and slope characteristics was done. The developed method allows increasing the efficiency of devices by eliminating the voltage losses on the active component of traction loads. That will reduce the loss of electricity in the system of traction power supply. Changing the parameters of the characteristics will increase the relationship between the reactive power consumed in the zone and the voltage measured by the devices. Following the results of the formation of the methodology, an example of the choice of characteristics for a real compensation device is presented.

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“…Voltage regulation of real time that existed in Saudi Arabia distribution network using 16‐MVAr STATCOM is addressed in Alabduljabbar et al Dynamic reactive power compensation provided with D‐STATCOM in 44‐kV weak industrial distribution systems to maintain acceptable voltage profiles and prevent process shutdowns. Various optimization and sensitivity based techniques were used by many authors to determine optimal location and rating of D‐STATCOM in radial distribution systems to minimize power losses. Few researchers have studied this D‐STATCOM placement problem along with DG placement and reconfiguration of radial distribution systems …”

Section: Introductionmentioning

confidence: 99%

“…Thereafter, rating of DG was determined by analytical method and D‐STATCOM size was determined by direct search algorithm. Analysis of distribution system with D‐STATCOM and DG was presented in Singh and Yada to minimize total power loss for different load models. Optimal size and locations were obtained by using GA.…”

Section: Introductionmentioning

confidence: 99%

Impact of D-STATCOM in distribution systems with load growth on stability margin enhancement and energy savings using PSO and GAMS

Murty

Kumar

2018

Int Trans Electr Energ Syst

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Summary Optimal reactive power deployment as per the statutory provisions of Indian Electricity Grid Codes is essential for better operation of the system. In this paper, a multiobjective optimization problem is solved for sizing and siting of the reactive compensation device. The proposed scheme comprises combination of particle swarm optimization and General Algebraic Modeling System to obtain location and rating of Distribution Static Synchronous Compensator (D‐STATCOM). The main highlights of the proposed work are (i) optimal sizing and siting of D‐STATCOM under load growth and load variations scenario; (ii) voltage stability margin enhancement with D‐STATCOM in a stressed distribution system with load variations and growth; (iii) impact of single and multiple D‐STATCOM units on the losses, voltage profile, and voltage stability margin improvement; and (iv) cost of energy loss savings and annual energy savings. The proposed method is tested on 33‐bus, 69‐bus, and 30‐bus real‐time distribution system of the East Delta Network of the Unified Egyptian network. Benefits to distribution network operator are assessed in reduction in cost of energy loss, annual cost savings, and enhanced voltage stability margin. The results are compared with other methods reported in literature to verify the competency of the proposed multiobjective optimization problem using particle swarm optimization and General Algebraic Modeling System. Annual cost savings of $27 776.97 and $33 297.17 are obtained with proposed technique for 33‐bus and 69‐bus, respectively, which is higher than existing methods. After installation of D‐STATCOM, voltage stability margin enhanced from 0.6956 to 0.75845 for 33‐bus RDS, from 0.68339 to 0.74555 for 69‐bus RDS, and from 0.80223 to 0.83001 for 30‐bus RDS.

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GA for enhancement of system performance by DG incorporated with D-STATCOM in distribution power networks

Cited by 21 publications

References 17 publications

Optimal location and sizing of DG and D-STATCOM in distribution networks

Optimal location and sizing of DG and D-STATCOM in distribution networks

Method for improving performance of devices for adjustable reactive power compensation

Impact of D-STATCOM in distribution systems with load growth on stability margin enhancement and energy savings using PSO and GAMS

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