A survey on enhancement of power system performances by optimally placed DG in distribution networks

Singh, Bindeshwar; Mishra, Deependra Kumar

doi:10.1016/j.egyr.2018.01.004

Cited by 32 publications

(8 citation statements)

References 303 publications

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“…DER integration into distribution systems is complex and requires in-depth assessment and efficient operational and planning tools. This is mainly because DERs are not dispatchable by distribution system operators and can have a large impact on losses, power flow, voltage stability and power quality [90], [91]. Numerous algorithms have been employed for DER optimal allocation, resulting in the best location and size of DERs considering loss reduction [92].…”

Section: B Der Managementmentioning

confidence: 99%

Overview of Loss Sensitivity Analysis in Modern Distribution Systems

Abujubbeh

Natarajan

2022

IEEE Access

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Section: B Der Managementmentioning

confidence: 99%

Overview of Loss Sensitivity Analysis in Modern Distribution Systems

Abujubbeh

Natarajan

2022

IEEE Access

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“…Several research works have used PSO in combination with other techniques to gain more precise and accurate results. Hybrid GA-PSO [41], PSO and Linearized AC load flow [39], PSO-Compromise Programming [42], fuzzy approach and PSO [43] and discrete PSO-OPF [44] are some of the hybrid approaches. More comprehensive reviews on the DGs optimization problem can be observed in [45,46], where different algorithms and methods have been discussed.…”

Section: Related Workmentioning

confidence: 99%

SPSO Based Optimal Integration of DGs in Local Distribution Systems under Extreme Load Growth for Smart Cities

et al. 2021

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Renewable energy-based distributed generators (DGs) are gaining more penetration in modern grids to meet the growing demand for electrical energy. The anticipated techno-economic benefits of these eco-friendly resources require their judicious and properly sized allocation in distribution networks (DNs). The preeminent objective of this research is to determine the sizing and optimal placing of DGs in the condensed DN of a smart city. The placing and sizing problem is modeled as an optimization problem to reduce the distribution loss without violating the technical constraints. The formulated model is solved for a radial distribution system with a non-uniformly distributed load utilizing the selective particle swarm optimization (SPSO) algorithm. The intended technique decreases the power loss and perfects the voltage profile at the system’s nodes. MATLAB is used for the simulation, and the obtained results are also validated by the Electrical Transient Analysis Program (ETAP). Results show that placing optimally sized DGs at optimal system nodes offers a considerable decline in power loss with an improved voltage profile at the network’s nodes. Distribution system operators can utilize the proposed technique to realize the reliable operation of overloaded urban networks.

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“…The Voltage constancy in the broadcasting or in the distributed network can also be considered by having a support of fixed load boundary which is generally a supplementary loading that scheme could endure above and beyond the base case load former to the collapse argument. Load ability is proportionate to the fixed loading boundary of the method and it could be contingent on load and peers commands [18], [19]. Amongst numerous practices to solve power flow equations, Newton-Raphson is an effective method when there is large size of bus system.…”

Section: Voltage Stabilitymentioning

confidence: 99%

Multiple DG Placement in Radial Bus System using Weight Adaptive Swarm Intelligence to Improve Voltage Profile

2019

IJITEE

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Methods found in the literature are regularly not capable of concurrently examine financial and technical oriented benefits for multi-location DG placement systems. Therefore an effective system is presented to such benefits as for multiple DG placements. Particle Swarm Optimization (PSO) is extensively used to optimize dimensional data in number of applications due to its fast searching and converging property to optimal solution and hence used in finding optimal location for multi DG placement. It is tested on 33 IEEE bus systems in which three initial locations are selected on random basis for DG placement and power flow analysis is done to evaluate electricity losses and voltage profile at all buses. Then PSO is used to find the optimal locations which give high values of voltage profile then initial configuration and proposed three best effective, beneficial locations where there are minimum electricity losses and high voltage profile indices. For speedy convergence of the algorithm adaptive weight parameter is used instead of fixed weight. Experimental results have been carried out for IEEE 33 radial bus in which type-1 DG placement is considered. With optimized locations, new switch-ties gives 70.4 % less power loss than the initial tied switches.

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A survey on enhancement of power system performances by optimally placed DG in distribution networks

Cited by 32 publications

References 303 publications

Overview of Loss Sensitivity Analysis in Modern Distribution Systems

Overview of Loss Sensitivity Analysis in Modern Distribution Systems

SPSO Based Optimal Integration of DGs in Local Distribution Systems under Extreme Load Growth for Smart Cities

Multiple DG Placement in Radial Bus System using Weight Adaptive Swarm Intelligence to Improve Voltage Profile

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