scholarly journals Planning and Research of Distribution Feeder Automation with Decentralized Power Supply

Electronics ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 362
Author(s):  
Yen-Chih Huang ◽  
Wen-Ching Chang ◽  
Hsuan Hsu ◽  
Cheng-Chien Kuo
Keyword(s):  
Power System ◽  
Power Loss ◽  
Power Grid ◽  
Loss Reduction ◽  
Voltage Profile ◽  
Distributed Energy ◽  
Feeder Automation ◽  
Distributed Generator ◽  
Load Demand ◽  
Power Loss Reduction

The high penetration of distributed generation in distributed energy systems causes the variation of power loss and makes the power grid become more complicated, so this paper takes various types of optimal algorithms into account and simulates the feeder reconfiguration on the IEEE-33 system as well as the Taiwan power system. The simulation verifies linear population size reduction of successful history-based adaptive differential evolution (L-SHADE) and particle swarm optimization (PSO) fitness in different systems and provides the recommended location of distributed energy. The proposed method keeps the voltage bound of 0.95 to 1.03 p.u. of Taiwan regulation. In the IEEE-33 system, we achieved a 52.57% power loss reduction after feeder reconfiguration, and a 70.55% power loss reduction after the distributed generator was implemented and feeder reconfiguration. Under the variation of load demand and power generation of the Taiwan power system, we establish the system models by forecasting one-day load demand. Then, we propose a one-day feeder switch operation strategy by considering the switches’ operation frequency with the reduction of 83.3% manual operation and recommend feeder automation to achieve feeder power loss reduction, voltage profile improvement and get regional power grid resilient configuration.

scholarly journals Self-Adaptive Firefly-Algorithm-Based Unified Power Flow Controller Placement with Single Objectives

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Selvarasu Ranganathan ◽  
S. Rajkumar
Keyword(s):  
Power Loss ◽  
Power Flow ◽  
Unified Power Flow Controller ◽  
Loss Reduction ◽  
Voltage Profile ◽  
Power Loss Reduction ◽  
Voltage Stability Enhancement ◽  
Stability Enhancement ◽  
Power Flow Controller ◽  
Voltage Profile Improvement

The selection of positions for unified power flow controller (UPFC) placement in transmission network is an essential factor, which aids in operating the system in a more reliable and secured manner. This paper focuses on strengthening the power system performance through UPFC placement employing self-adaptive firefly algorithm (SAFA), which selects the best positions along with parameters for UPFC placement. Three single objectives of real power loss reduction, voltage profile improvement, and voltage stability enhancement are considered in this work. IEEE 14, 30, and 57 test systems are selected to accomplish the simulations and to reveal the efficacy of the proposed SAFA approach; besides, solutions are compared with two other algorithms solutions of honey bee algorithm (HBA) and bacterial foraging algorithm (BFA). The proposed SAFA contributes real power loss reduction, voltage profile improvement, and voltage stability enhancement by optimally choosing the placement for UPFC.

scholarly journals Power Loss Reduction in Power System based on PSO: Case Study

2017 ◽  
Vol 164 (10) ◽  
pp. 22-26 ◽  
Author(s):  
Sameer Singh ◽  
Vivek Kumar ◽  
Upendra Prasad
Keyword(s):  
Power System ◽  
Power Loss ◽  
Loss Reduction ◽  
Power Loss Reduction

scholarly journals Recloser-Fuse settings in distribution systems with optimizing multiple distributed generation considering technical aspects

2020 ◽  
Vol 17 (3) ◽  
pp. 1135
Author(s):  
Ahmed Mohamed Abdelbaset ◽  
AboulFotouh A. Mohamed ◽  
Essam Abou El-Zahab ◽  
M. A. Moustafa Hassan
Keyword(s):  
Distributed Generation ◽  
Distribution System ◽  
Power Loss ◽  
Distribution Systems ◽  
Test System ◽  
Optimal Size ◽  
Loss Reduction ◽  
Voltage Profile ◽  
Power Loss Reduction ◽  
System Power

<p><span>With the widespread of using distributed generation, the connection of DGs in the distribution system causes miscoordination between protective devices. This paper introduces the problems associated with recloser fuse miscoordination (RFM) in the presence of single and multiple DG in a radial distribution system. Two Multi objective optimization problems are presented. The first is based on technical impacts to determine the optimal size and location of DG considering system power loss reduction and enhancement the voltage profile with a certain constraints and the second is used for minimizing the operating time of all fuses and recloser with obtaining the optimum settings of fuse recloser coordination characteristics. Whale Optimizer algorithm (WOA) emulated RFM as an optimization problem. The performance of the proposed methodology is applied to the standard IEEE 33 node test system. The results show the robustness of the proposed algorithm for solving the RFM problem with achieving system power loss reduction and voltage profile enhancement.</span></p>

scholarly journals Distribution Network Reconfiguration for Power Loss Reduction and Voltage Profile Improvement Using Chaotic Stochastic Fractal Search Algorithm

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-15 ◽  
Author(s):  
Tung Tran The ◽  
Dieu Vo Ngoc ◽  
Nguyen Tran Anh
Keyword(s):  
Diffusion Process ◽  
Power Loss ◽  
Distribution Systems ◽  
Search Algorithm ◽  
Loss Reduction ◽  
Voltage Profile ◽  
Power Loss Reduction ◽  
Voltage Profile Improvement ◽  
Stochastic Fractal Search Algorithm ◽  
Stochastic Fractal Search

This paper proposes a chaotic stochastic fractal search algorithm (CSFSA) method to solve the reconfiguration problem for minimizing the power loss and improving the voltage profile in distribution systems. The proposed method is a metaheuristic method developed for overcoming the weaknesses of the conventional SFSA with two processes of diffuse and update. In the first process, new points will be created from the initial points by the Gaussian walk. For the second one, SFSA will update better positions for the particles obtained in the diffusion process. In addition, this study has also integrated the chaos theory to improve the SFSA diffusion process as well as increase the rate of convergence and the ability to find the optimal solution. The effectiveness of the proposed CSFSA has been verified on the 33-bus, 84-bus, 119-bus, and 136-bus distribution systems. The obtained results from the test cases by CSFSA have been verified to those from other natural methods in the literature. The result comparison has indicated that the proposed method is more effective than many other methods for the test systems in terms of power loss reduction and voltage profile improvement. Therefore, the proposed CSFSA can be a very promising potential method for solving the reconfiguration problem in distribution systems.

Investigating the Impact of Distributed Generators Power Factor to Simultaneous Optimization Analysis

2015 ◽  
Vol 785 ◽  
pp. 253-257
Author(s):  
Jasrul Jamani Jamian ◽  
M.W. Mustafa ◽  
Mohd Noor Abdullah
Keyword(s):  
Power Factor ◽  
Power Loss ◽  
Simultaneous Optimization ◽  
Loss Reduction ◽  
Optimization Analysis ◽  
Swarm Optimization ◽  
Distributed Generator ◽  
Distributed Generators ◽  
Power Loss Reduction ◽  
The Impact

This paper discusses the optimal Distributed Generator (DG) coordination using the Particle Swarm Optimization (PSO) technique where the DG output and location are determined simultaneously. Furthermore, this study analyzes both single DG and multiple DGs configurations. The influence of DG Power Factor (PF) to the optimal DG placement and the DG output are investigated by varying the DG PF values. Specifically, the PF were configured to five values, which are 0.8, 0.85, 0.9, 0.95 and 1.0. From the results, the optimal DG placements are similar, regardless of the PF condition. For example, in the single DG unit experiment, the optimal DG location is at bus 6 whilst in the triple DG units test, the optimal locations are at busses 14, 24, and 30. In contrast, the value of PF significantly influences the optimal DG output and power loss reduction. This study concludes that the design with three DGs where their PFs are configured to 0.8 has the least power loss.

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