An Analytical Approach to Find Optimal Location and Sizing of DGs for Power Loss Reduction and Voltage Stability Improvement

2016 ◽  
Vol 4 (4) ◽  
pp. 189-193
Author(s):  
Jyotsna Singh ◽  
◽  
Saurabh Ratra ◽  
Rajive Tiwari ◽  
K. R. Niazi
Keyword(s):  
Power Loss ◽  
Analytical Approach ◽  
Voltage Stability ◽  
Optimal Location ◽  
Loss Reduction ◽  
Power Loss Reduction

Real Power Loss Reduction by Billfish and Red Mullet Optimization Algorithms

2021 ◽  
Author(s):  
Lenin Kanagasabai
Keyword(s):  
Power Loss ◽  
Voltage Stability ◽  
Reactive Power ◽  
Smart Cities ◽  
Fitness Function ◽  
Loss Reduction ◽  
Real Power ◽  
Red Mullet ◽  
Power Loss Reduction ◽  
Continuous Power

In this paper Billfish Optimization Algorithm (BOA) and Red Mullet Optimization (RMO) Algorithm has been designed for voltage stability enhancement and power loss reduction. Electrical Power is one among vital need in the society and also it plays lead role in formation of smart cities. Continuous power supply is essential and mainly quality of the power should be maintained in good mode. In this work real power loss reduction is key objective. Natural hunting actions of Billfish over pilchards are utilized to model the algorithm. Candidate solutions in the projected algorithm are Billfish and population in the exploration space is arbitrarily engendered. Movement of Billfish is high, it will attack the pilchards vigorously and it can’t escape from the attack done by the group of Billfish. Then in this paper Red Mullet Optimization (RMO) Algorithm is proposed to solve optimal reactive power problem. Projected RMO algorithm modeled based on the behavior and characteristics of red mullet. As a group they hunt for the prey and in each group there will be chaser and blocker. When the prey approaches any one of the blocker red mullet then automatically it will turn as new chaser. So roles will interchangeable and very much flexible. At any time chaser will become blocker and any of the blocker will become a chaser with respect to prey position and conditions. Then in that particular area when all the preys are hunted completed then red mullet group will change the area. So there will be flexibility and changing the role quickly with respect to prey position. Alike to that with reference to the fitness function the particle will be chosen as chaser. By means of considering L (voltage stability) - index BOA, and RMO algorithms verified in IEEE 30- bus system. Then without L-index BOA and RMO algorithms is appraised in 30 bus test systems. Both BOA and RMO algorithms condensed the power loss proficiently with improvement in voltage stability and minimization of voltage deviation.

scholarly journals ACTIVE POWER LOSS REDUCTION AND IMPROVEMENT OF STATIC VOLTAGE STABILITY MARGIN INDEX BY WATERWAY ALGORITHM

SINERGI ◽  
2018 ◽  
Vol 22 (3) ◽  
pp. 155
Author(s):  
Kanagasabai Lenin
Keyword(s):  
Power Loss ◽  
Voltage Stability ◽  
Stability Margin ◽  
Natural World ◽  
Active Power ◽  
Superior Performance ◽  
Loss Reduction ◽  
Static Voltage Stability ◽  
Voltage Stability Margin ◽  
Power Loss Reduction

In this paper, the Waterway Algorithm (WA) is used for Active Power Loss Reduction and improvement of Static Voltage Stability Margin Index. The design of the Waterway Algorithm (WA) is imitated from nature and the whole waterway process which involves the flow of streams and rivers into the sea in the natural world. The proposed Waterway Algorithm (WA) algorithm has been tested on standard IEEE 30 bus test system and simulation results show clearly about the superior performance of the proposed algorithm in reducing the real power loss and upgrading the Static Voltage Stability Margin Index.

scholarly journals Optimal Location and Size of Distributed Generators in an Electric Distribution System based on a Novel Metaheuristic Algorithm

2020 ◽  
Vol 10 (1) ◽  
pp. 5325-5329 ◽  
Author(s):  
T. N. Ton ◽  
T. T. Nguyen ◽  
A. V. Truong ◽  
T. P. Vu
Keyword(s):  
Distribution System ◽  
Power Loss ◽  
Optimal Location ◽  
Metaheuristic Algorithm ◽  
Loss Reduction ◽  
Control Parameters ◽  
Electric Distribution System ◽  
Distributed Generators ◽  
Power Loss Reduction ◽  
Electric Distribution

This paper proposes a method for optimizing the location and size of Distributed Generators (DGs) based on the Coyote Algorithm (COA), in order to minimize the power loss in an Electric Distribution System (EDS). Compared to other algorithms, COA does not need control parameters during its execution. The effectiveness of COA was evaluated in an EDS with 33 nodes for two scenarios: the optimization of location and capacity of DGs in an initial radial configuration, and the best radial configuration for power loss reduction. Results were compared with other methods, showing that the proposed COA is a reliable tool for optimizing the location and size of DGs in an EDS.

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