scholarly journals ENRICHED BLACK HOLE ALGORITHM FOR DIMINUTION OF REAL POWER LOSS

2017 ◽  
Vol 5 (9) ◽  
pp. 186-194
Author(s):  
K. Lenin
Keyword(s):  
Black Hole ◽  
Power Loss ◽  
Power Flow ◽  
Reactive Power ◽  
Solution Space ◽  
Real Power ◽  
Large Size ◽  
Candidate Solution ◽  
Reactive Power Flow ◽  
Black Hole Algorithm

This paper presents an Enriched Black Hole (EBH) algorithm for solving reactive power flow problem. The Black Hole Algorithm starts with a preliminary population of contestant  and for all iteration of the black hole algorithm, the most excellent candidate is favored to be the black hole, which followed by  pulling further candidates around it, called stars. If a star move very close to the black hole, it will be consumed by the black hole and is vanished undyingly. In such a case, a new star - candidate solution is arbitrarily created and placed in the exploration space and starts a new search. Black hole algorithm is feeble to carry out global search completely in the large size problem spaces.  So the enhancement in the amalgamation process in black hole algorithm has to be done. In this work, black hole algorithm will be enhanced, using stars gravities information. For this aim, a kind of gravitational force between stars is defined and the movement of stars to the black hole is adjusted during the penetration of solution space. In order to evaluate the projected Enriched Black Hole (EBH) algorithm, it has been tested in Standard IEEE 57,118 bus systems and compared to other standard reported algorithms. Simulation results reveal about the Enriched performance of the projected algorithm in plummeting the real power loss.

scholarly journals Minimization of real power loss by enhanced teaching learning based optimization algorithm

2020 ◽  
Vol 9 (1) ◽  
pp. 1
Author(s):  
K. Lenin
Keyword(s):  
Power Loss ◽  
Power Flow ◽  
Reactive Power ◽  
Optimization Problems ◽  
High Concentration ◽  
Real Power ◽  
Reactive Power Flow ◽  
Tlbo Algorithm ◽  
Teaching Learning Based Optimization ◽  
Teaching Learning

<p class="Abstract">This paper presents an Enhanced Teaching-Learning-Based Optimization (ETLBO) algorithm for solving reactive power flow problem. Basic Teaching-Learning-Based Optimization (TLBO) is reliable, accurate and vigorous for solving the optimization problems. Also it has been found that TLBO algorithm slow in convergence due to its high concentration in the accuracy. This paper presents an, enhanced version of TLBO algorithm, called as enhanced Teaching-Learning-Based Optimization (ETLBO). A parameter called as “weight” has been included in the fundamental TLBO equations &amp; subsequently it increases the rate of convergence. In order to evaluate the proposed algorithm, it has been tested in Standard IEEE 57,118 bus systems and compared to other standard reported algorithms. Simulation results reveal about the better performance of the proposed algorithm in reducing the real power loss &amp; voltage profiles are within the limits.</p><p> </p>

scholarly journals Interphase Power Flow Control via Single-Phase Elements in Distribution Systems

2021 ◽  
Vol 3 (1) ◽  
pp. 37-58
Author(s):  
Piyapath Siratarnsophon ◽  
Vinicius C. Cunha ◽  
Nicholas G. Barry ◽  
Surya Santoso
Keyword(s):  
Power Consumption ◽  
Power Systems ◽  
Power Flow ◽  
Distribution Systems ◽  
Single Phase ◽  
Reactive Power ◽  
Active Power ◽  
Real Power ◽  
Power Flow Control ◽  
Reactive Power Flow

The capability of routing power from one phase to another, interphase power flow (IPPF) control, has the potential to improve power systems efficiency, stability, and operation. To date, existing works on IPPF control focus on unbalanced compensation using three-phase devices. An IPPF model is proposed for capturing the general power flow caused by single-phase elements. The model reveals that the presence of a power quantity in line-to-line single-phase elements causes an IPPF of the opposite quantity; line-to-line reactive power consumption causes real power flow from leading to lagging phase while real power consumption causes reactive power flow from lagging to leading phase. Based on the model, the IPPF control is proposed for line-to-line single-phase power electronic interfaces and static var compensators (SVCs). In addition, the control is also applicable for the line-to-neutral single-phase elements connected at the wye side of delta-wye transformers. Two simulations on a multimicrogrid system and a utility feeder are provided for verification and demonstration. The application of IPPF control allows single-phase elements to route active power between phases, improving system operation and flexibility. A simple IPPF control for active power balancing at the feeder head shows reductions in both voltage unbalances and system losses.

scholarly journals Minimizing Power Loss Using Modified Artificial Bee Colony Algorithm

2021 ◽  
Vol 6 (2) ◽  
pp. 111-118
Author(s):  
Nur Azlin Ashiqin Mohd Amin ◽  
Siti Hafawati Jamaluddin ◽  
Nur Syuhada Muhammat Pazil ◽  
Norwaziah Mahmud ◽  
Norhanisa Kimpol
Keyword(s):  
Power System ◽  
Power Loss ◽  
Power Flow ◽  
Artificial Bee Colony ◽  
Reactive Power ◽  
Control Variable ◽  
Test System ◽  
Abc Algorithm ◽  
Bee Colony ◽  
Reactive Power Flow

Electrical energy losses are found in any part of the power system. In the power system, it is essential to minimize the real power loss in transmission lines. The voltage deviation at the load buses through controlling the reactive power flow is very important. This ensures the secured operation of power systems regarding voltage stability and the economics of the process due to loss minimization. In this paper, the Modified Artificial Bee Colony (MABC) algorithm is implemented to solve the power system's optimal reactive power flow problem. Generator bus voltages, transformer tap positions, and settings of switched shunt of compensators are used as decision variables to control the reactive power flow. These control variable values are adjusted for loss reduction. MABC algorithm is tested on the standard IEEE-30 bus test system. The results are compared with Firefly algorithm (FA) and Artificial Bee Colony (ABC) algorithm method to prove the effectiveness of the newest algorithm. The power loss results are quite productive, and the algorithm is the most efficient than the other methods such as ABC algorithm and FA algorithm. These results are produced by Matlab 2017b.

scholarly journals LESSENING OF ACTUAL POWER LOSS BY MODIFIED ALGORITHM

2018 ◽  
Vol 6 (8) ◽  
pp. 159-167
Author(s):  
K. Lenin
Keyword(s):  
Power Loss ◽  
Power Flow ◽  
Reactive Power ◽  
Optimization Problems ◽  
High Concentration ◽  
Reactive Power Flow ◽  
Tlbo Algorithm ◽  
Teaching Learning Based Optimization ◽  
Teaching Learning ◽  
Power Flow Problem

This paper presents a Modified Teaching-Learning-Based Optimization (MTLBO) algorithm for solving reactive power flow problem. Basic Teaching-Learning-Based Optimization (TLBO) is reliable, accurate and vigorous for solving the optimization problems. Also, it has been found that TLBO algorithm slow in convergence due to its high concentration in the accuracy. This paper presents an, Modified version of TLBO algorithm, called as Modified Teaching-Learning-Based Optimization (MTLBO). A parameter called as “weight” has been included in the fundamental TLBO equations & subsequently it increases the rate of convergence. In order to evaluate the proposed algorithm, it has been tested in practical 191 test bus system. Simulation results reveal about the better performance of the proposed algorithm in reducing the real power loss & voltage profiles are within the limits.

scholarly journals Enhanced wormhole optimizer algorithm for solving optimal reactive power problem

2020 ◽  
Vol 9 (1) ◽  
pp. 1
Author(s):  
Kanagasabai Lenin
Keyword(s):  
Black Hole ◽  
Power Loss ◽  
High Probability ◽  
Inflation Rate ◽  
Reactive Power ◽  
Optimal Solution ◽  
Real Power ◽  
Local Optimal Solution ◽  
Simulation Results ◽  
Power Problem

In this paper Enhanced Wormhole Optimizer (EWO) algorithm is used to solve optimal reactive power problem. Proposed algorithm based on the Wormholes which exploits the exploration space. Between different universes objects are exchanged through white or black hole tunnels. Regardless of the inflation rate, through wormholes objects in all universes which possess high probability will shift to the most excellent universe. In the projected Enhanced Wormhole Optimizer (EWO) algorithm in order to avoid the solution to be get trapped into the local optimal solution Levy flight has been applied.  Projected Enhanced Wormhole Optimizer (EWO) algorithm has been tested in standard IEEE 14, 30, 57,118,300 bus test systems and simulation results show that the EWO algorithm reduced the real power loss efficiently.

scholarly journals MODELING AND CONTROL OF FACTS DEVICES FOR REAL & REACTIVE POWER ENHANCEMENT

2014 ◽  
pp. 116-121
Author(s):  
A. MURUGAN
Keyword(s):  
Transmission Lines ◽  
Power Flow ◽  
Reactive Power ◽  
Real Power ◽  
Modeling And Control ◽  
Reactive Power Flow ◽  
Capacitor Voltage ◽  
Flow Controller ◽  
Ac Transmission ◽  
Power Flow Controller

The main objective of this paper is detailed study about a new real and reactive power coordination controller for a interline power flow controller (IPFC). The reactive power transfer is occurring at reactive power coordination of IPFC The basic control for the IPFC is such that the series converter of the IPFC controls the transmission line real/reactive power flow and the shunt converter of the IPFC controls the IPFC bus voltage/shunt reactive power and the DC link capacitor voltage. In steady state, the shunt converter of the IPFC supplies the real power demand of the series converter. The interline power flow controller (IPFC) is one of the latest generation flexible AC transmission systems (FACTS) controller used to control power flows of multiple transmission lines To avoid instability/loss of DC link capacitor voltage during transient conditions, a new real power coordination controller has been designed.

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