scholarly journals Optimal Integration of Distributed Generation in Distribution System: A Case Study of Sallaghari Feeder from Thimi Switching Station, Bhaktapur, Nepal

2020 ◽  
Vol 15 (1) ◽  
pp. 242-249
Author(s):  
Basanta Pancha ◽  
Rajendra Shrestha ◽  
Ajay Kumar Jha
Keyword(s):  
Power Distribution ◽  
Distribution System ◽  
Power Loss ◽  
Low Voltage ◽  
Test System ◽  
Load Flow ◽  
Voltage Profile ◽  
Alternative Source ◽  
Load Demand ◽  
Higher Power

 The modern power distribution network is constantly being faced with an ever-growing load demand resulting into increased burden and reduced voltage, which leads to find alternative source of energy to meet it. In Nepal, the electricity supply is based on hydropower primarily, which are situated very far from load centers and hence the generated power are to be transmitted through transmission and distributed system. Among the systems, radial distribution system is popular because of low cost and simple design, but it has power quality issues like low voltage profile and higher loss. In response to the problem of increased load demand, efforts have been made to decentralize this infrastructure through the use of distributed generators. However, the improper sizing and placement of DG unit may lead to higher power loss and power instability. The optimization problem of DG unit placement and its capacity determination were performed in this research. The study has been carried out for Thimi-Sallaghari Feeder and this feeder has low voltage profile and higher power loss. The IEEE 33 bus test system was examined as a test case to demonstrate the effectiveness of the proposed approach. The study has been carried out in MATLAB using “Backward and Forward Sweep Method” for load flow analysis and Genetic Algorithm for optimization. The number of DG unit of different size integrated was varied from one to ten. The result of this study showed that the voltage at minimum voltage node, maximum active and reactive loss reduction of Thimi-Sallaghari feeder have been improved by 3.69% (from 0.942 p.u. to 0.976 p.u), 75.88 % and 75.88 % respectively with placement of DG units at three bus locations of total 658.2019 kW and 395.873 kVAR capacity. Likewise, the voltage at minimum voltage node, maximum active and reactive loss of IEEE- 33 bus system have been improved by 6.88 %, 90.11% and 89.9% respectively with placement of DG units of total 2215.488 kW and 1176.059 kVAR at 6 different locations of the network.  

Optimal Capacitors in Radial Distribution System for Loss Reduction and Voltage Enhancement

2016 ◽  
Vol 2 (3) ◽  
pp. 566 ◽  
Author(s):  
S. Bhongade ◽  
Sachin Arya
Keyword(s):  
Radial Distribution ◽  
Distribution System ◽  
Power Loss ◽  
Distribution Systems ◽  
Pso Algorithm ◽  
Load Flow ◽  
Base Case ◽  
Voltage Profile ◽  
Radial Distribution System ◽  
Case Load

The work presented in this paper is carried out with the objective of identifying the optimal location and size (Kvar ratings) of shunt capacitors to be placed in radial distribution system, to have overall economy considering the saving due to energy loss minimization. To achieve this objective, a two stage methodology is adopted in this paper. In the first stage, the base case load flow of uncompensated distribution system is carried out. On the basis of base case load flow solution, Nominal voltage magnitudes and Loss Sensitivity Factors are calculated and the weak buses are selected for capacitor placement.In the second stage, Particle Swarm Optimization (PSO) algorithm is used to identify the size of the capacitors to be placed at the selected buses for minimizing the power loss. The developed algorithm is tested for 10-bus, 34-bus and 85-bus Radial Distribution Systems. The results show that there has been an enhancement in voltage profile and reduction in power loss thus resulting in much annual saving.

AGC Control of Scheduling with Distributing Power Generation and Performance Study

2012 ◽  
Vol 220-223 ◽  
pp. 101-106
Author(s):  
Xing Wan ◽  
Xiao Li Zhang
Keyword(s):  
Power Distribution ◽  
Distribution System ◽  
Low Voltage ◽  
Performance Study ◽  
Power Distribution System ◽  
Power Resources ◽  
Distributed Generators ◽  
Load Demand ◽  
Micro Grid ◽  
And Performance

Abstract: Scheduling plans of running a large, traditional power grid often distribute power resources in each small system. And they didn’t take the scope of scheduling operation within the power distribution system into consideration. With the trend separate transmission and distribution, the number of distributed generators that installed is growing rapidly. More and more micro-grid network composed of low-voltage distribution power network are formed. With effective regulation, this system can satisfy local load demand and support networking. The establishment of mechanisms such as AGC support services, with be vital to insure the power quality and reliability. Keywords: distributing power Micro-Grid DG AGC

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 Management of Voltage Profile and Power Loss Minimization in a Grid-Connected Microgrid System Using Fuzzy-Based STATCOM Controller

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Mezigebu Getinet Yenealem ◽  
Livingstone M. H. Ngoo ◽  
Dereje Shiferaw ◽  
Peterson Hinga
Keyword(s):  
Distribution System ◽  
Power Loss ◽  
Power Flow ◽  
Fossil Fuels ◽  
Distribution Network ◽  
Voltage Profile ◽  
Static Synchronous Compensator ◽  
Voltage Unbalance ◽  
Load Demand ◽  
Power Loss Reduction

The expansion of renewable energy is continuing powerfully. Electrical system ought to transmit power with diminished loss, improved power quality, and reliability while pleasing the need of customer’s load demand. Nevertheless, owing to the exhaustion of fossil fuels and their environmental impact, the availability of quality, stable, and reliable power in developing countries is worrying. Integrating a solar-wind based microgrid to the distribution network is the more feasible and best alternative solution to gratify the customer intensifying power demand while seeing the strict environmental regulations of generating power. However, the microgrid system connected in a distribution network has diverse problems and challenges. The problems comprise the development of voltage sag and swell, voltage unbalance, and power losses because of the intermittent nature of PV and wind resources. The objective of this study is to integrate microgrid system with STATCOM (static synchronous compensator) controller to ensure the higher power flow with enhanced voltage profile and reduced power loss. MATLAB/PSAT is used to model microgrid and STATCOM controller connected to the grid. Proportional integral (PI) and fuzzy logic controllers (FLC) are also applied to control the STATCOM. The effectiveness of STATCOM with microgrid integration is tested by connecting to the main distribution system using standard IEEE 30-bus system. Finally, it was observed that STATCOM raises the capacity of the distribution line and contributes to voltage profile improvements and power loss reduction.

scholarly journals Continuous domain ant colony optimization for distributed generation placement and losses minimization

2020 ◽  
Vol 9 (2) ◽  
pp. 261
Author(s):  
Zulkiffli Abdul Hamid ◽  
Ismail Musirin ◽  
Ammar Yasier Azman ◽  
Muhammad Murtadha Othman
Keyword(s):  
Ant Colony Optimization ◽  
Distributed Generation ◽  
Distribution System ◽  
Power Loss ◽  
Test System ◽  
Ant Colony ◽  
Optimal Size ◽  
Voltage Profile ◽  
Radial Distribution System ◽  
Continuous Domain

This paper proposes a method for distributed generation (DG) placement in distribution system for losses minimization and voltage profile improvement. An IEEE 33-bus radial distribution system is used as the test system for the placement of DG. To facilitate the sizing of DG capacity, a meta-heuristic algorithm known as Continuous Domain Ant Colony Optimization (ACO<sub>R</sub>) is implemented. The ACO<sub>R</sub> is a modified version of the traditional ACO which was developed specially for solving continuous domain optimization problem like sizing a set of variables. The objective of this paper is to determine the optimal size and location of DG for power loss minimization and voltage profile mitigation. Three case studies were conducted for the purpose of verification. It was observed that the proposed technique is able to give satisfactory results of real power loss and voltage profile at post-optimization condition. Experiment under various loadings of the test system further justifies the objective of the study.

scholarly journals Energy Loss Minimization by Optimal Siting and Sizing of DG with Network Reconfiguration in Distribution Networks

2019 ◽  
Vol 8 (10) ◽  
pp. 3621-3625
Keyword(s):  
Energy Loss ◽  
Distribution System ◽  
Power Loss ◽  
Reactive Power ◽  
Low Voltage ◽  
Distribution Networks ◽  
Network Reconfiguration ◽  
Voltage Profile ◽  
Loss Minimization ◽  
Power Loss Reduction

The main aim of the distribution system is delivery the power to the consumers. Because of, aging of electrical infrastructure, old control mechanism, increased power demand causing exploitation of the present electrical networks leads to low voltage profile, more active and reactive power loss with various power quality related issues causing poor network operation. In this method maximization of voltage profile with energy loss minimization is carried using network reconfiguration along with optimal siting of the distributed generation (DG). The proposed methodology is carried out on five bus system. The obtained results are impressive interms of voltage stability and power loss reduction.

scholarly journals Optimal distributed generation location and sizing for loss minimization and voltage profile optimization using ant colony algorithm

2021 ◽  
Vol 3 (2) ◽  
Author(s):  
Adeseye Amos Ogunsina ◽  
Moses Omolayo Petinrin ◽  
Olutomilayo Olayemi Petinrin ◽  
Emeka Nelson Offornedo ◽  
Joseph Olawole Petinrin ◽  
...  
Keyword(s):  
Distributed Generation ◽  
Power Distribution ◽  
Distribution System ◽  
Power Loss ◽  
Ant Colony Algorithm ◽  
Ant Colony ◽  
Voltage Profile ◽  
Real Power ◽  
Power Distribution System ◽  
The Impact

AbstractA system of power generation whereby the generating equipment is located close to the point of usage, thereby reducing losses and operation cost is called distributed generation (DG). However, it is imperative that DGs are sited such that the quality of power delivered is optimized and the total real power loss within the system minimized. This paper proposes an approach for optimum sizing and siting of DGs sizing in a power distribution system using Ant Colony Optimization (ACO) algorithm. To validate the algorithm the IEEE 30 bus standard test system was employed. A 92% decrease in real power loss within the system relative to the value before the connection of DGs was observed, while the minimum bus voltage increased from 0.656 per unit to 0.965 per unit. The results obtained from ACO are further verified by creating an ETAP model of the IEEE 30 bus system and simulating the impact of DG on the system. A significant reduction in total real power losses within the system and improvement in voltage profile was observed when the DGs are placed at the ACO derived sites relative to at other locations. Therefore, Ant Colony Algorithm can be used in deriving the optimum sites and sizes of DGs in a power distribution system.

scholarly journals Gaussian Copula Methodology to Model Photovoltaic Generation Uncertainty Correlation in Power Distribution Networks

Energies ◽  
2021 ◽  
Vol 14 (9) ◽  
pp. 2349
Author(s):  
Harshavardhan Palahalli ◽  
Paolo Maffezzoni ◽  
Giambattista Gruosso
Keyword(s):  
Power Distribution ◽  
Distribution System ◽  
Low Voltage ◽  
Distribution Networks ◽  
Load Flow ◽  
Power Grids ◽  
Gaussian Copula ◽  
Expansion Planning ◽  
Probabilistic Load Flow ◽  
Photovoltaic Generators

Deterministic load flow analyses of power grids do not include the uncertain factors that affect the network elements; hence, their predictions can be very unreliable for distribution system operators and for the decision makers who deal with the expansion planning of the power network. Adding uncertain probability parameters in the deterministic load flow is vital to capture the wide variability of the currents and voltages. This is achieved by probabilistic load flow studies. Photovoltaic systems represent a remarkable source of uncertainty in the distribution network. In this study, we used a Gaussian copula to model the uncertainty in correlated photovoltaic generators. Correlations among photovoltaic generators were also included by exploiting the Gaussian copula technique. The large sets of samples generated with a statistical method (Gaussian copula) were used as the inputs for Monte Carlo simulations. The proposed methodologies were tested on two different networks, i.e., the 13 node IEEE test feeder and the non-synthetic European low voltage test network. Node voltage uncertainty and network health, measured by the percentage voltage unbalance factor, were investigated. The importance of including correlations among photovoltaic generators is discussed.

scholarly journals Optimal sizing and location of distributed generation for loss minimization using firefly algorithm

2019 ◽  
Vol 14 (1) ◽  
pp. 421 ◽  
Author(s):  
Muhamad Najib Kamarudin ◽  
Tengku Juhana Tengku Hashim ◽  
AbdulHamid Musa
Keyword(s):  
Distributed Generation ◽  
Radial Distribution ◽  
Power Distribution ◽  
Firefly Algorithm ◽  
Distribution Network ◽  
Flow Analysis ◽  
Test System ◽  
Load Flow ◽  
Voltage Profile ◽  
Load Flow Analysis

<span>Distributed generation (DG) plays an important role in improving power quality as well as system realibility. As the incorporation of DG in the power distribution network creates several problems to the network operators, locating a suitable capacity and placement for DG will essentially help to improve the quality of power delivery to the end users. This paper presents the simulation of an application of firefly algorithm (FA) for optimally locating the most suitable placement and capacity of distributed generation (DG) in IEEE 33-bus radial distribution network. This strategy aims at minimizing losses together with improving the voltage profile in distribution network. The losses in real power and voltages at each bus are obtained using load flow analysis which was performed on an IEEE 33-bus radial distribution network using forward sweep method.  The proposed method comprises of simulation of the test system with DG as well as in the absence of DG in the system. </span><span>A comparison between the Firefly Algorithm (FA) with Genetic Algorithm (GA) is also demonstrated in this paper. The results obtained have proven that the Firefly Algorithm has a better capability at improving both the voltage profile and the power losses in the system.</span>

A WDO Framework for Optimal Deployment of DGs and DSCs in a Radial Distribution System Under Daily Load Pattern to Improve Techno-Economic Benefits

2018 ◽  
Vol 7 (2) ◽  
pp. 1-38
Author(s):  
Satish Kumar Injeti ◽  
Thunuguntla Vinod Kumar
Keyword(s):  
Objective Function ◽  
Radial Distribution ◽  
Distribution System ◽  
Power Loss ◽  
Economic Benefits ◽  
Load Flow ◽  
Outcome Analysis ◽  
Voltage Profile ◽  
Load Pattern ◽  
Daily Load

This article presents a methodology to determine optimal locations and sizes of DGs (Distributed Generator) and DSCs (D-STATCOM) simultaneously in a radial distribution network during a daily load pattern to improve the techno-economic benefits. An effective weighted objective function has been designed to address daily power loss minimization of the three techno-economic benefits, improvement of daily voltage profile and maximization of net annual savings due to the placement of DGs and DSCs. A repetitive backward-forward sweep based load flow has been used to calculate the daily power loss and bus voltages. To optimize the designed objective function, an efficient and simple nature-inspired wind driven optimization (WDO) algorithm has been used. To validate the effectiveness of the proposed methodology, different scenarios are considered and a detailed outcome analysis is presented.

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