scholarly journals Enhancement of Voltage Profile by Optimal Placement of Distributed Generators with UPFC in Distribution Networks

2019 ◽  
Vol 8 (6) ◽  
pp. 2733-2738 ◽  
Keyword(s):  
Transmission Lines ◽  
Network Reliability ◽  
Distribution Network ◽  
Flow Analysis ◽  
Distribution Networks ◽  
Load Flow ◽  
Optimal Placement ◽  
Voltage Profile ◽  
Load Flow Analysis ◽  
Distributed Generators

The Distributed generation and fast operating power electronic devices are attracting more attention due to their effective solution for improvement in the voltage profile, to meet the increasing power consumption, reduction in the power loss, enhancement in the power transfer capacity of the transmission lines, reducing the overloading of the entire network. The optimal placement of DG and FACTs devices plays key role in improvement of the network reliability and voltage stability. In this paper exhaustive load flow analysis is carried out for optimal placement of DG and UPFC. The proposed method is tested on 40 bus distribution network. The obtained results are satisfactory in terms of improvement in the overall performance of the distribution network.

scholarly journals Optimal Placement of Capacitor to Enhance the Efficiency of the Distribution Network

2019 ◽  
Vol 8 (9) ◽  
pp. 2877-2881 ◽  
Keyword(s):  
Reactive Power ◽  
Distribution Network ◽  
Flow Analysis ◽  
Distribution Networks ◽  
Load Flow ◽  
Optimal Placement ◽  
Load Flow Analysis ◽  
Network Operation ◽  
Overall Performance ◽  
Shunt Capacitor

In this paper optimal placement of capacitor is carried out by using exhaustive load flow analysis for minimization of the power loss at different loading conditions. The shunt capacitor mainly used for reactive power compensation to maintain the good p.f in the network to improve the overall performance of the distribution networks. The obtained results are satisfactory interms of improvement in the efficiency of the distribution network operation.

scholarly journals Probabilistic Load Flow Algorithm of Distribution Networks with Distributed Generators and Electric Vehicles Integration

Energies ◽  
2019 ◽  
Vol 12 (22) ◽  
pp. 4234 ◽  
Author(s):  
Zhou ◽  
Yang ◽  
Yang ◽  
Yang ◽  
Littler ◽  
...  
Keyword(s):  
Correlation Analysis ◽  
Energy Distribution ◽  
Flow Analysis ◽  
Electrical Energy ◽  
Distribution Networks ◽  
Load Flow ◽  
Probabilistic Load Flow ◽  
Load Flow Analysis ◽  
Distributed Generators ◽  
Probabilistic Load

Probabilistic Load Flow (PLF) calculations are important tools for analysis of the steady-state operation of electrical energy networks, especially for electrical energy distribution networks with large-scale distributed generators (DGs) and electric vehicle (EV) integration. Traditional PLF has used the Cumulant Method (CM) and Latin Hypercube Sampling (LHS) method. However, traditional CM requires that each input variable be independent of one another, and the Cholesky decomposition adopted by the traditional LHS has limitations in that it is only applicable for positive definite matrices. To solve these problems, taking into account the Q-MCS theory of LHS, this paper proposes a CM PLF algorithm based on improved LHS (ILHS-CM). The cumulants of the input variables are obtained based on sampling results. The probability distribution of the output variables is obtained according to the Gram-Charlier series expansion. Moreover, DGs, such as wind turbines, photovoltaic (PV) arrays, and EVs integrated into the electrical energy distribution networks are comprehensively considered, including correlation analysis and dynamic load flow analysis for EV-coordinated charging. Four scenarios are analyzed based on the IEEE-30 node network, including with/without DGs and EVs, error analysis and performance evaluation of the proposed algorithm, correlation analysis of DGs and EVs, and dynamic load flow analysis with EV integration. The results presented in this paper demonstrate the effectiveness, accuracy, and practicability of the proposed algorithm.

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>

scholarly journals Cost Sustainability Analysis of an Enhanced Distribution Network

2018 ◽  
Vol 3 (1) ◽  
Author(s):  
Oluleke Babayomi ◽  
Sunday Adetona ◽  
Charles Osheku ◽  
Ayodele Opasina
Keyword(s):  
Capital Investment ◽  
Energy Savings ◽  
Distribution Network ◽  
Flow Analysis ◽  
Load Flow ◽  
Solar Pv ◽  
Voltage Profile ◽  
Power Losses ◽  
Load Flow Analysis ◽  
Sustainability Analysis

This study presents the cost sustainability analysis of an enhanced distribution network (DN). In the study, the enhancement of the DN was achieved through network reconfiguration (NR) and the introduction of distributed generation units (DGs) at some locations. When the DN was only reconfigured, the power losses in the network reduced by 23.39 % at 1.0 p.u loading; whereas, the minimum voltage profile in the network improved by 1.79 %. When both reconfiguration and DG were engaged in losses minimization, power losses reduced by 61.94 % at full load, whereas the minimum voltages in the network improved by 7.66 %. When the DN was reconfigured and DGs were embedded at three different locations, the energy losses in the entire network reduced by 61.94 % and 58.37 % at 0.5 and 1.0 loadings respectively; whereas, the minimum voltages in the network improved by 1.21 % and 8.46 % at 0.5 p.u and 1.0 p.u loadings respectively. The information obtained from the load flow analysis was used for the economic analysis of the DN when both reconfigured and three DGs were embedded at different locations of the network. The annual financial energy gains evaluated from the annual energy savings was about $125,000.00, when the DN operated at 100 % loading capacity all year round. The financial savings are sufficient to cover annual operational cost of solar PV DGs; as well as, recovering its capital investment with a payback period of 5 years.

scholarly journals Load flow analysis using newton raphson method in presence of distributed generation

2021 ◽  
Vol 12 (1) ◽  
pp. 489
Author(s):  
Tebbakh Noureddine ◽  
Labed Djamel
Keyword(s):  
Reactive Power ◽  
Flow Analysis ◽  
Distribution Networks ◽  
Test System ◽  
Load Flow ◽  
Voltage Profile ◽  
Real Power ◽  
Load Flow Analysis ◽  
Newton Raphson ◽  
Raphson Method

<p>Distributed generations (DG), specially including renewable sources such as wind and sun are offering several opportunities for the currently in existence distribution networks and becoming one of the keys of treatment of its problems. Knowing the effects of each kind of DG on distribution networks is a primordial task because DG impacts differ from one kind to another. In this paper, we have analyzed and compared the effects of two kinds of DG, DG which provides real power only and DG which provides real power and reactive power at the same time connected at the critical bus in DN on the voltage profile, real and reactive power losses. We have proposed Newton Raphson method using Matlab to investigate the impacts of these two kinds of DG on 57-bus IEEE distribution test system. The obtained results have been exposed in detail at the end of this paper.</p>

scholarly journals Fault Location of Active Distribution Networks Based on the Golden Section Method

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Haizhu Yang ◽  
Xiangyang Liu ◽  
Yiming Guo ◽  
Peng Zhang
Keyword(s):  
Fault Location ◽  
Golden Section ◽  
Flow Analysis ◽  
Energy Resource ◽  
Distribution Networks ◽  
Load Flow ◽  
Distributed Energy ◽  
Load Flow Analysis ◽  
Distributed Energy Resource ◽  
Golden Section Method

Aiming at the problem of fault location in distribution networks with distributed energy resources (DERs), a fault location method based on the concepts of minimum fault reactance and golden section is proposed in this paper. Considering the influence of distributed energy resource supply on fault point current in distribution networks, an improved trapezoidal iteration method is proposed for load flow analysis and fault current calculation. This method only needs to measure the synchronous current of the distributed energy resource and does not need to measure the voltage information. Therefore, the investment in equipment is reduced. Validation is made using the IEEE 34-node test feeder. The simulation results show that the method is suitable for fault location of distribution networks with multiple distributed generators. This method can accurately locate the faults of the active distribution network under different conditions.

scholarly journals Multi-Objective Grey Wolf Optimization for Optimal Allocation of Distributed Generators in Distribution Networks

2020 ◽  
Vol 9 (3) ◽  
pp. 664-670
Keyword(s):  
Radial Distribution ◽  
Power Loss ◽  
Distribution Network ◽  
Distribution Networks ◽  
Optimal Placement ◽  
Grey Wolf ◽  
Grey Wolf Optimization ◽  
Real Power ◽  
Multi Objective ◽  
Distributed Generators

The power loss in the radial distribution network is appreciable as compared to transmission network. To reduce the power loss in distribution network which is radial in nature, the solution methodology adopted in this paper is optimal placement of distributed generators (DG). The optimization incorporated is Multi-objective Grey Wolf Optimization (MOGWO). The optimization is accomplished for three different cases. In each case two objective functions are simultaneously optimized to obtain non-dominated solutions using Multi-objective Grey Wolf Optimization. Case (1): To minimize the real power loss and maximize the savings obtained due to DG installation. Case (2): To minimize real power loss and maximum voltage deviation in the network. Case (3): To minimize real power loss and rating of DG installed. MOGWO method maintains an archive which contains pareto-optimal solutions. The archive mimics the behaviour of grey wolves. MOGWO method is verified on radial distribution networks. The effectiveness of the optimization method is proven by comparing the results with other optimization methods available in the literature.

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