scholarly journals A Novel Hybrid Approach for Optimal Placement of Non-Dispatchable Distributed Generations in Radial Distribution System

Mathematics ◽  
2021 ◽  
Vol 9 (24) ◽  
pp. 3171
Author(s):  
Prem Prakash ◽  
Duli Chand Meena ◽  
Hasmat Malik ◽  
Majed A. Alotaibi ◽  
Irfan Ahmad Khan
Keyword(s):  
Radial Distribution ◽  
Distribution Network ◽  
Hybrid Approach ◽  
Optimization Techniques ◽  
Optimal Placement ◽  
Normal Distribution Function ◽  
Voltage Profile ◽  
Loss Minimization ◽  
Distributed Generations ◽  
Point Estimate Method

The objective of the present paper is to study the optimum installation of Non-dispatchable Distributed Generations (NDG) in the distribution network of given sizes under the given scheme. The uncertainty of various random (uncertain) parameters like load, wind and solar operated DG besides uncertainty of fuel prices has been investigated by the three-point estimate method (3-PEM) and Monte Carlo Simulation (MCS) based methods. Nearly twenty percent of the total number of buses are selected as candidate buses for NDG placement on the basis of system voltage profile to limit the search space. Weibull probability density function (PDF) is considered to address uncertain characteristics of solar radiation and wind speed under different scenarios. Load uncertainty is described by Standard Normal Distribution Function (SNDF). To investigate the solution of optimal probabilistic load flow (OPLF) three-point PEM-based technique was applied. For optimization, Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and GA-PSO hybrid-based Artificial Intelligent (AI) based optimization techniques are employed to achieve the optimum value of the multi-objectives function. The proposed multi-objective function comprises loss and different costs. The proposed methods have been applied to IEEE 33- bus radial distribution network. Simulation results obtained by these techniques are compared based on loss minimization capability, enhancement of system bus voltage profile and reduction of cost and fitness functions. The major findings of the present study are the PEM-based method which provides almost similar results as MCS based method with less computation time and as far as loss minimization capacity, voltage profile improvement etc. is concerned, the hybrid-based optimization methods are compared with GA and PSO based optimization techniques.

scholarly journals Voltage Profile Enhancement and Loss Minimization Using Optimal Placement and Sizing of Distributed Generation in Reconfigured Network

Machines ◽  
2021 ◽  
Vol 9 (1) ◽  
pp. 20
Author(s):  
Waseem Haider ◽  
S Jarjees Ul Hassan ◽  
Arif Mehdi ◽  
Arif Hussain ◽  
Gerardo Ondo Micha Adjayeng ◽  
...  
Keyword(s):  
Distributed Generation ◽  
Radial Distribution ◽  
Distribution System ◽  
Power Loss ◽  
Distribution Network ◽  
Optimal Placement ◽  
Total Power ◽  
Voltage Profile ◽  
Penalty Factor ◽  
Before And After

Power loss and voltage instability are major problems in distribution systems. However, these problems are typically mitigated by efficient network reconfiguration, including the integration of distributed generation (DG) units in the distribution network. In this regard, the optimal placement and sizing of DGs are crucial. Otherwise, the network performance will be degraded. This study is conducted to optimally locate and sizing of DGs into a radial distribution network before and after reconfiguration. A multi-objective particle swarm optimization algorithm is utilized to determine the optimal placement and sizing of the DGs before and after reconfiguration of the radial network. An optimal network configuration with DG coordination in an active distribution network overcomes power losses, uplifts voltage profiles, and improves the system stability, reliability, and efficiency. For considering the actual power system scenarios, a penalty factor is also considered, this penalty factor plays a crucial role in the minimization of total power loss and voltage profile enhancement. The simulation results showed a significant improvement in the percentage power loss reduction (32% and 68.05% before and after reconfiguration, respectively) with the inclusion of DG units in the test system. Similarly, the minimum bus voltage of the system is improved by 4.9% and 6.53% before and after reconfiguration, respectively. The comparative study is performed, and the results showed the effectiveness of the proposed method in reducing the voltage deviation and power loss of the distribution system. The proposed algorithm is evaluated on the IEEE-33 bus radial distribution system, using MATLAB software.

scholarly journals Optimization of fuzzy controllers for a radial distribution network

2019 ◽  
Vol 13 (1) ◽  
pp. 17-23
Author(s):  
Helbert Eduardo Espitia Cuchango ◽  
Iván Machón González ◽  
Hilario López García ◽  
Domingo Guzmán Díaz González
Keyword(s):  
Energy Distribution ◽  
Distributed Generation ◽  
Radial Distribution ◽  
Distribution Systems ◽  
Distribution Network ◽  
Voltage Profile ◽  
Fuzzy Controllers ◽  
Descent Algorithm ◽  
Distributed Approach

Energy distribution systems present alterations in the voltage profile in their nodes when distributed generation elements are installed. As a consequence, tension can be risen in a level beyond the admissible. This paper presents the optimization to three fuzzy controllers located in a distribution network with radial topology. The optimization of each controller is performed using the maximum descent algorithm, which is separately carried out; thus, having a distributed approach. The interaction between generators is considered to perform this process; the results show that the adjustment of the controllers is achieved

scholarly journals Investigation of Optimal PV Allocation to Minimize System Losses and Improve Voltage Stability for Distribution and Transmission Networks Using MATLAB and DigSilent

2021 ◽  
Vol 9 ◽  
Author(s):  
Mohamed Abdul Rasheed ◽  
Renuga Verayiah
Keyword(s):  
Objective Function ◽  
Radial Distribution ◽  
Power Factor ◽  
Analytical Method ◽  
Distribution Network ◽  
Computation Time ◽  
Transmission Network ◽  
Voltage Profile ◽  
Multi Objective ◽  
Test Systems

Electricity generation from renewable energy sources such as solar energy is an emerging sustainable solution. In the last decade, this sustainable source was not only being used as a source of power generation but also as distributed generation (DG). Many literatures have been published in this field with the objective to minimize losses by optimizing the DG size and location. System losses and voltage profile go hand-in-hand; as a result, when system losses are minimized, eventually the voltage profile improves. With improvement in inverter technologies, PV-DG units do not have to operate at a unity power factor. The majority of proposed algorithms and methods do not consider power factor optimization as a necessary optimization. This article aims to optimize the size, location, and power factor of PV-DG units. The simulations are performed on the IEEE 33 bus radial distribution network and IEEE 14 bus transmission network. The methodologies developed in this article are divided into two sections. The first section aims to optimize the PV-DG size and location. A multi-objective function is developed by using system losses and a voltage deviation index. Genetic algorithm (GA) is used to optimize the multi-objective function. Next, analytical processes are developed for verification. The second section aims to further enhance PV-DG by optimizing the power factor of PV-DG. The simulation is performed for static load in both systems, which are the IEEE 33 bus radial distribution network and IEEE 14 bus transmission network. A mathematical analytical method was developed, and it was found to be sufficient to optimize the power factor of the PV-DG unit. The results obtained show that voltage stability indices help minimize the computation time by determining the optimal locations for DG placement in both networks. In addition, the GA method attained faster convergence than the analytical method and hence is the best optimal sizing for both test systems with minimum computation time. Additionally, the optimization of the power factor for both test systems has demonstrated further improvement in the voltage profile and loss minimization. In conclusion, the proposed methodology has shown promising results for both transmission and distribution networks.

Swarm-Intelligence-Based Optimal Placement and Sizing of Distributed Generation in Distribution Network

2018 ◽  
pp. 29-48 ◽  
Author(s):  
Mahesh Kumar ◽  
Perumal Nallagownden ◽  
Irraivan Elamvazuthi ◽  
Pandian Vasant ◽  
Luqman Hakim Rahman
Keyword(s):  
Distributed Generation ◽  
Radial Distribution ◽  
Distribution System ◽  
Voltage Stability ◽  
Reactive Power ◽  
Distribution Network ◽  
Stability Index ◽  
Pso Algorithm ◽  
Distribution Networks ◽  
Optimal Placement

In the distribution system, distributed generation (DG) are getting more important because of the electricity demands, fossil fuel depletion and environment concerns. The placement and sizing of DGs have greatly impact on the voltage stability and losses in the distribution network. In this chapter, a particle swarm optimization (PSO) algorithm has been proposed for optimal placement and sizing of DG to improve voltage stability index in the radial distribution system. The two i.e. active power and combination of active and reactive power types of DGs are proposed to realize the effect of DG integration. A specific analysis has been applied on IEEE 33 bus system radial distribution networks using MATLAB 2015a software.

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