scholarly journals Optimal Placement and Sizing of Distributed Generation in Distribution System using Analytical Method

2019 ◽  
Vol 8 (4) ◽  
pp. 6357-6363

The reliability of distribution network can be improved with the penetration of small scale distributed generation (DG) unit to the distribution grid. Nevertheless, the location and sizing of the DG in the distribution network have always become a topic of debate. This problem arises as different capacity of DG at various location can affect the performance of the entire system. The main objective of this study is to recommend a suitable size of DG to be placed at the most appropriate location for better voltage profile and minimum power loss. Therefore, this paper presents an analytical approach with a fixed DG step size of 500 kW up to 4500 kW DG to analyses the effect of a single P-type DG in IEEE 33 bus system with consideration of system power loss and voltage profile. Four scenarios have been selected for discussions where Scenario 1: 3500 kW DG placed at node 3; Scenario 2: 2500 kW DG placed at node 6; Scenario 3: 1000 kW DG placed at node 18 and Scenario 4: 3000 kW DG placed at node 7. Results show that all the four scenarios are able to reduce the power loss and improve the voltage profile however Scenario 4 has better performance where it complies with minimum voltage requirement and minimizing the system power loss.

Machines ◽  
2021 ◽  
Vol 9 (1) ◽  
pp. 20
Author(s):  
Waseem Haider ◽  
S Jarjees Ul Hassan ◽  
Arif Mehdi ◽  
Arif Hussain ◽  
Gerardo Ondo Micha Adjayeng ◽  
...  

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.


Author(s):  
Ahmed Mohamed Abdelbaset ◽  
AboulFotouh A. Mohamed ◽  
Essam Abou El-Zahab ◽  
M. A. Moustafa Hassan

<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>


2021 ◽  
Vol 39 (4A) ◽  
pp. 528-542
Author(s):  
Ali H. Mohammed ◽  
Suad I. Shahl

Voltage sags are considered as one of the most detrimental power quality (PQ) disturbance due to their costly influence on sensitive loads. This paper investigates the voltage sag mitigation in distribution network following the occurrence of a fault. Two software are used in this work; the 1st is MATLAB R2017a for implementation of the Differential Evaluation (DE) algorithm to find the optimal location and size DG and while the 2nd software is CYME 7.1 for the distribution system modelling and analysis. The effectiveness of the proposed method is tested by implementing it on IEEE 33-bus system, and then it is applied to Al-Masbh distribution network in Baghdad city as a case study. The paper aims to enhance voltage profile, power loss reduction, and relieve distribution lines overloading, by optimal placement of distributed generation (DG). The results indicate the efficiency of the proposed method comparing with Real Coded Genetic Algorithm (RCGA).


2018 ◽  
Vol 7 (4.24) ◽  
pp. 167
Author(s):  
Mr. Rajesh Kumar Samala ◽  
Dr. K Mercy Rosalina

This research is to enhance the quality of power by reduce real power loss in distribution system and enables voltage profile enhancement at each bus. This will achieve by integrating Distributed Generation (DG) in optimal place with suitable size. In order to overcome the disadvantage of sluggish convergence of conventional algorithms the BAT Algorithm (BA) is used. In this paper the week buses are finding by using Backward/Forward (BW/FW) sweep approach based on real power loss. Later by using BA approach determination of optimal capacity and location will be done. This optimal size and location will leads to great minimization in real power loss and improvement of voltage at each bus. In this research the wind energy and Photo Voltaic (PV) energies are consider as DGs. This research is to determine the advantage of the proposed analysis on IEEE-69 radial bus using MATLAB software. The results were evaluated with the GSA approach existing in literature. Finally simulation outcomes prove that the proposed approach performance is superior in enhancing the power quality by optimal placement of DG and capacity of the DG.


Reconfiguration is a process that supports to eliminate the power loss from a distribution network and this process have the capability to reduce the losses up to a specific point. Additionally, loss minimization may be calculated through the presentation of Distributed Generation (DG) units. Conversely, the incorporation of DG into the distribution network at an improper position may cause higher in losses and fluctuations in voltage. In the meantime, the uncertainty in voltage may produce partial power failure in the system. For that reason, it is essential to deliberate the stability boundaries in DGs position and sizing in the Radial Distribution System (RDS). In this research paper, hybrid Binary Particle Swarm Optimization (BPSO) with Flower Pollination Algorithm (FPA) is proposed for the ideal reconfiguration process and placing the DG in the 69-bus RDS. BPSO is applied to identify the best DG reconfiguration and FPA is proposed to determine the optimal DG size. This technique narrowly changes the DG location in every load bus of the network that delivers the minimum value of the objective function, which is considered as the finest candidate for DG connection. The simulation outcomes indicate the proposed method is more effective in reducing the power loss from 224.9804 to 27.2183 KW with the reduction of 88.8972% when compared to existing algorithm


2012 ◽  
Vol 433-440 ◽  
pp. 7190-7194 ◽  
Author(s):  
Nattachote Rugthaicharoencheep ◽  
Thong Lantharthong ◽  
Awiruth Ratreepruk ◽  
Jenwit Ratchatha

This paper presents the optimal and sizing of distributed generation (DG) placement in a radial distribution system for loss reduction. The main emphasis of this paper is to identify proper locations for installing DGs in a distribution system to reduce active power loss and improve bus voltages. Nevertheless, proper placement and sizing of DG units are not straightforward to be identified as a number of their positions and capacities need to be determined. It is therefore proposed in this paper to solve a DG placement problem based on a Tabu search algorithm. The objective function of the problem is to minimize the system loss subject to power flow constraints, bus voltage limits, pre specified number of DGs, and their allowable total installed capacity, and only one distributed generator for one installation position. The effectiveness of the methodology is demonstrated by a practical sized distribution system consisting of 69 bus and 48 load points. The results show that the optimal DG placement and sizing can be identified to give the minimum power loss while respecting all the constraints.


Author(s):  
Mahesh Kumar ◽  
Perumal Nallagownden ◽  
Irraivan Elamvazuthi ◽  
Pandian Vasant ◽  
Luqman Hakim Rahman

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.


Sign in / Sign up

Export Citation Format

Share Document