scholarly journals Optimal Location of Distributed Generation and its Impacts on Voltage Stability

Author(s):  
Manoj Kumar Nigam ◽  
V.K. Sethi

<p>Distributed generation (DG) technology is based on the renewable sources of energy. Now a day’s distributed generation plays an important role of power generation utilities to fulfill the increasing demand of power at the costumer’s site. A distributed generation is the small generation unit with capacity varying from kW (kilowatt) to few MW (megawatt). The main aim of this paper is to find the solution for optimal location of connecting DG and also the disturbances in the voltage fluctuations responds to imperfection of connecting DG. A test network of IEEE-30 bus system has been simulated using PSAT 2.1.7. The compensation methods have also been developed for filtering out the disturbances caused by the DG connection. The disturbance in the voltage profile is improved by minimizing the real and reactive power losses with the help of STATCOM. The proposed approach IEEE-30-bus system was tested and the result was discussed.</p>

Author(s):  
Manoj Kumar Nigam ◽  
V.K. Sethi

<p>Distributed generation (DG) technology is based on the renewable sources of energy. Now a day’s distributed generation plays an important role of power generation utilities to fulfill the increasing demand of power at the costumer’s site. A distributed generation is the small generation unit with capacity varying from kW (kilowatt) to few MW (megawatt). The main aim of this paper is to find the solution for optimal location of connecting DG and also the disturbances in the voltage fluctuations responds to imperfection of connecting DG. A test network of IEEE-30 bus system has been simulated using PSAT 2.1.7. The compensation methods have also been developed for filtering out the disturbances caused by the DG connection. The disturbance in the voltage profile is improved by minimizing the real and reactive power losses with the help of STATCOM. The proposed approach IEEE-30-bus system was tested and the result was discussed.</p>


Author(s):  
Su Hlaing Win ◽  
Pyone Lai Swe

A Radial Distribution network is important in power system area because of its simple design and reduced cost. Reduction of system losses and improvement of voltage profile is one of the key aspects in power system operation. Distributed generators are beneficial in reducing losses effectively in distribution systems as compared to other methods of loss reduction. Sizing and location of DG sources places an important role in reducing losses in distribution network. Four types of DG are considered in this paper with one DG installed for minimize the total real and reactive power losses. The objective of this methodology is to calculate size and to identify the corresponding optimum location for DG placement for minimizing the total real and reactive power losses and to improve voltage profile   in primary distribution system. It can obtain maximum loss reduction for each of four types of optimally placed DGs. Optimal sizing of Distributed Generation can be calculated using exact loss formula and an efficient approach is used to determine the optimum location for Distributed Generation Placement.  To demonstrate the performance of the proposed approach 36-bus radial distribution system in Belin Substation in Myanmar was tested and validated with different sizes and the result was discussed.


2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Sanjay Jain ◽  
Ganga Agnihotri ◽  
Shilpa Kalambe ◽  
Renuka Kamdar

This paper intends to enumerate the impact of distributed generation (DG) on distribution system in terms of active as well as reactive power loss reduction and improved voltage stability. The novelty of the method proposed in this paper is the simple and effective way of sizing and siting of DG in a distribution system by using two-port Z-bus parameters. The validity of the method is verified by comparing the results with already published methods. Comparative study presented has shown that the proposed method leads existing methods in terms of its simplicity, undemanding calculation procedures, and less computational efforts and so does the time. The method is implemented on IEEE 69-bus test radial distribution system and results show significant reduction in distribution power losses with improved voltage profile of the system. Simulation is carried out in MATLAB environment for execution of the proposed algorithm.


2019 ◽  
Vol 4 (10) ◽  
pp. 18-23 ◽  
Author(s):  
Abubakar Bawa ◽  
Muhammad Uthman ◽  
Farouq E. Shaibu ◽  
Koledowo Saliu Oyewale

The Point of Common Coupling (PCC) where suppliers’ responsibility and customers demand meet is of great concern due to increase degree of voltage variation assessment; valuable indicator of system conditions (voltage profile). Unstable condition of the power system outside operational or statutory limit, an adverse effect of nonlinear loads usually generate harmonics as well as fundamental frequency voltage variations and increase rate of power losses. These loads need to be compensated for. The major concerns of utility operations is to mitigate adverse effect of this system conditions. This research work focuses on optimal siting and sizing of Distributed Generation (DG) in a 43 bus distribution system. Power losses coupled with voltage deviation, considering objective function that compute present percentage losses in 11kV Dikko feeder, Abuja Electricity Distribution Company (AEDC), Suleja Distribution Network, Nigeria. We identified buses with poor voltage profile without DG installation and determined optimal sizing and siting of DGs where losses can be mitigated and power quality improved. ETAP version 12.6 2014 was used for load flow analysis to establish a decisive based case. The total load of the system considered was (3490 + j2700) kVA. Active and Reactive power losses in the system before DG installation were 246.300 kW and 289.903 kVAR respectively. DGs installation in the case study, has a considerable effects on loss reduction in the network. It is observed that 8.10% and 7.20% active and reactive power loss reduction was achieved while bus voltage improved by 0.4%. Genetic Algorithm Optimization techniques programmed in MATLAB 2015 software was used for optimal placement and sizing of the DG in the system.


Distributed generation system penetration in the existing distribution system is done for minimizing the losses and improving the voltage profile. There are total five types of distributed generation systems exist based on their power delivery like distributed generation system injecting real and reactive power, supplying real power only, supplying reactive power only, absorbing reactive power only , supplying real power and absorbing reactive power. All these five types of distributed generation systems have different penetration effects on the radial distribution system. We get different voltage profiles and power losses for different types of distributed generation systems. The testing of these five types of distributed generation systems will be done on IEEE 33 bus radial distribution system. For computing, the line parameters and power losses of the above testing system the forward-backward sweep load flow method will be applied


Author(s):  
Manoj Kumar Bansal ◽  
Pratibha Garg ◽  
Neha Gupta ◽  
Mohini Agarwal

The distribution of electricity has become a challenge as there are losses associated with its distribution and transmission. In reducing such losses employment of Distributed Generation units in the transmission network can benefit greatly. Thus, the concern is on the optimal placement of Distributed Generation units that can provide maximum benefits and optimize several conflicting attributes. In this paper, the emphasis is laid on determining an optimal location for the placement of a Distributed Generation unit under conflicting attributes such as losses, real and reactive power, and voltages at different buses. For this purpose, the Technique for Order of Preference by Similarity to best Solution a Multi-Criteria Decision-Making technique, and Fuzzy TOPSIS technique have been employed for determining the optimal placement of 10 MW Distributed Generation unit at the IEEE 20 Bus System. The results obtained can significantly benefit in reducing losses and greatly help in economical perspective as well.


2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Ghulam Mujtaba ◽  
Zeeshan Rashid ◽  
Farhana Umer ◽  
Shadi Khan Baloch ◽  
G. Amjad Hussain ◽  
...  

Decentralized power generation efficaciously merges technological advances in a rapidly changing face of power networks introducing new power system components, advanced control, renewable sources, elegant communication, and web technology paving the way for the so called smart grids. Distributed generation technology lies at the intersection point of power systems, power electronics, control engineering, renewable energy, and communication systems which are not mutually exclusive subjects. Key features of renewable integration in a distribution network include loss minimization, voltage stability, power quality improvement, and low-cost consumption resulting from abundant natural resources such as solar or wind energy. In this research work, a case study has been carried out at a 132 kV grid station of Layyah, Pakistan, which has active losses, reactive losses, low power factor, low voltage on the demand side, and overloaded transformers and distribution lines. As a result, power outage issue is frequent on the consumer side. To overcome this issue, a simulation of load flow of this system is performed using the Newton-Raphson method due to its less computational time, fewer iterations, fast convergence, and independence from slack bus selection. It finds the harsh condition in which there were 23 overloaded transformers, 38 overloaded distribution lines, poor voltage profile, and low power factor at the demand side. There is a deficit of 24 MW in the whole system along with 4.58 MW active and 12.30 MVAR reactive power losses. To remove power deficiency, distributed generation using solar plants is introduced to an 11 kV distribution system with a total of 24 units with each unit having a capacity of 1 MW. Consequently, active and reactive power losses are reduced to 0.548 MW and 0.834 MVAR, respectively. Furthermore, the voltage profile improves, the power factor enhances, and the line losses reduce to a great extent. Finally, overloaded transformers and distribution lines also return to normal working conditions.


Author(s):  
Mostafa Elshahed ◽  
Mahmoud Dawod ◽  
Zeinab H. Osman

Integrating Distributed Generation (DG) units into distribution systems can have an impact on the voltage profile, power flow, power losses, and voltage stability. In this paper, a new methodology for DG location and sizing are developed to minimize system losses and maximize voltage stability index (VSI). A proper allocation of DG has to be determined using the fuzzy ranking method to verify best compromised solutions and achieve maximum benefits. Synchronous machines are utilized and its power factor is optimally determined via genetic optimization to inject reactive power to decrease system losses and improve voltage profile and VSI. The Augmented Lagrangian Genetic Algorithm with nonlinear mixed-integer variables and Non-dominated Sorting Genetic Algorithm have been implemented to solve both single/multi-objective function optimization problems. For proposed methodology effectiveness verification, it is tested on 33-bus and 69-bus radial distribution systems then compared with previous works.


2021 ◽  
pp. 15-27
Author(s):  
Mamdouh Kamaleldin AHMED ◽  
◽  
Mohamed Hassan OSMAN ◽  
Nikolay V. KOROVKIN ◽  
◽  
...  

The penetration of renewable distributed generations (RDGs) such as wind and solar energy into conventional power systems provides many technical and environmental benefits. These benefits include enhancing power system reliability, providing a clean solution to rapidly increasing load demands, reducing power losses, and improving the voltage profile. However, installing these distributed generation (DG) units can cause negative effects if their size and location are not properly determined. Therefore, the optimal location and size of these distributed generations may be obtained to avoid these negative effects. Several conventional and artificial algorithms have been used to find the location and size of RDGs in power systems. Particle swarm optimization (PSO) is one of the most important and widely used techniques. In this paper, a new variant of particle swarm algorithm with nonlinear time varying acceleration coefficients (PSO-NTVAC) is proposed to determine the optimal location and size of multiple DG units for meshed and radial networks. The main objective is to minimize the total active power losses of the system, while satisfying several operating constraints. The proposed methodology was tested using IEEE 14-bus, 30-bus, 57-bus, 33-bus, and 69- bus systems with the change in the number of DG units from 1 to 4 DG units. The result proves that the proposed PSO-NTVAC is more efficient to solve the optimal multiple DGs allocation with minimum power loss and a high convergence rate.


DYNA ◽  
2015 ◽  
Vol 82 (192) ◽  
pp. 60-67 ◽  
Author(s):  
John Edwin Candelo-Becerra ◽  
Helman Hernández-Riaño

<p>Distributed generation (DG) is an important issue for distribution networks due to the improvement in power losses, but the location and size of generators could be a difficult task for exact techniques. The metaheuristic techniques have become a better option to determine good solutions and in this paper the application of a bat-inspired algorithm (BA) to a problem of location and size of distributed generation in radial distribution systems is presented. A comparison between particle swarm optimization (PSO) and BA was made in the 33-node and 69-node test feeders, using as scenarios the change in active and reactive power, and the number of generators. PSO and BA found good results for small number and capacities of generators, but BA obtained better results for difficult problems and converged faster for all scenarios. The maximum active power injections to reduce power losses in the distribution networks were found for the five scenarios.</p>


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