AN OPTIMIZATION APPROACH FOR MINIMIZING ENERGY LOSSES OF DISTRIBUTION SYSTEMS BASED ON DISTRIBUTED GENERATION PLACEMENT

2017 ◽  
Vol 79 (4) ◽  
Author(s):  
Umbrin Sultana ◽  
Azhar Khairuddin ◽  
A. S. Mokhtar ◽  
Sajid Hussain Qazi ◽  
Beenish Sultana
Keyword(s):  
Distributed Generation ◽  
Distribution System ◽  
Distribution Systems ◽  
Search Algorithm ◽  
Gravitational Search Algorithm ◽  
Environmental Benefits ◽  
Optimal Placement ◽  
Energy Losses ◽  
Grey Wolf Optimizer ◽  
Optimization Approach

The interest of electric utilities in distributed energy resources has increased in terms of maximising the latter’s technical, economic and  environmental benefits. This paper presents a Grey Wolf Optimizer (GWO) -based approach for optimal placement and sizing of multiple Distributed Generation (DG), aimed at reducing active and reactive energy losses in the distribution system. Power system constraints, such as voltage magnitude limits and current boundaries are also considered. Recently, a swarm intelligence technique, namely, GWO was introduced, which is inspired by grey wolves strategy and utilises four categories of grey wolves (alpha, beta, delta and omega) to simulate a leadership hierarchy. The GWO technique and two other popular methods Particle Swarm Optimization (PSO) and Gravitational Search Algorithm (GSA) – are here tested on 15- and 33-bus radial distribution systems. The numerical results obtained using these methods are compared, with the best performance recorded via the proposed GWO method in terms of not only active and reactive energy loss but also voltage profile and convergence characteristics.

Optimal Placement and Sizing of Renewable Distributed Generation via Gravitational Search Algorithm

2015 ◽  
Vol 785 ◽  
pp. 556-560 ◽  
Author(s):  
Sa'adah Daud ◽  
Aida Fazliana Abdul Kadir ◽  
Chin Kim Gan ◽  
Abdul Rahim Abdullah ◽  
Mohamad Fani Sulaima ◽  
...  
Keyword(s):  
Distributed Generation ◽  
Distribution System ◽  
Search Algorithm ◽  
Gravitational Search Algorithm ◽  
Operating Cost ◽  
Heuristic Method ◽  
Harmonic Distortion ◽  
Optimal Placement ◽  
Voltage Deviation ◽  
Gravitational Search

The installation of distributed generation (DG) gives advantages to the environment such as, it contribute in the reduction of non-peak operating cost, diversification of energy resources, lower losses thus improving overall organization. These advantages might be rescinded if no proper location and sizing of DGs are considered before the DG’s installation. This paper offers an optimal location and sizing of multiple DGs using heuristic method called gravitational search algorithm (GSA). The suggested algorithm is tested on 13-bus radial distribution system. This method is being compared with particle swarm optimization (PSO) in terms of system power loss, voltage deviation and total voltage harmonic distortion (THDv). GSA shows the ability to locate and sized DG optimally with a better performance and more reliable than PSO.

Optimal Placement and Sizing of Photovoltaic Based Distributed Generation Considering Costs of Operation Planning of Monocrystalline and Thin-Film Technologies

2018 ◽  
Vol 141 (1) ◽  
Author(s):  
Aida Fazliana Abdul Kadir ◽  
Tamer Khatib ◽  
Loo Soon Lii ◽  
Elia Erwani Hassan
Keyword(s):  
Thin Film ◽  
Distributed Generation ◽  
Distribution Systems ◽  
Search Algorithm ◽  
Gravitational Search Algorithm ◽  
Optimal Placement ◽  
Operation Planning ◽  
Power Losses ◽  
Overall Efficiency ◽  
Gravitational Search

Distributed generation (DG) technology has been growing rapidly in industries as this technology can increase the overall efficiency to the power systems. Improper placement and sizing can lead to power losses and interrupt the voltage profile of distribution systems. Studies have been done to solve the DG placement and sizing problem considering several factors, and one of the common factor is minimizing the power losses. However, it is not adequate by only considering the power losses, whereas, the costs of the generation, investment, maintenance, and losses of the distribution system must be taken in consideration. In this research, DG chosen to study is photovoltaic (PV) type which is monocrystalline and thin-film. Costs of operation planning with respect to the power losses is considered which include the costs of investment, maintenance, power loss, and generation that are determined for optimal placement and sizing of DG. The proposed method improved gravitational search algorithm (IGSA) is used in the matlab environment to find the optimal placement and sizing of DG and is tested with the IEEE 34-bus system. The performance of IGSA is then compared with gravitational search algorithm (GSA) and particle swarm optimization (PSO) to find out which algorithm gives the best fitness value and convergence rate. The purpose of this research is to identify the operation planning cost based on the optimization results and improves the optimal placement and sizing of DG in future, to provide maximum economical, technical, environmental benefits, and increase the overall efficiency to the power system.

scholarly journals A Novel Multiobjective Hybrid Technique for Siting and Sizing of Distributed Generation and Capacitor Banks in Radial Distribution Systems

2021 ◽  
Vol 13 (6) ◽  
pp. 3308
Author(s):  
Chandrasekaran Venkatesan ◽  
Raju Kannadasan ◽  
Mohammed H. Alsharif ◽  
Mun-Kyeom Kim ◽  
Jamel Nebhen
Keyword(s):  
Multiobjective Optimization ◽  
Distributed Generation ◽  
Radial Distribution ◽  
Hybrid Method ◽  
Distribution Systems ◽  
Optimization Technique ◽  
Optimal Placement ◽  
Grey Wolf Optimizer ◽  
Hybrid Technique ◽  
Metaheuristic Optimization

Distributed generation (DG) and capacitor bank (CB) allocation in distribution systems (DS) has the potential to enhance the overall system performance of radial distribution systems (RDS) using a multiobjective optimization technique. The benefits of CB and DG injection in the RDS greatly depend on selecting a suitable number of CBs/DGs and their volume along with the finest location. This work proposes applying a hybrid enhanced grey wolf optimizer and particle swarm optimization (EGWO-PSO) algorithm for optimal placement and sizing of DGs and CBs. EGWO is a metaheuristic optimization technique stimulated by grey wolves. On the other hand, PSO is a swarm-based metaheuristic optimization algorithm that finds the optimal solution to a problem through the movement of the particles. The advantages of both techniques are utilized to acquire mutual benefits, i.e., the exploration ability of the EGWO and the exploitation ability of the PSO. The proposed hybrid method has a high convergence speed and is not trapped in local optimal. Using this hybrid method, technical, economic, and environmental advantages are enhanced using multiobjective functions (MOF) such as minimizing active power losses, voltage deviation index (VDI), the total cost of electrical energy, and total emissions from generation sources and enhancing the voltage stability index (VSI). Six different operational cases are considered and carried out on two standard distribution systems, namely, IEEE 33- and 69-bus RDSs, to demonstrate the proposed scheme’s effectiveness extensively. The simulated results are compared with existing optimization algorithms. From the obtained results, it is observed that the proposed EGWO-PSO gives distinguished enhancements in multiobjective optimization of different conflicting objective functions and high-level performance with global optimal values.

Application of Tabu Search for Optimal Placement and Sizing of Distributed Generation for Loss Reduction

2012 ◽  
Vol 433-440 ◽  
pp. 7190-7194 ◽  
Author(s):  
Nattachote Rugthaicharoencheep ◽  
Thong Lantharthong ◽  
Awiruth Ratreepruk ◽  
Jenwit Ratchatha
Keyword(s):  
Tabu Search ◽  
Distributed Generation ◽  
Distribution System ◽  
Power Loss ◽  
Power Flow ◽  
Search Algorithm ◽  
Optimal Placement ◽  
Loss Reduction ◽  
Placement Problem ◽  
Bus Voltage

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.

scholarly journals Optimal Network Reconfiguration in Active Distribution Networks with Soft Open Points and Distributed Generation

Energies ◽  
2019 ◽  
Vol 12 (21) ◽  
pp. 4172 ◽  
Author(s):  
Ibrahim Diaaeldin ◽  
Shady Abdel Aleem ◽  
Ahmed El-Rafei ◽  
Almoataz Abdelaziz ◽  
Ahmed F. Zobaa
Keyword(s):  
Distributed Generation ◽  
Distribution System ◽  
Distribution Systems ◽  
Search Algorithm ◽  
Distribution Networks ◽  
Mixed Integer ◽  
Network Reconfiguration ◽  
Efficient Manner ◽  
Optimal Network ◽  
Network Losses

In this study, we allocated soft open points (SOPs) and distributed generation (DG) units simultaneously with and without network reconfiguration (NR), and investigate the contribution of SOP losses to the total active losses, as well as the effect of increasing the number of SOPs connected to distribution systems under different loading conditions. A recent meta-heuristic optimization algorithm called the discrete-continuous hyper-spherical search algorithm is used to solve the mixed-integer nonlinear problem of SOPs and DGs allocation, along with new NR methodology to obtain radial configurations in an efficient manner without the possibility of getting trapped in local minima. Further, multi-scenario studies are conducted on an IEEE 33-node balanced benchmark distribution system and an 83-node balanced distribution system from a power company in Taiwan. The contributions of SOP losses to the total active losses, as well as the effect of increasing the number of SOPs connected to the system, are investigated to determine the real benefits gained from their allocation. It was clear from the results obtained that simultaneous NR, SOP, and DG allocation into a distribution system creates a hybrid configuration that merges the benefits offered by radial distribution systems and mitigates drawbacks related to losses, power quality, and voltage violations, while offering a far more efficient and optimal network operation. Also, it was found that the contribution of the internal loss of SOPs to the total loss for different numbers of installed SOPs is not dependent on the number of SOPs and that loss minimization is not always guaranteed by installing more SOPs or DGs along with NR. One of the findings of the paper demonstrates that NR with optimizing tie-lines could reduce active losses considerably. The results obtained also validate, with proper justifications, that SOPs installed for the management of constraints in LV feeders could further reduce losses and efficiently address issues related to voltage violations and network losses.

An Optimal Load Shedding Methodology for Radial Power Distribution Systems to Improve Static Voltage Stability Margin using Gravity Search Algorithm

2014 ◽  
Vol 68 (3) ◽  
Author(s):  
Aziah Khamis ◽  
H. Shareef ◽  
A. Mohamed ◽  
Erdal Bizkevelci
Keyword(s):  
Power Distribution ◽  
Distribution System ◽  
Distribution Systems ◽  
Voltage Stability ◽  
Search Algorithm ◽  
Gravitational Search Algorithm ◽  
Stability Margin ◽  
Maximum Amount ◽  
Load Shedding ◽  
Voltage Stability Margin

Voltage stability is one of the major concerns in operational and planning of modern power system. Many strategies have been implemented to avoid voltage collapse, which the load shedding considered as the last option. However, optimization is needed to estimate the minimum amount to shed so as to prevent voltage instability. In this paper, an effective method is presented for estimating the optimal amount of load to be shed in a distribution system based on the gravitational search algorithm (GSA). The voltage stability margin (VSM) of the system has been considered in the objective function. The optimization problem is formulated to maximize the VSM of the system and at the same time satisfying the operation and security constraints. The optimum solution depends on the predefined constraints such as the number of load buses available to shed and the maximum amount of load permitted to shed. Simulation result conducted on the IEEE 33 bus radial distribution system shows that the system voltage stability can be improved by optimally shedding the loads at critical system buses. The results also indicate that the numbers of load buses available for load shedding does not have a significant impact on voltage stability margin, but it is highly dependent on the maximum amount of load permitted to shed. 

scholarly journals MINIMIZING POWER LOSS BY PLACING DG OPTIMALLY IN DISTRIBUTION SYSTEM BY PSO TECHNIQUE

2021 ◽  
Vol 6 (4) ◽  
Author(s):  
Prakash D B ◽  
Lakshminarayana C
Keyword(s):  
Particle Swarm Optimization ◽  
Objective Function ◽  
Distributed Generation ◽  
Distribution System ◽  
Power Loss ◽  
Distribution Systems ◽  
Active Power ◽  
Optimal Placement ◽  
Swarm Optimization ◽  
Intelligence Technique

— This paper presents optimal placement and sizing of Distributed Generation (DG) by using an intelligence technique called Particle Swarm Optimization (PSO). Here the objective function is considered as minimization of active power loss. The proposed methodology is applied and tested for IEEE 33 and IEEE 69 bus radial distribution systems. The result shows that the proposed algorithm is more effective.

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