scholarly journals Optimal placement and sizing of distributed generation for loss minimization using ABC optimization

2021 ◽  
Vol 10 (4) ◽  
pp. 347
Author(s):  
Madhu Valavala
Keyword(s):  
Distributed Generation ◽  
Public Services ◽  
Optimal Allocation ◽  
Probabilistic Approach ◽  
Optimal Placement ◽  
Voltage Profile ◽  
High Loss ◽  
Bee Colony ◽  
Delivery Reliability ◽  
Stochastic Optimization Algorithm

The distributed generation (DG) refers to the use of the nearby units of small generation or in the sleefelzentres. Revisions have shown that unfitting choice of the position and scope of the DG can lead to bigger system sufferers than DG's sufferers. Public services are already available before the high loss of energy loss and of the mediocre voltage profile, in particular developing countries cannot tolerate any increase in losses. From optimal allocation, public services in the reduction of system losses improve tension adjustment and improve delivery reliability. This article aims to minimalize the annual system's annual loss through the appropriate positioning and size of the DG units. The artificials bee colony (ABC) of EPA are inspired by the behavior of the API feeding, this method is incredibly conventional, a stroke or a peoplated stochastic optimization algorithm to meet the solution of the specified problem. At MATLAB, a probabilistic approach is simulated to reach the target indicates that the size of the DGs to be installed to reduce almost the same loss as a percentage that the situation in which the load power is considered constant.

scholarly journals Simultaneous Distribution Network Reconfiguration and Optimal Placement of Distributed Generation

2019 ◽  
Vol 1 (1) ◽  
Author(s):  
Abdullahi Bala Kunya ◽  
Gaddafi Sani Shehu ◽  
Usman Muhammad Hassan ◽  
Abdurrahman Umar Lawal
Keyword(s):  
Distributed Generation ◽  
Power Loss ◽  
Optimal Allocation ◽  
Optimization Problems ◽  
Distribution Networks ◽  
Optimal Placement ◽  
Voltage Profile ◽  
Combinatorial Optimization Problems ◽  
Power Loss Reduction ◽  
Real Coded Genetic Algorithm

A reliable, eco- and nature-friendly operation has been the major concern of modern power system (PS). To improve the PS reliability and reduce the adverse environmental effect of conventional thermal generation facilities, renewable energy based distributed generation (RDG) are being enormously integrated to low and medium voltage distribution networks (DN). However, if these systems are not properly deployed, the reliability and stability of the PS will be endangered and its quality can be dreadfully jeopardized. Among the measures taken to avoid such is optimizing the location and size of each RDG unit in the DNs. These networks are generally operated in a radial configuration, though they can be reconfigured to other topologies to achieve certain objectives. Both RDG placement/sizing and DN reconfiguration are highly non-linear, multi-objective, constrained and combinatorial optimization problems. In this study, a hybrid of Particle Swarm Optimization (PSO) and real-coded Genetic Algorithm (GA) techniques is employed for DN reconfiguration and optimal allocation (size and location) of multiple RDG units in primary DNs simultaneously. The objectives of the proposed technique are active power loss reduction, voltage profile (VP) and feeder load balancing (LB) improvement. It is carried out subject to some technical constraints, with the search space being the set of DN branches, DG sizes and potential locations.  To ascertain the effectiveness of the technique, it is implemented on standard IEEE 16-bus, 33-bus and 69-bus test DNs. The proposed algorithm is implemented in MATLAB and MATPOWER environments. It is observed the power loss, voltage deviation and LB are found to be reduced by 32.84%, 12.33% and 24.03% of their respective inherent values in the biggest system when the system is reconfigured only. With the optimized RDGs placed in the reconfigured systems, a further reductions of 46.27%, 25.92% and 36.65% are observed respectively.  

scholarly journals Optimal distributed generation in green building assessment towards line loss reduction for Malaysian public hospital

2019 ◽  
Vol 8 (4) ◽  
Author(s):  
Mohd Effendi Amran ◽  
Mohd Nabil Muhtazaruddin ◽  
Nurul Aini Bani ◽  
Hazilah Mad Kaidi ◽  
Mohamad Zaki Hassan ◽  
...  
Keyword(s):  
Distributed Generation ◽  
Public Hospital ◽  
Green Building ◽  
Energy Performance ◽  
Optimization Approach ◽  
Loss Reduction ◽  
Voltage Profile ◽  
Bee Colony ◽  
Line Loss ◽  
Current Setting

This paper presents an optimization approach for criteria setting of Renewable Distributed Generation (DG) in the Green Building Rating System (GBRS). In this study, the total line loss reduction is analyzed and set as the main objective function in the optimization process which then a reassessment of existing criteria setting for renewable energy (RE) is proposed towards lower loss outcome. Solar photovoltaic (PV)-type DG unit (PV-DG) is identified as the type of DG used in this paper. The proposed PV-DG optimization will improve the sustainable energy performance of the green building by total line losses reduction within accepted lower losses region using Artificial bee colony (ABC) algorithm. The distribution network uses bus and line data setup from selected one of each three levels of Malaysian public hospital. MATLAB simulation result shows that the PV-DG expanding capacity towards optimal scale and location provides a better outcome in minimizing total line losses within an appropriate voltage profile as compared to the current setting of PV-DG imposed in selected GBRS. Thus, reassessment of RE parameter setting and the proposed five rankings with new PV-DG setting for public hospital provides technical justification and give the best option to the green building developer for more effective RE integration.

scholarly journals Voltage Control and Power Loss Reduction in Distribution Networks using Distributed Generation

2019 ◽  
Vol 8 (12) ◽  
pp. 2863-2867
Keyword(s):  
Distributed Generation ◽  
Optimization Algorithm ◽  
Power Loss ◽  
Optimal Allocation ◽  
Distribution Networks ◽  
Voltage Profile ◽  
Vector Method ◽  
Index Vector ◽  
Power Loss Reduction ◽  
Whale Optimization

Distributed generation (DG) units can provide many benefits when they are incorporated along the distribution network/system. These benefits are more if DG units are connected at suitable nodes with appropriate rating otherwise, they may cause to increased power loss and poor voltage profile. In this work, optimal allocation (both location and size) problem is solved by considering power loss minimization as an objective function. An analytical method “index vector method (IVM)” is applied to find DG location. A new optimization algorithm “Whale Optimization Algorithm (WOA)” is employed to determine the DG rating. Two popularly known test systems “IEEE 33 & IEEE 69”bus systems are used to evaluate the efficacy of IVM and WOA.

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

2019 ◽  
Vol 8 (4) ◽  
pp. 6357-6363
Keyword(s):  
Distributed Generation ◽  
Distribution System ◽  
Power Loss ◽  
Distribution Network ◽  
Optimal Placement ◽  
Small Scale ◽  
Voltage Profile ◽  
Distribution Grid ◽  
Step Size ◽  
System Power

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.

scholarly journals Multi-Criteria Optimal Sizing and Allocation of Renewable and Non-Renewable Distributed Generation Resources at 63 kV/20 kV Substations

Energies ◽  
2020 ◽  
Vol 13 (20) ◽  
pp. 5364
Author(s):  
Seyed Siavash Karimi Madahi ◽  
Andrija T. Sarić
Keyword(s):  
Objective Function ◽  
Distributed Generation ◽  
Gas Turbines ◽  
Optimal Allocation ◽  
Short Circuit ◽  
Mathematical Formulation ◽  
Economic Factors ◽  
Voltage Profile ◽  
Optimal Sizing ◽  
Technical Parameters

The optimal allocation and sizing of distributed generation (DG) resources are important in installing these resources, to improve the technical parameters of the network, including the power losses, voltage profile, and short-circuit level, as well as to increase economic factors. In this paper, a new multi-criteria algorithm and objective function are proposed for the optimal sizing and allocation of renewable and non-renewable DG resources simultaneously. The proposed algorithm is implemented on 63/20 kV substations at 20 kV levels. In the proposed objective function, all important technical and economic factors as well as important constraints, such as penetration level of DGs and budget constraint, are considered in a way that all factors are assigned to monetary values. Moreover, a new mathematical formulation is introduced for the allocation of renewable DG resources to reduce run-time optimization. The genetic algorithm (GA) is employed in the proposed algorithm to minimize the objective function. For renewable DG resources, photovoltaic panels and wind turbines, and for non-renewable DG resources, gas turbines are considered. The 115 buses network of Bakhtar Regional Electric Company (BREC) in Iran is used to evaluate the performance of the proposed algorithm. The results demonstrate that the proposed algorithm improves technical factors efficiently and maximizes the profitability of the investment.

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