scholarly journals Optimal Location, Sizing, and Appropriate Technology Selection of Distributed Generators for Minimizing Power Loss Using Genetic Algorithm

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
T. R. Ayodele ◽  
A. S. O. Ogunjuyigbe ◽  
O. O. Akinola
Keyword(s):  
Genetic Algorithm ◽  
Power Loss ◽  
Optimal Operation ◽  
Optimal Location ◽  
Appropriate Technology ◽  
Technology Selection ◽  
Synchronous Generators ◽  
Distributed Generator ◽  
Induction Generators ◽  
Distributed Generators

Genetic algorithm (GA) is utilized to select most suitable Distributed Generator (DG) technology for optimal operation of power system as well as determine the optimal location and size of the DG to minimize power loss on the network. Three classes of DG technologies, synchronous generators, asynchronous generators, and induction generators, are considered and included as part of the variables for the optimization problem. IEEE 14-bus network is used to test the applicability of the algorithm. The result reveals that the developed algorithm is able to successfully select the most suitable DG technology and optimally size and place the DGs to minimize power loss in the network. Furthermore, optimum multiple placement of DG is considered to see the possible impact on power loss in the network. The result reveals that multiple placements can further reduce the power loss in the network.

Investigating the Impact of Distributed Generators Power Factor to Simultaneous Optimization Analysis

2015 ◽  
Vol 785 ◽  
pp. 253-257
Author(s):  
Jasrul Jamani Jamian ◽  
M.W. Mustafa ◽  
Mohd Noor Abdullah
Keyword(s):  
Power Factor ◽  
Power Loss ◽  
Simultaneous Optimization ◽  
Loss Reduction ◽  
Optimization Analysis ◽  
Swarm Optimization ◽  
Distributed Generator ◽  
Distributed Generators ◽  
Power Loss Reduction ◽  
The Impact

This paper discusses the optimal Distributed Generator (DG) coordination using the Particle Swarm Optimization (PSO) technique where the DG output and location are determined simultaneously. Furthermore, this study analyzes both single DG and multiple DGs configurations. The influence of DG Power Factor (PF) to the optimal DG placement and the DG output are investigated by varying the DG PF values. Specifically, the PF were configured to five values, which are 0.8, 0.85, 0.9, 0.95 and 1.0. From the results, the optimal DG placements are similar, regardless of the PF condition. For example, in the single DG unit experiment, the optimal DG location is at bus 6 whilst in the triple DG units test, the optimal locations are at busses 14, 24, and 30. In contrast, the value of PF significantly influences the optimal DG output and power loss reduction. This study concludes that the design with three DGs where their PFs are configured to 0.8 has the least power loss.

scholarly journals Optimal Location and Sizing of Distributed Generators in DC Networks Using a Hybrid Method Based on Parallel PBIL and PSO

Electronics ◽  
2020 ◽  
Vol 9 (11) ◽  
pp. 1808
Author(s):  
Luis Fernando Grisales-Noreña ◽  
Oscar Danilo Montoya ◽  
Carlos Andrés Ramos-Paja ◽  
Quetzalcoatl Hernandez-Escobedo ◽  
Alberto-Jesus Perea-Moreno
Keyword(s):  
Distributed Generation ◽  
Power Loss ◽  
Hybrid Methods ◽  
Population Based ◽  
Optimal Location ◽  
Swarm Optimization ◽  
Distributed Generators ◽  
Parallel Version ◽  
Location Methods ◽  
Hybrid Methodology

This paper addresses the problem of the locating and sizing of distributed generators (DGs) in direct current (DC) grids and proposes a hybrid methodology based on a parallel version of the Population-Based Incremental Learning (PPBIL) algorithm and the Particle Swarm Optimization (PSO) method. The objective function of the method is based on the reduction of the power loss by using a master-slave structure and the consideration of the set of restrictions associated with DC grids in a distributed generation environment. In such a structure, the master stage (PPBIL) finds the location of the generators and the slave stage (PSO) finds the corresponding sizes. For the purpose of comparison, eight additional hybrid methods were formed by using two additional location methods and two additional sizing methods, and this helped in the evaluation of the effectiveness of the proposed solution. Such an evaluation is illustrated with the electrical test systems composed of 10, 21 and 69 buses and simulated on the software, MATLAB. Finally, the results of the simulation demonstrated that the PPBIL–PSO method obtains the best balance between the reduction of power loss and the processing time.

scholarly journals Supervised evolutionary programming based technique for multi-DG installation in distribution system

2020 ◽  
Vol 9 (1) ◽  
pp. 11
Author(s):  
Muhammad Firdaus Shaari ◽  
Ismail Musirin ◽  
Muhamad Faliq Mohamad Nazer ◽  
Shahrizal Jelani ◽  
Farah Adilah Jamaludin ◽  
...  
Keyword(s):  
Distribution System ◽  
Power Loss ◽  
Distribution Systems ◽  
Optimization Technique ◽  
Evolutionary Programming ◽  
Optimal Location ◽  
Programming Method ◽  
Network System ◽  
Distributed Generators ◽  
System Power

<span lang="EN-US">Installing DG in network system, has supported the distribution system to provide the increasing number of consumer demand and load, in order to achieve that this paper presents an efficient and fast converging optimization technique based on a modification of traditional evolutionary programming method for obtain the finest optimal location and power loss in distribution systems. The proposed algorithm that is supervised evolutionary programming is implemented in MATLAB and apply on the 69-bus feeder system in order to minimize the system power loss and obtaining the best optimal location of the distributed generators. </span>

scholarly journals Optimal Location and Size of Distributed Generators in an Electric Distribution System based on a Novel Metaheuristic Algorithm

2020 ◽  
Vol 10 (1) ◽  
pp. 5325-5329 ◽  
Author(s):  
T. N. Ton ◽  
T. T. Nguyen ◽  
A. V. Truong ◽  
T. P. Vu
Keyword(s):  
Distribution System ◽  
Power Loss ◽  
Optimal Location ◽  
Metaheuristic Algorithm ◽  
Loss Reduction ◽  
Control Parameters ◽  
Electric Distribution System ◽  
Distributed Generators ◽  
Power Loss Reduction ◽  
Electric Distribution

This paper proposes a method for optimizing the location and size of Distributed Generators (DGs) based on the Coyote Algorithm (COA), in order to minimize the power loss in an Electric Distribution System (EDS). Compared to other algorithms, COA does not need control parameters during its execution. The effectiveness of COA was evaluated in an EDS with 33 nodes for two scenarios: the optimization of location and capacity of DGs in an initial radial configuration, and the best radial configuration for power loss reduction. Results were compared with other methods, showing that the proposed COA is a reliable tool for optimizing the location and size of DGs in an EDS.

DG Planning with Amalgamation of Operational and Reliability Considerations

2016 ◽  
Vol 17 (2) ◽  
pp. 131-141 ◽  
Author(s):  
Neelakanteshwar Rao Battu ◽  
A. R. Abhyankar ◽  
Nilanjan Senroy
Keyword(s):  
Distributed Generation ◽  
Radial Distribution ◽  
Distribution System ◽  
Power Loss ◽  
Distribution Systems ◽  
Vital Role ◽  
Radial Distribution System ◽  
Real Power ◽  
Distributed Generator ◽  
Distributed Generators

Abstract Distributed Generation has been playing a vital role in dealing issues related to distribution systems. This paper presents an approach which provides policy maker with a set of solutions for DG placement to optimize reliability and real power loss of the system. Optimal location of a Distributed Generator is evaluated based on performance indices derived for reliability index and real power loss. The proposed approach is applied on a 15-bus radial distribution system and a 18-bus radial distribution system with conventional and wind distributed generators individually.

scholarly journals A Novel Method on Hydrographic Survey Technology Selection Based on the Decision Tree Supervised Learning

2021 ◽  
Vol 11 (11) ◽  
pp. 4966
Author(s):  
Ivana Golub Medvešek ◽  
Igor Vujović ◽  
Joško Šoda ◽  
Maja Krčum
Keyword(s):  
Decision Tree ◽  
Supervised Learning ◽  
Autonomous Underwater Vehicle ◽  
Specific Area ◽  
Underwater Vehicle ◽  
Appropriate Technology ◽  
Technology Selection ◽  
Hydrographic Survey ◽  
Seabed Mapping ◽  
Novel Method

Hydrographic survey or seabed mapping plays an important role in achieving better maritime safety, especially in coastal waters. Due to advances in survey technologies, it becomes important to choose well-suited technology for a specific area. Moreover, various technologies have various ranges of equipment and manufacturers, as well as characteristics. Therefore, in this paper, a novel method of a hydrographic survey, i.e., identifying the appropriate technology, has been developed. The method is based on a reduced elimination matrix, decision tree supervised learning, and multicriteria decision methods. The available technologies were: remotely operated underwater vehicle (ROV), unmanned aerial vehicle (UAV), light detection and ranging (LIDAR), autonomous underwater vehicle (AUV), satellite-derived bathymetry (SDB), and multibeam echosounder (MBES), and they are applied as a case study of Kaštela Bay. Results show, considering the specifics of the survey area, that UAV is the best-suited technology to be used for a hydrographic survey. However, some other technologies, such as SDB come close and can be considered an alternative for hydrographic surveys.

Operation Characteristics of Zone 3 Distance Protection in Wind Power Systems with Fixed-Speed Induction Generators

2011 ◽  
Vol 12 (4) ◽  
Author(s):  
Shenghu Li
Keyword(s):  
Power Systems ◽  
Wind Power ◽  
Reactive Power ◽  
Flow Analysis ◽  
Load Flow ◽  
Synchronous Generators ◽  
Induction Generators ◽  
Load Flow Analysis ◽  
Wind Power Systems ◽  
Operation Characteristics

The induction generators (IGs) are basic to wind energy conversion. They produce the active power and consume the reactive power, with the voltage characteristics fragile compared with that of the synchronous generators and doubly-fed IGs. In the stressed system states, they may intensify var imbalance, yielding undesirable operation of zone 3 impedance relays.In this paper, the operation characteristics of the zone 3 relays in the wind power systems is studied. With the theoretical and load flow analysis, it is proved that the equivalent impedance of the IGs lies in the 2nd quadrature, possibly seen as the backward faults by the mho relays, i.e. the apparent impedance enters into the protection region from the left side. The undesirable operation may be caused by more wind power, larger load, less var compensation, and larger torque angle.

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