scholarly journals OPTIMASI PENENTUAN LOKASI DAN KELUARAN DAYA AKTIF PEMBANGKIT KECIL TERSEBAR METODE ALGORITMA GENETIKA STANDAR PADA PENYULANG 1 SISTEM DISTRIBUSI 20 KV TARAKAN

2018 ◽  
Vol 8 (1) ◽  
pp. 1
Author(s):  
Achmad Budiman
Keyword(s):  
Genetic Algorithm ◽  
Distributed Generation ◽  
Power Output ◽  
Distribution System ◽  
Active Power ◽  
Electrical Distribution ◽  
Genetic Algorithm Method ◽  
Standard Genetic Algorithm

Abstract - The use of distributed generation (DG) at Feeder I Tarakan Distribution System 20 kV aims to meet the needs of consumer electricity, but it is expected to reduce the loss of power on the network. Therefore, optimization is needed in determining the location and output of DG’s active power. The standard genetic algorithm method is used in the determination of the location and output of active power for 3 units of each 250 kW capacity in Feeder I Tarakan Distribution System 20 kV. The optimized results were achieved for optimal locations on 22,28, 47 buses with each 196, 192, 200 kW active power output and 37.73 % or 17,000 Watt network loss. Keywords: standard genetic algorithm, electrical distribution system, distributed generation  Intisari - Pemanfaatan pembangkit kecil tersebar (PKT) pada Penyulang I Sistem Distribusi Listrik Tarakan 20 kV bertujuan untuk pemenuhan kebutuhan listrik konsumen dan diharapkan dapat meminimalkan rugi daya pada jaringan. Untuk itu diperlukan optimasi dalam menentukan lokasi dan keluaran daya aktif PKT. Metode algoritma genetika standar digunakan dalam penentuan lokasi dan keluaran daya aktif untuk 3 Unit PKT kapasitas masing-masing 250 kW pada Penyulang I Sistem Distribusi 20  KV Tarakan. Hasil optimasi yang dicapai untuk lokasi optimal pada bus 22, 28, 47 dengan masing-masing keluaran daya aktif 196, 192, 200 kW dan penurunan rugi daya jaringan sebesar 37,73 % atau 17.000 Watt. Kata Kunci : algoritma genetika standar, sistem distribusi listrik, pembangkit kecil tersebar

Determining the Norton’s Equivalent Model of Distribution System with Distributed Generation (DG) for Stability Analysis

2019 ◽  
Vol 12 (2) ◽  
pp. 190-198
Author(s):  
Sunny Katyara ◽  
Lukasz Staszewski ◽  
Faheem Akhtar Chachar
Keyword(s):  
Distributed Generation ◽  
Normal Condition ◽  
Distribution System ◽  
Distribution Networks ◽  
Equivalent Model ◽  
Stability Factor ◽  
Matlab Simulation ◽  
The Stability ◽  
Stability Issues

Background: Since the distribution networks are passive until Distributed Generation (DG) is not being installed into them, the stability issues occur in the distribution system after the integration of DG. Methods: In order to assure the simplicity during the calculations, many approximations have been proposed for finding the system’s parameters i.e. Voltage, active and reactive powers and load angle, more efficiently and accurately. This research presents an algorithm for finding the Norton’s equivalent model of distribution system with DG, considering from receiving end. Norton’s model of distribution system can be determined either from its complete configuration or through an algorithm using system’s voltage and current profiles. The algorithm involves the determination of derivative of apparent power against the current (dS/dIL) of the system. Results: This work also verifies the accuracy of proposed algorithm according to the relative variations in the phase angle of system’s impedance. This research also considers the varying states of distribution system due to switching in and out of DG and therefore Norton’s model needs to be updated accordingly. Conclusion: The efficacy of the proposed algorithm is verified through MATLAB simulation results under two scenarios, (i) normal condition and (ii) faulty condition. During normal condition, the stability factor near to 1 and change in dS/dIL was near to 0 while during fault condition, the stability factor was higher than 1 and the value of dS/dIL was away from 0.

scholarly journals A Multi-Objective Hybrid Genetic Algorithm for Sizing and Siting of Renewable Distributed Generation

2021 ◽  
Vol 11 (16) ◽  
pp. 7442
Author(s):  
Paulo S. Zanin ◽  
Lina Paola Garcés Negrete ◽  
Gelson A. A. Brigatto ◽  
Jesús M. López-Lezama
Keyword(s):  
Genetic Algorithm ◽  
Distributed Generation ◽  
Distribution System ◽  
Hybrid Genetic Algorithm ◽  
Test System ◽  
Environmental Benefits ◽  
New Paradigm ◽  
Multi Objective ◽  
Multi Objective Genetic Algorithm ◽  
Pareto Sets

Renewable generation has been addressed in several aspects but it still represents a new paradigm for the expansion of the electricity supply. This paper aims to propose a new model for the sizing and siting problem of distributed generation (DG), based on renewable sources and considering three main aspects: technical, from the distribution utility viewpoint; economical, from the DG owner’s viewpoint, and environmental, from a sustainability perspective. A multi-objective Genetic Algorithm and the Maximin metric are implemented to obtain optimal Pareto sets; also, three decision criteria, considering the concept of preference, are applied to select a final solution from Pareto sets. Case-studies are carried out in medium voltage systems: the 69-bus distribution test system, known from literature, and a 918-bus Brazilian distribution system. Diversity of alternatives in the obtained Pareto sets testify algorithm effectiveness in searching for solutions to the distributed generation sizing and siting problem, in order to ensure power loss reductions, investment return, and environmental benefits. The proposed methodology contributes to the discussions and perspectives among electricity utilities, DG owners, society, and regulators regarding planning and decision making tools.

scholarly journals Penentuan Jarak Terpendek Pada Jalur Pengiriman Musae Chips Dengan Menggunakan Algoritma Genetika

2019 ◽  
Vol 6 (1) ◽  
pp. 19-23
Author(s):  
Muhammad Bahrul Arif
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Distribution Channel ◽  
Optimal Solutions ◽  
Distribution Lines ◽  
Good Path ◽  
Crossover Probability ◽  
Study Results ◽  
Genetic Algorithm Method

Combination of good path distribution by land can optimize travel time and costs. However, not all of these path distribution combinations will provide the best solution. The study was conducted to determine the distribution of goods so that the best solution is achieved. To simplify the process of determining the goods distribution channel, it is supported by software development. Genetic algorithms that have reliability in producing optimal solutions can be used to solve this problem. The application of the genetic algorithm method is applied in software. In the software that is built, there are several inputs needed, namely: cities destination distribution as the initial chromosome number, number of generations, crossover probability and probability of mutation. The result of processing is a combination of goods distribution lines to be taken which represent the solution to this problem. Only the best chromosomes will be given as a result. Through the software that was built, the determination of goods distribution lines is expected to be better and can optimize the time and cost of travel. Based on the research, 5 road combinations are used as chip distribution routes used for testing. This study results from the first fitness gene get the highest fitness 7.4, fitness lowest 5.6 and the second gene get the highest fitness 9.3, fitness lowest 5.6.

scholarly journals Optimal sizing and location of multiple distributed generation for power loss minimization using genetic algorithm

2019 ◽  
Vol 16 (2) ◽  
pp. 956
Author(s):  
Abdulhamid Musa ◽  
Tengku Juhana Tengku Hashim
Keyword(s):  
Genetic Algorithm ◽  
Distributed Generation ◽  
Distribution System ◽  
Power Loss ◽  
Total Power ◽  
Power Losses ◽  
Loss Minimization ◽  
Power Constraints ◽  
Voltage Deviation ◽  
Power Limits

This paper presents a Genetic Algorithm (GA) for optimal location and sizing of multiple distributed generation (DG) for loss minimization. The study is implemented on a 33-bus radial distribution system to optimally allocate different numbers of DGs through the minimization of total active power losses and voltage deviation at power constraints of 0 – 2 MW and 0 – 3 MW respectively. The study proposed a PQ model of DG and Direct Load Flow (DLF) technique that uses Bus Incidence to Branch current (BIBC) and Branch Current to Bus Voltage (BCBV) matrices. The result obtained a minimum base case voltage level of 0.9898 p.u at bus 18 with variations of voltage improvements at other buses after single and multiple DG allocations in the system. Besides, the total power loss before DG allocation is observed as 0.2243 MW, and total power loss after DG allocation was determined based on the power constraints. Various optimal locations were seen depending on the power limits of different DG sizes. The results have shown that the impact of optimal allocation and sizing of three DG is more advantageous concerning voltage improvement, reduction of the voltage deviation and also total power loss in the distribution system. The results obtained in the 0 – 2 MW power limit is consistent to the 0 – 3 MW power limits regarding the influence of allocating DG to the network and minimization of total power losses.

scholarly journals DG integration to distribution system with active power injection control

2020 ◽  
Vol 11 (2) ◽  
pp. 692
Author(s):  
P. V. V Satyanarayana ◽  
P. V. Ramana Rao
Keyword(s):  
Distributed Generation ◽  
Distribution System ◽  
Electrical Power ◽  
Active Power ◽  
Control Technique ◽  
Integration Scheme ◽  
Electrical Power System ◽  
Grid Simulation ◽  
Power Injection ◽  
Injection Control

Conventional methodology for electrical power generation is vulnerable due to environmental limitations and the availability of fuel. Distributed generation, offering virtuous benefits to the market partakers, is trending in electrical power system in modern era. This paper presents the distributed generation integration to grid with active power injection control. Distributed generation source delivers DC power which is processed through square wave inverter. Inverter circuit is controlled using a simple control technique to match grid code. Fixing the current reference and varying the same, analysis is carried out for grid integration scheme of distributed generation injecting active power to grid. Simulation work is carried out and results are shown using MATLAB/SIMULINK software.

scholarly journals Power Loss Minimization and Voltage Stability Improvement in Electrical Distribution System via Network Reconfiguration and Distributed Generation Placement Using Novel Adaptive Shuffled Frogs Leaping Algorithm

Energies ◽  
2019 ◽  
Vol 12 (3) ◽  
pp. 553 ◽  
Author(s):  
Arun Onlam ◽  
Daranpob Yodphet ◽  
Rongrit Chatthaworn ◽  
Chayada Surawanitkun ◽  
Apirat Siritaratiwat ◽  
...  
Keyword(s):  
Distributed Generation ◽  
Distribution System ◽  
Power Loss ◽  
Distribution Systems ◽  
Voltage Stability ◽  
Network Reconfiguration ◽  
Loss Minimization ◽  
Power Loss Minimization ◽  
Electrical Distribution ◽  
Power Loss Reduction

This paper proposes a novel adaptive optimization algorithm to solve the network reconfiguration and distributed generation (DG) placement problems with objective functions including power loss minimization and voltage stability index (VSI) improvement. The proposed technique called Adaptive Shuffled Frogs Leaping Algorithm (ASFLA) was performed for solving network reconfiguration and DG installation in IEEE 33- and 69-bus distribution systems with seven different scenarios. The performance of ASFLA was compared to that of other algorithms such as Fireworks Algorithm (FWA), Adaptive Cuckoo Search Algorithm (ACSA) and Shuffled Frogs Leaping Algorithm (SFLA). It was found that the power loss and VSI provided by ASFLA were better than those given by FWA, ACSA and SFLA in both 33- and 69-bus systems. The best solution of power loss reduction and VSI improvement of both 33- and 69-bus systems was achieved when the network reconfiguration with optimal sizing and the location DG were simultaneously implemented. From our analysis, it was indicated that the ASFLA could provide better solutions than other methods since the generating process, local and global searching of this algorithm were significantly improved from a conventional method. Hence, the ASFLA becomes another effective algorithm for solving network reconfiguration and DG placement problems in electrical distribution systems.

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