Minimizing Power Losses for Distributed Generation (DG) Placements by Considering Voltage Profiles on Distribution Lines for Different Loads Using Genetic Algorithm Methods

被引:5
|
作者
Siregar, Ramdhan Halid [1 ,2 ]
Away, Yuwaldi [1 ,2 ]
Tarmizi [1 ,2 ]
Akhyar [1 ,3 ]
机构
[1] Univ Syiah Kuala, Doctoral Sch Engn Sci, Banda Aceh 23111, Indonesia
[2] Univ Syiah Kuala, Dept Elect & Comp Engn, Banda Aceh 23111, Indonesia
[3] Univ Syiah Kuala, Dept Mech Engn, Jl Syech Abdurrauf 7 Darussalam, Banda Aceh 23111, Indonesia
关键词
distributed generation; genetic algorithms; minimization of losses; voltage profile; load variation; PARTICLE SWARM OPTIMIZATION; DISTRIBUTION-SYSTEM; DISTRIBUTION NETWORKS; UNITS; RECONFIGURATION; STABILITY; LOCATION; SAG;
D O I
10.3390/en16145388
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
The need for electrical energy is increasing in line with the increase in population and increasing progress in welfare. On the other hand, the availability of fossil fuels as the main fuel in generating electricity is dwindling; so, there is a need for policies that require the use of environmentally friendly renewable energy. The utilization of renewable energy does not necessarily apply freely due to several constraints. One effort is a generator or distributed generation (DG) which is placed in the distribution line close to the load. The utilization of DG must go through planning, especially the large capacity and position on the bus and on the feeder, which will result in small network losses and a voltage profile that meets tolerance limits. Thus, the purpose of this study is to optimize to obtain the capacity and location of the DG calculated by considering the variation in the load through the genetic algorithm method. As a result, the optimal DG position for normal load is obtained on bus 18, bus 20, and bus 32 with capacities of 190 kW, 463 kW, and 370 kW, respectively. The losses obtained decreased from 54.6733 kW to 9.9447 kW, and the voltage profile was maintained within the specified limits. Optimization was carried out for decreasing and increasing loads in percent. The result is that losses can be minimized, and the voltage profile remains within the required limits. The lower the load, the more stable the voltage and the smaller the losses; meanwhile, the larger the load, the more fluctuating the voltage is, but still within the limits specified in the optimization.
引用
收藏
页数:25
相关论文
共 28 条
  • [21] Multi-objective reconfiguration of restructured distribution network considering Energy Supply Cost and Power Losses using Micro Genetic Algorithm
    Karegar, H. Kazemi
    Nabaei, V.
    Jalilzadeh, S.
    Iranian Journal of Electrical and Computer Engineering, 2009, 8 (02): : 89 - 96
  • [22] Optimal Placement and Sizing of Distributed Generation Using Wale Optimization Algorithm Considering Voltage Stability and Voltage Profile Improvement, Power Loss and Investment Cost Reducing
    Yahyazadeh, Meisam
    Rezaeeye, Hojat
    IRANIAN JOURNAL OF SCIENCE AND TECHNOLOGY-TRANSACTIONS OF ELECTRICAL ENGINEERING, 2020, 44 (01) : 227 - 236
  • [23] Optimal Placement and Sizing of Distributed Generation Using Wale Optimization Algorithm Considering Voltage Stability and Voltage Profile Improvement, Power Loss and Investment Cost Reducing
    Meisam Yahyazadeh
    Hojat Rezaeeye
    Iranian Journal of Science and Technology, Transactions of Electrical Engineering, 2020, 44 : 227 - 236
  • [24] Stability analysis and voltage improvement in DG-integrated distribution networks using VCPI-based critical buses and lines detection considering uncertain power factor
    Qazi, Hasan Saeed
    Ullah, Zia
    Alferidi, Ahmad
    Alsolami, Mohammed
    Lami, Badr
    Akber, Syed Muhammad Abrar
    AIN SHAMS ENGINEERING JOURNAL, 2024, 15 (12)
  • [25] Technico-economic optimization of Distributed Generation (DG) and Static Var Compensator (SVC) positioning in a real radial distribution network using the NSGA-II genetic algorithm
    Arouna, Oloulade
    Adolphe, Moukengue Imano
    Robert, Adekambi O.
    Kenneth, Amoussou Zinsou
    Antoine, Vianou
    Ramanou, Badarou
    Herman, Tamadaho
    Celestin, Dangbedji
    2019 IEEE PES/IAS POWERAFRICA, 2019, : 42 - +
  • [26] Impact of integrating type-1 distributed generation on distribution network using modified genetic algorithm and voltage stability index: a technical and cost–benefit analysis approach
    Olakunle Elijah Olabode
    Daniel Oluwaseun Akinyele
    Titus Oluwasuji Ajewole
    Samuel Okeolu Omogoye
    Akeem Abimbola Raji
    Journal of Engineering and Applied Science, 2024, 71 (1):
  • [27] 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
    Onlam, Arun
    Yodphet, Daranpob
    Chatthaworn, Rongrit
    Surawanitkun, Chayada
    Siritaratiwat, Apirat
    Khunkitti, Pirat
    ENERGIES, 2019, 12 (03)
  • [28] Ubicación de generación distribuida para minimización de pérdidas usando un algoritmo genético híbrido location of distributed generation for power losses reduction using a hybrid genetic algorithm
    Narváez, Pablo A.
    López-Lezama, Jesús M.
    Velilla, Esteban
    Informacion Tecnologica, 2015, 26 (03): : 123 - 131