Optimal Power Flow Through Hybrid Power System Using Metaheuristic Hybrid Algorithm

被引:0
|
作者
Kumar, Naveen [1 ]
Kumar, Ramesh [1 ]
机构
[1] Natl Inst Technol, Dept Elect Engn, Patna 800005, Bihar, India
关键词
Greenhouse gases; solar photovoltaic plant; windfarm; hybrid power system; environment; cost; emission; renewable energy sources; OPTIMIZATION;
D O I
10.3233/AJW220077
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The growing population and modernisation in life styles of people increase the demand of electrical power. This has led to pressure on conventional thermal power plants to increase the production of electrical energy by using more and more fossil fuels like coal, petrol, diesel and natural gases, which enhance the emission of greenhouse gases causing environmental pollution. Hence, renewable sources of energy attract the attention of researchers as these can reduce the cost of production, and carbon emissions and has high efficiency. In this study, an IEEE 30- bus hybrid power test system consisting of thermal generators, wind generators and solar photo voltaic have been considered to achieve economically, environmentally as well as physically stable systems. The adopted hybrid power system follows a highly non-linear and complex nature, hence a novel hybrid algorithm named SHADE-SSA is framed to find optimal solutions economically and environmentally with stable voltage deviation and low power loss. The performance of the SHADE-SSA algorithm is compared with the SHADE-SF algorithm and SSA, to confirm the superiority in solving complex, non-linear hybrid power system problems.
引用
收藏
页码:103 / 112
页数:10
相关论文
共 50 条
  • [1] Optimal power flow approaches for a hybrid system using metaheuristic techniques: a comprehensive review
    Saini A.
    Rahi O.P.
    International Journal of Ambient Energy, 2024, 45 (01)
  • [2] Probabilistic Optimal Power Flow Solution Using a Novel Hybrid Metaheuristic and Machine Learning Algorithm
    Shaheen, Mohamed A. M.
    Hasanien, Hany M.
    Mekhamer, Said F.
    Qais, Mohammed H.
    Alghuwainem, Saad
    Ullah, Zia
    Tostado-Veliz, Marcos
    Turky, Rania A.
    Jurado, Francisco
    Elkadeem, Mohamed R.
    MATHEMATICS, 2022, 10 (17)
  • [3] Optimal Power Flow Using Hybrid PSOGSA Algorithm
    Radosavljevic, Jordan
    Arsic, Nebojsa
    Jevtic, Miroljub
    2014 55TH INTERNATIONAL SCIENTIFIC CONFERENCE ON POWER AND ELECTRICAL ENGINEERING OF RIGA TECHNICAL UNIVERSITY (RTUCON), 2014, : 136 - 140
  • [4] Optimal location and sizing of UPFC for optimal power flow in a deregulated power system using a hybrid algorithm
    Sita, Hareesh
    Reddy, P. Umapathi
    Kiranmayi, R.
    INTERNATIONAL JOURNAL OF AMBIENT ENERGY, 2020, 43 (01) : 1413 - 1419
  • [5] Power system dynamic optimal power flow with hybrid immune genetic algorithm
    Liu, Fang
    Chung, ChiYung
    Wong, KitPot
    Yan, Wei
    Xu, GuoYu
    DYNAMICS OF CONTINUOUS DISCRETE AND IMPULSIVE SYSTEMS-SERIES B-APPLICATIONS & ALGORITHMS, 2007, 14 : 255 - 261
  • [6] Multiobjective optimal power flow using hybrid evolutionary Algorithm
    Alawode Kehinde, O.
    Jubril Abimbola, M.
    Komolafe Olusola, A.
    World Academy of Science, Engineering and Technology, 2009, 39 : 790 - 795
  • [7] Optimal sizing of hybrid power system using genetic algorithm
    Shahirinia, A. H.
    Tafreshi, S. M. M.
    Gastaj, A. Hajizadeh
    Moghaddamjoo, A. R.
    2005 International Conference on Future Power Systems (FPS), 2005, : 672 - 677
  • [8] Optimal Power Flow for Transmission Power Networks Using a Novel Metaheuristic Algorithm
    Li, Zelan
    Cao, Yijia
    Le Van Dai
    Yang, Xiaoliang
    Thang Trung Nguyen
    ENERGIES, 2019, 12 (22)
  • [9] Optimal power flow based on hybrid genetic algorithm
    Younes, M.
    Rahli, M.
    Abdelhakem-Koridak, L.
    JOURNAL OF INFORMATION SCIENCE AND ENGINEERING, 2007, 23 (06) : 1801 - 1816
  • [10] Optimal AGC Design for a Hybrid Power System Using Hybrid Bacteria Foraging Optimization Algorithm
    Panwar, Akhilesh
    Sharma, Gulshan
    Bansal, Ramesh C.
    ELECTRIC POWER COMPONENTS AND SYSTEMS, 2019, 47 (11-12) : 955 - 965