Optimal design of a grid-connected desalination plant powered by renewable energy resources using a hybrid PSO-GWO approach

被引:182
作者
Abdelshafy, Alaaeldin M. [1 ,2 ]
Hassan, Hamdy [1 ,3 ]
Jurasz, Jakub [4 ]
机构
[1] Egypt Japan Univ Sci & Technol, Energy Resources Engn Dept, Alexandria, Egypt
[2] Assiut Univ, Elect Engn Dept, Fac Engn, Assiut, Egypt
[3] Assiut Univ, Mech Engn Dept, Fac Engn, Assiut, Egypt
[4] AGH Univ Sci & Technol, Fac Management, Dept Engn Management, Krakow, Poland
关键词
Optimization; PSO; GWO; Desalination; Renewable energy; Grid; GREY WOLF OPTIMIZER; GENETIC ALGORITHM; SYSTEM; SOLAR; BATTERY; METHODOLOGY; COST;
D O I
10.1016/j.enconman.2018.07.083
中图分类号
O414.1 [热力学];
学科分类号
摘要
This paper presents a grid-connected hybrid renewable energy integrated with a reverse osmosis desalination plant to provide fresh water for a residential community. The hybrid energy system comprises a photovoltaic module and wind turbine as the main source of energy, and battery storage systems or hydrogen storage systems are used as an energy storage system, while a diesel generator is used as a backup energy source. A new multiobjective hybrid Particle Swarm Optimization - Grey Wolf Optimizer (PSO-GWO) optimization method is used to obtain the optimal size of the different system components to minimize both the total cost of fresh water production and, at the same time, CO2 emissions, for a period of 20 years. Moreover, a comparison is done between the PSO-GWO optimization method and the use of PSO alone and the use of GWO alone. The solar radiation, temperature and wind speed of the residential community are measured using the weather station system. A comparison between different hybrid system configurations using three different optimization methods is presented. The complete model for energy management strategies and the optimization models for this study are programmed using MATLAB software. The results show that the proposed PSO-GWO hybrid performs better at determining the optimization parameters than either of the same optimization methods used in isolation. The optimization results indicate that a battery storage system is more economical than a hydrogen storage system. Further reduction in cost can be achieved by incorporating a diesel generator into the hybrid system. Finally, sensitivity analyses are performed to show how varying certain parameters affects total investment cost. Such analyses have shown that the variation in annual solar irradiance has a greater impact on the total investment cost than wind speed variation.
引用
收藏
页码:331 / 347
页数:17
相关论文
共 36 条
[1]   A review on recent size optimization methodologies for standalone solar and wind hybrid renewable energy system [J].
Al-Falahi, Monaaf D. A. ;
Jayasinghe, S. D. G. ;
Enshaei, H. .
ENERGY CONVERSION AND MANAGEMENT, 2017, 143 :252-274
[2]   Optimization of a combined solar chimney for desalination and power generation [J].
Asayesh, Mohammad ;
Kasaeian, Alibakhsh ;
Ataei, Abtin .
ENERGY CONVERSION AND MANAGEMENT, 2017, 150 :72-80
[3]  
Bilal BO, 2015, Int J Phys Sci, V10, P192, DOI [10.5897/ijps2014.4251, DOI 10.5897/IJPS2014.4251]
[4]   Optimization of micro-grid system using MOPSO [J].
Borhanazad, Hanieh ;
Mekhilef, Saad ;
Ganapathy, Velappa Gounder ;
Modiri-Delshad, Mostafa ;
Mirtaheri, Ali .
RENEWABLE ENERGY, 2014, 71 :295-306
[5]  
Coello CAC, 2002, IEEE C EVOL COMPUTAT, P1051, DOI 10.1109/CEC.2002.1004388
[6]   A fast and elitist multiobjective genetic algorithm: NSGA-II [J].
Deb, K ;
Pratap, A ;
Agarwal, S ;
Meyarivan, T .
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, 2002, 6 (02) :182-197
[7]   A methodology or optimal sizing of autonomous hybrid PV/wind system [J].
Diaf, S. ;
Diaf, D. ;
Belhamel, M. ;
Haddadi, M. ;
Louche, A. .
ENERGY POLICY, 2007, 35 (11) :5708-5718
[8]   Optimization of control strategies for stand-alone renewable energy systems with hydrogen storage [J].
Dufo-Lopez, Rodolfo ;
Bernal-Agustin, Jose L. ;
Contreras, Javier .
RENEWABLE ENERGY, 2007, 32 (07) :1102-1126
[9]   Size optimization of a PV/wind hybrid energy conversion system with battery storage using simulated annealing [J].
Ekren, Orhan ;
Ekren, Banu Y. .
APPLIED ENERGY, 2010, 87 (02) :592-598