A genetic algorithm based improved optimal sizing strategy for solar-wind-battery hybrid system using energy filter algorithm

Abstract

In this paper, the genetic algorithm (GA) is applied to optimize a grid connected solar photovoltaic (PV)-wind-battery hybrid system using a novel energy filter algorithm. The main objective of this paper is to minimize the total cost of the hybrid system, while maintaining its reliability. Along with the reliability constraint, some of the important parameters, such as full utilization of complementary nature of PV and wind systems, fluctuations of power injected into the grid and the battery’s state of charge (SOC), have also been considered for the effective sizing of the hybrid system. A novel energy filter algorithm for smoothing the power injected into the grid has been proposed. To validate the proposed method, a detailed case study has been conducted. The results of the case study for different cases, with and without employing the energy filter algorithm, have been presented to demonstrate the effectiveness of the proposed sizing strategy.

Keywords

PV-wind-battery hybrid system / size optimization / genetic algorithm

References

[1] Mahesh A, Sandhu K S. Hybrid wind/photovoltaic energy system developments: critical review and findings. Renewable & Sustainable Energy Reviews, 2015, 52: 1135–1147

[2] Yang H X, Lu L, Zhou W. A novel optimization sizing model for hybrid solar-wind power generation system. Solar Energy, 2007, 81(1): 76–84

[3] Ekren O, Ekren B Y. Size optimization of a PV/wind hybrid energy conversion system with battery storage using simulated annealing. Applied Energy, 2010, 87(2): 592–598

[4] Kaabeche A, Belhamel M, Ibtiouen R. Sizing optimization of grid-independent hybrid photovoltaic/wind power generation system. Energy, 2011, 36(2): 1214–1222

[5] Kellogg W D, Nehrir M H, Venkataramanan G, Gerez V. Generation unit sizing and cost analysis for stand-alone wind, photovoltaic, and hybrid wind/PV systems. IEEE Transactions on Energy Conversion, 1998, 13(1): 70–75

[6] Markvart T. Sizing of hybrid photovoltaic-wind energy systems. Solar Energy, 1996, 57(4): 277–281

[7] Dufo-López R, Bernal-Agustín J L. Multi-objective design of PV-wind-diesel-hydrogen-battery systems. Renewable Energy, 2008, 33(12): 2559–2572

[8] Dufo-López R, Bernal-Agustín J L, Yusta-Loyo J M, Domínguez-Navarro J A, Ramírez-Rosado I J, Lujano J, Aso I. Multi-objective optimization minimizing cost and life cycle emissions of stand-alone PV-wind-diesel systems with batteries storage. Applied Energy, 2011, 88(11): 4033–4041

[9] Yang H X, Zhou W, Lu L, Fang Z H. Optimal sizing method for stand-alone hybrid solar-wind system with LPSP technology by using genetic algorithm. Solar Energy, 2008, 82(4): 354–367

[10] Diaf S, Diaf D, Belhamel M, Haddadi M, Louche A. A methodology for optimal sizing of autonomous hybrid PV/wind system. Energy Policy, 2007, 35(11): 5708–5718

[11] Ren H B, Zhou W S, Nakagami K, Gao W J, Wu Q. Multi-objective optimization for the operation of distributed energy systems considering economic and environmental aspects. Applied Energy, 2010, 87(12): 3642–3651

[12] Zhao B, Zhang X S, Li P, Wang K, Xue M D, Wang C S. Optimal sizing, operating strategy and operational experience of a stand-alone microgrid on Dongfushan Island. Applied Energy, 2014, 113: 1656–1666

[13] Sheng W X, Liu K Y, Meng X L, Ye X S, Liu Y M. Research and practice on typical modes and optimal allocation method for PV-Wind-ES in microgrid. Electric Power Systems Research, 2015, 120: 242–255

[14] Yazdanpanah Jahromi M A, Farahat S, Barakati S M. Optimal size and cost analysis of stand-alone hybrid wind/photovoltaic power-generation systems. Civil Engineering and Environmental Systems, 2014, 31(4): 283–303

[15] Maleki A, Askarzadeh A. Artificial bee swarm optimization for optimum sizing of a standalone PV/WT/FC hybrid system considering LPSP concept. Solar Energy, 2014, 107: 227–235

[16] Askarzadeh A. Solution for sizing a PV/diesel HPGS for isolated sites. IET Renewable Power Generation, 2017, 11(1): 143–151

[17] Fetanat A, Khorasaninejad E. Size optimization for hybrid photovoltaic-wind energy system using ant colony optimization for continuous domains based integer programming. Applied Soft Computing, 2015, 31: 196–209

[18] Zhao J Y, Yuan X F. Multi-objective optimization of stand-alone hybrid PV-wind-diesel-battery system using improved fruit fly optimization algorithm. Soft Computing, 2016, 20(7): 2841–2853

[19] Ahmadi S, Abdi S. Application of the Hybrid Big Bang-Big Crunch algorithm for optimal sizing of a stand-alone hybrid PV/wind/battery system. Solar Energy, 2016, 134: 366–374

[20] Maleki A, Pourfayaz F, Rosen M A. A novel framework for optimal design of hybrid renewable energy-based autonomous energy systems: a case study for Namin, Iran. Energy, 2016, 98: 168–180

[21] Tito S R, Lie T T, Anderson T N. Optimal sizing of a wind-photovoltaic-battery hybrid renewable energy system considering socio-demographic factors. Solar Energy, 2016, 136: 525–532

[22] Dufo-López R, Cristóbal-Monreal I R, Yusta J M. Optimisation of PV-wind-diesel-battery stand-alone systems to minimise cost and maximise human development index and job creation. Renewable Energy, 2016, 94: 280–293

[23] Sandhu K S, Mahesh A. A new approach of sizing battery energy storage system for smoothing the power fluctuations of a PV/wind hybrid system. International Journal of Energy Research, 2016, 40(9): 1221–1234

[24] Askarzadeh A. Electrical power generation by an optimised autonomous PV/wind/tidal/battery system. IET Renewable Power Generation, 2017, 11(1): 152–164

[25] Li X J, Hui D, Lai X K. Battery energy storage station (BESS)-based smoothing control of photovoltaic (PV) and wind power generation fluctuations. IEEE Transactions onSustainable Energy, 2013, 4(2):464–473

[26] Li X J, Hui D, Wu L, Lai X K. Control strategy of battery state of charge for wind/battery hybrid power system. In:2010 IEEE International Symposium on Industrial Electronics (ISIE2010), Bari, Italy, 2010, 2723–2726

[27] Ahmed N A, Miyatake M, Al-Othman A K. Power fluctuations suppression of stand-alone hybrid generation combining solar photovoltaic/wind turbine and fuel cell systems. Energy Conversion and Management, 2008, 49(10): 2711–2719

[28] Kim S K, Jeon J H, Cho C H, Ahn J B, Kwon S H. Dynamic modeling and control of a grid-connected hybrid generation system with versatile power transfer. IEEE Transactions on Industrial Electronics, 2008, 55(4): 1677–1688

[29] Datta M, Senjyu T, Yona A, Funabashi T, Kim C H. A coordinated control method for leveling PV output power fluctuations of PV/diesel hybrid systems connected to isolated power utility. IEEE Transactions on Energy Conversion, 2009, 24(1): 153–162

[30] Omran W A, Kazerani M, Salama M M A. Investigation of methods for reduction of power fluctuations generated from large grid-connected photovoltaic systems. IEEE Transactions on Energy Conversion, 2011, 26(1): 318–327

[31] Aissou S, Rekioua D, Mezzai N, Rekioua T, Bacha S. Modeling and control of hybrid photovoltaic wind power system with battery storage. Energy Conversion and Management, 2015, 89: 615–625

[32] Datta M, Senjyu T, Yona A, Funabashi T. A fuzzy based method for leveling output power fluctuations of photovoltaic-diesel hybrid power system. Renewable Energy, 2011, 36(6): 1693–1703

[33] Xu L, Ruan X B, Mao C X, Zhang B H, Luo Y. An improved optimal sizing method for wind-solar-battery hybrid power system. IEEE Transactions on Sustainable Energy, 2013, 4(3): 774–785

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Higher Education Press and Springer-Verlag Berlin Heidelberg