Power generation cost minimization of the grid-connected hybrid renewable energy system through optimal sizing using the modified seagull optimization technique

Abstract A hybrid renewable power system is studied in this paper. This system is composed of PV panels, wind turbines, inverter, rectifier, electrolyzer, and fuel cell such that it prioritizes storing excess energy by converting it to hydrogen and using it later in the fuel cell. Additional extra generation power is sold to the main electricity network. The system generates power from clean sources and has zero emission. To achieve minimum power generation cost, the optimal size of each component is obtained using the proposed modified seagull optimization technique. The cooperative generation of wind and PV and energy storage mitigate the uncertain behavior of renewable energy sources. The proposed hybrid power system and optimization are implemented in a real-world case study in Qingdao, China. The consumption and meteorological data of the year 2018 are used as input to the system. To prove the superiority of the proposed optimization method in terms of accuracy and computation time, it is compared to two other optimization methods, namely original seagull optimization algorithm (SOA) and modified farmland fertility algorithm (MFFA), which are used in similar applications. The proposed method has achieved 2.02% and 2.78% better results and converged 69.36% and 47.07% faster compared to conventional SOA and MFFA methods, respectively. In addition, the hybrid system is able to operate with high reliability and loss of power supply probability well below the threshold of 8 . 96 e 20 .

[1]  Noradin Ghadimi,et al.  A new prediction model of battery and wind-solar output in hybrid power system , 2019, J. Ambient Intell. Humaniz. Comput..

[2]  D. Noble,et al.  The influence of migration patterns on exposure to contaminants in Nearctic shorebirds: a historical study , 2020, Environmental Monitoring and Assessment.

[3]  Lorenzo Bartolucci,et al.  Fuel cell based hybrid renewable energy systems for off-grid telecom stations: Data analysis and system optimization , 2019, Applied Energy.

[4]  Partha Sarathi Subudhi,et al.  Wireless Power Transfer Topologies used for Static and Dynamic Charging of EV Battery: A Review , 2020 .

[5]  Aref Jalili,et al.  Hybrid harmony search algorithm and fuzzy mechanism for solving congestion management problem in an electricity market , 2016, Complex..

[6]  Paolo Maria Congedo,et al.  A novel energy-economic-environmental multi-criteria decision-making in the optimization of a hybrid renewable system , 2020 .

[7]  M. Lerch,et al.  Ionomer distribution control in porous carbon-supported catalyst layers for high-power and low Pt-loaded proton exchange membrane fuel cells , 2019, Nature Materials.

[8]  Zhi Yuan,et al.  A new technique for optimal estimation of the circuit-based PEMFCs using developed Sunflower Optimization Algorithm , 2020 .

[9]  Noradin Ghadimi,et al.  Multi-objective energy management in a micro-grid , 2018, Energy Reports.

[10]  Noradin Ghadimi,et al.  Optimal preventive maintenance policy for electric power distribution systems based on the fuzzy AHP methods , 2016, Complex..

[11]  Marc A. Rosen,et al.  Sizing a stand-alone solar-wind-hydrogen energy system using weather forecasting and a hybrid search optimization algorithm , 2019, Energy Conversion and Management.

[12]  Ramchandra Bhandari,et al.  Hybrid off-grid renewable power system for sustainable rural electrification in Benin , 2020 .

[13]  Marc A. Rosen,et al.  Optimal location and size of a grid-independent solar/hydrogen system for rural areas using an efficient heuristic approach , 2020 .

[14]  Mohsen Mohammadi,et al.  A new multiobjective allocator of capacitor banks and distributed generations using a new investigated differential evolution , 2014, Complex..

[15]  Richard Perez,et al.  Overbuilding & curtailment: The cost-effective enablers of firm PV generation , 2019, Solar Energy.

[16]  Li Sun,et al.  Life Cycle Optimization of Renewable Energy Systems Configuration with Hybrid Battery/Hydrogen Storage: A Comparative Study , 2020 .

[17]  Wei Wang,et al.  Electricity load forecasting by an improved forecast engine for building level consumers , 2017 .

[18]  Noradin Ghadimi,et al.  The price prediction for the energy market based on a new method , 2018 .

[19]  Noradin Ghadimi,et al.  Islanding detection for inverter-based DG coupled with using an adaptive neuro-fuzzy inference system , 2013 .

[20]  Di Cao,et al.  Implementation of repowering optimization for an existing photovoltaic‐pumped hydro storage hybrid system: A case study in Sichuan, China , 2019, International Journal of Energy Research.

[21]  Nader Karimi,et al.  Techno-economic assessment and optimization of a hybrid renewable earth - air heat exchanger coupled with electric boiler, hydrogen, wind and PV configurations , 2020, Renewable Energy.

[22]  Hexu Sun,et al.  Multi-objective optimization for the proper selection of the best heat pump technology in a fuel cell-heat pump micro-CHP system , 2020 .

[23]  K. Jermsittiparsert,et al.  New optimal design for a hybrid solar chimney, solid oxide electrolysis and fuel cell based on improved deer hunting optimization algorithm , 2020 .

[24]  Gordon H. Huang,et al.  Planning municipal-scale mixed energy system for stimulating renewable energy under multiple uncertainties - The City of Qingdao in Shandong Province, China , 2019, Energy.

[25]  M. J. Khan,et al.  Pre-feasibility study of stand-alone hybrid energy systems for applications in Newfoundland , 2005 .

[26]  Agnimitra Biswas,et al.  Techno-economic optimization of an off-grid hybrid renewable energy system using metaheuristic optimization approaches – Case of a radio transmitter station in India , 2019, Energy Conversion and Management.

[27]  Mohammad Ghiasi,et al.  Extracting Appropriate Nodal Marginal Prices for All Types of Committed Reserve , 2019 .

[28]  Hosein Hayati,et al.  Wind power penetration impact on power system frequency , 2019 .

[29]  Joydeep Mitra,et al.  A new method for estimating the longevity and degradation of photovoltaic systems considering weather states , 2016 .

[30]  C. Ghenai,et al.  Technico-economic analysis of off grid solar PV/Fuel cell energy system for residential community in desert region , 2020 .

[31]  Noradin Ghadimi,et al.  A new feature selection and hybrid forecast engine for day-ahead price forecasting of electricity markets , 2017, J. Intell. Fuzzy Syst..

[32]  Hadi Zayandehroodi,et al.  A New Formulation to Reduce the Number of Variables and Constraints to Expedite SCUC in Bulky Power Systems , 2019 .

[33]  Amir Ahadi,et al.  Reliability evaluation of future photovoltaic systems with smart operation strategy , 2016 .

[34]  Saeed Tavakoli,et al.  Reliability based optimal allocation of distributed generations in transmission systems under demand response program , 2019, Electric Power Systems Research.

[35]  Ahmed M. Anter,et al.  Feature selection strategy based on hybrid crow search optimization algorithm integrated with chaos theory and fuzzy c-means algorithm for medical diagnosis problems , 2019, Soft Computing.

[36]  Xinbo Ruan,et al.  An Improved Optimal Sizing Method for Wind-Solar-Battery Hybrid Power System , 2013, IEEE Transactions on Sustainable Energy.

[37]  Mehdi Hosseinzadeh,et al.  A framework to expedite joint energy-reserve payment cost minimization using a custom-designed method based on Mixed Integer Genetic Algorithm , 2018, Eng. Appl. Artif. Intell..

[38]  Dongmin Yu,et al.  Reliability constraint stochastic UC by considering the correlation of random variables with Copula theory , 2019, IET Renewable Power Generation.

[39]  Haiguo Tang,et al.  A new wind power prediction method based on ridgelet transforms, hybrid feature selection and closed-loop forecasting , 2018, Adv. Eng. Informatics.

[40]  M. Rani,et al.  Levels and profiles of persistent organic pollutants in resident and migratory birds from an urbanized coastal region of South Korea. , 2014, The Science of the total environment.

[41]  Karzan Wakil,et al.  Optimal bidding and offering strategies of compressed air energy storage: A hybrid robust-stochastic approach , 2019 .

[42]  Leopoldo G. Franquelo,et al.  Binary Search Based Flexible Power Point Tracking Algorithm for Photovoltaic Systems , 2021, IEEE Transactions on Industrial Electronics.

[43]  D. Kammen,et al.  Where, when and how much solar is available? A provincial-scale solar resource assessment for China , 2016 .

[44]  Hooman Farzaneh,et al.  Techno-Economic Analysis of a Novel Hydrogen-Based Hybrid Renewable Energy System for Both Grid-Tied and Off-Grid Power Supply in Japan: The Case of Fukushima Prefecture , 2020, Applied Sciences.

[45]  Vijay Kumar,et al.  Seagull optimization algorithm: Theory and its applications for large-scale industrial engineering problems , 2019, Knowl. Based Syst..

[46]  Pengjun Wang,et al.  Chaos-enhanced synchronized bat optimizer , 2020 .

[47]  Ali M. Eltamaly,et al.  A novel framework-based cuckoo search algorithm for sizing and optimization of grid-independent hybrid renewable energy systems , 2018, International Journal of Green Energy.

[48]  Chengye Li,et al.  Gaussian mutational chaotic fruit fly-built optimization and feature selection , 2020, Expert Syst. Appl..

[49]  Noradin Ghadimi,et al.  Hybrid PSOTVAC/BFA technique for tuning of robust PID controller of fuel cell voltage , 2016 .

[50]  Elif Varol Altay,et al.  Bird swarm algorithms with chaotic mapping , 2019, Artificial Intelligence Review.

[51]  Xianbing Liu,et al.  An analysis of the interactions between electricity, fossil fuel and carbon market prices in Guangdong, China , 2020 .

[52]  Amir Ahadi,et al.  Generating capacity adequacy evaluation of large-scale, grid-connected photovoltaic systems , 2016 .

[53]  Noradin Ghadimi,et al.  Robust optimization based optimal chiller loading under cooling demand uncertainty , 2019, Applied Thermal Engineering.

[54]  M. Akhtari,et al.  Techno-economic assessment and optimization of a hybrid renewable co-supply of electricity, heat and hydrogen system to enhance performance by recovering excess electricity for a large energy consumer , 2019, Energy Conversion and Management.

[55]  Hossam H.H. Mousa,et al.  Variable step size P&O MPPT algorithm for optimal power extraction of multi-phase PMSG based wind generation system , 2019, International Journal of Electrical Power & Energy Systems.

[56]  Ayda Darvishan,et al.  Fuzzy-based heat and power hub models for cost-emission operation of an industrial consumer using compromise programming , 2018, Applied Thermal Engineering.

[57]  K. Jermsittiparsert,et al.  An optimal configuration for a battery and PEM fuel cell-based hybrid energy system using developed Krill herd optimization algorithm for locomotive application , 2020 .

[58]  Farhad Soleimanian Gharehchopogh,et al.  Farmland fertility: A new metaheuristic algorithm for solving continuous optimization problems , 2018, Appl. Soft Comput..