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Efficiency and economic assessment of wind turbine-powered pumped hydro-compressed air storage coupled with alkaline fuel cell using hybrid approach

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Abstract

Traditional sources of energy are expensive, finite, and pollute the environment when used. Utilizing renewable energy resources is necessary to meet human societies’ energy needs and promote sustainable development. This paper presents a hybrid approach to analyze the efficiency and economic assessment of pumped hydro-compressed air storage coupled with alkaline fuel cells. The proposed hybrid method is the Siberian tiger optimization (STO) and spiking deep residual networks (SDRN). Hence, it is named as STO–SDRN approach. By integrating these advanced optimization techniques, the aim is to optimize system performance and minimize total operation costs. Wind energy is globally available in various intensities, while alkaline fuel cells offer energy provision as long as fuel and oxidant are supplied. Integrating these energy systems can enhance overall system effectiveness. Wind turbines and alkaline fuel cells convert wind kinetic energy and fuel chemical energy into power, correspondingly. Excess power produced by wind turbines and alkaline fuel cells is stored in the pumped hydro-compressed electrical energy system. Through meticulous control and optimization facilitated by STO–SDRN, the study seeks to overcome the limitations of existing methodologies. Implemented in MATLAB, the proposed model is compared with existing approaches like the heap-based optimizer (HBO), cuckoo search algorithm (CSA), and the salp swarm algorithm (SSA). Comparative analysis demonstrates that the proposed system achieves significantly higher efficiency, with 94% efficiency compared to 85% for HBO, 76% for CSA, and 68% for SSA. Furthermore, the proposed system incurs lower costs, with $1.3 compared to $2.5 for HBO, $3.5 for CSA, and $4.1 for SSA, showcasing its cost-effectiveness and efficiency over existing approaches. This study contributes a rigorous high-level discussion and quantitative assessment of the proposed approach’s performance, addressing key energy system challenges while offering tangible benefits for sustainable energy development.

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References

  • Al Keyyam I, Al-Nimr MD, Khashan S, Keewan A (2021) A new solar atmospheric water harvesting integrated system using CPV/T–Stirling engine–Absorption cooling cycle and vapor compression refrigeration cycle. Int J Energy Res 45(11):16400–16417

    Article  CAS  Google Scholar 

  • Arsad AZ, Hannan MA, Al-Shetwi AQ, Begum RA, Hossain MJ, Ker PJ, Mahlia TI (2023) Hydrogen electrolyser technologies and their modelling for sustainable energy production: a comprehensive review and suggestions. Int J Hydrog Energy 47(39):17285–17312

    Article  Google Scholar 

  • Bedakhanian A, Assareh E, Agarwal N, Lee M (2024) Thermoeconomical, wind assessments and environmental analysis of compressed air energy storage (CAES) integrated with a wind farm by using RSM as a machine learning optimization technique-case study-Denmark. J Energy Storage 78:110059

    Article  Google Scholar 

  • Behzadi A, Alirahmi SM, Yu H, Sadrizadeh S (2023) An efficient renewable hybridization based on hydrogen storage for peak demand reduction: a rule-based energy control and optimization using machine learning techniques. J Energy Storage 57:106168

    Article  Google Scholar 

  • Chen H, Wang H, Li R, Zhang Y, He X (2020) Thermo-dynamic and economic analysis of sa novel near-isothermal pumped hydro compressed air energy storage system. J Energy Storage 30:101487

    Article  Google Scholar 

  • Cheng S, Zhao G, Gao M, Shi Y, Huang M, Marefati M (2021) A new hybrid solar photovoltaic/phosphoric acid fuel cell and energy storage system; energy and exergy performance. Int J Hydrog Energy 46(11):8048–8066

    Article  CAS  Google Scholar 

  • De Schepper P, Danilov V, Denayer JF (2012) A tank in series model for alkaline fuel cell in cogeneration of hydrogen peroxide and electricity. Int J Hydrog Energy 37(22):17258–17267

    Article  Google Scholar 

  • Dehghani M, Montazeri Z, Trojovská E, Trojovský P (2023) Coati optimization algorithm: a new bio-inspired metaheuristic algorithm for solving optimization problems. Knowl-Based Syst 259:110011

    Article  Google Scholar 

  • Dong L, Xing T, Song J, Yousefi A (2021) Performance analysis of a novel hybrid solar photovoltaic-pumped-hydro and compressed-air storage system in different climatic zones. J Energy Storage 35:102293

    Article  Google Scholar 

  • Feng Y, Cai W, Wang S, Zhang C, Liu Y (2021) Numerical evaluation of energy system based on fresnel concentrating solar collector, stirling engine, and thermoelectric generator with electrical energy storage. Int J Energy Res 45(13):19423–19438

    Article  Google Scholar 

  • Hakamian K, Anderson KR, Shafahi M, Lakeh RB (2019) Thermal design and analysis of a solid-state grid-tied thermal energy storage for hybrid compressed air energy storage systems. J Energy Res Technol 141(6):061903

    Article  CAS  Google Scholar 

  • Ibrahim NI, Al-Sulaiman FA, Saat A, Rehman S, Ani FN (2020) Charging and discharging characteristics of absorption energy storage integrated with a solar driven double-effect absorption chiller for air conditioning applications. J Energy Storage 29:101374

    Article  Google Scholar 

  • Joshua KP, Rangasamy LV, Reddy CV, Veeruchinnan R (2023) Energy management of solar photovoltaic fed water pumping system based BLDC motor drive using NBO–SDRN approach. Electr Eng 1–5

  • Khanmohammadi S, Rahmani M, Musharavati F, Khanmohammadi S, Bach QV (2021) Thermal modeling and triple objective optimization of a new compressed air energy storage system integrated with rankine cycle, PEM fuel cell, and thermoelectric unit. Sustain Energy Technol Assess 43:100810

    Google Scholar 

  • Lee C, Sarwar SS, Panda P, Srinivasan G, Roy K (2020) Enabling spike-based backpropagation for training deep neural network architectures. Front Neurosci 14:119

    Article  CAS  Google Scholar 

  • Li D, Guo J, Zhang J, Zhan L, Alizadeh M (2021) Numerical assessment of a hybrid energy generation process and energy storage system based on alkaline fuel cell, solar energy and stirling engine. J Energy Storage 39:102631

    Article  Google Scholar 

  • Liu J, Chen C, Liu Z, Jermsittiparsert K, Ghadimi N (2020) An IGDT-based risk-involved optimal bidding strategy for hydrogen storage-based intelligent parking lot of electric vehicles. J Energy Storage 27:101057

    Article  Google Scholar 

  • Marefati M, Mehrpooya M (2019) Introducing a hybrid photovoltaic solar, proton exchange membrane fuel cell and thermoelectric device system. Sustain Energy Technol Assess 36:100550

    Google Scholar 

  • Oyelade ON, Ezugwu AES, Mohamed TI, Abualigah L (2022) Ebola optimization search algorithm: a new nature-inspired metaheuristic optimization algorithm. IEEE Access 10:16150–16177

    Article  Google Scholar 

  • Peng MY, Chen C, Peng X, Marefati M (2020) Energy and exergy analysis of a new combined concentrating solar collector, solid oxide fuel cell, and steam turbine CCHP system. Sustain Energy Technol Assess 39:100713

    Google Scholar 

  • Pottie DL, Ferreira RA, Maia TA, Porto MP (2020) An alternative sequence of operation for pumped-hydro compressed air energy storage (PH-CAES) systems. Energy 191:116472

    Article  Google Scholar 

  • Rajesh P, Naveen C, Venkatesan AK, Shajin FH (2021) An optimization technique for battery energy storage with wind turbine generator integration in unbalanced radial distribution network. J Energy Storage 43:103160

    Article  Google Scholar 

  • Sadeghi S, Ghandehariun S, Rezaie B, Javani N (2021) An innovative solar-powered natural gas-based compressed air energy storage system integrated with a liquefied air power cycle. Int J Energy Res 45(11):16294–16309

    Article  CAS  Google Scholar 

  • Sami I, Ullah S, Ullah N, Ro JS (2021) Sensorless fractional order composite sliding mode control design for wind generation system. ISA Trans 111:275–289

    Article  Google Scholar 

  • Saxena P, Singh N, Pandey AK (2020) Enhancing the dynamic performance of microgrid using derivative controlled solar and energy storage based virtual inertia system. J Energy Storage 31:101613

    Article  Google Scholar 

  • Trojovský P, Dehghani M (2022) Pelican optimization algorithm: a novel nature-inspired algorithm for engineering applications. Sensors 22(3):855

    Article  Google Scholar 

  • Trojovský P, Dehghani M, Hanuš P (2022) Siberian tiger optimization: a new bio-inspired metaheuristic algorithm for solving engineering optimization problems. IEEE Access 10:132396–132431

    Article  Google Scholar 

  • Viji D, Dhanka S, Binda MB, Thomas M (2024) Hybrid STO-IWGAN method based energy optimization in fuel cell electric vehicles. Energy Convers Manag 305:118249

    Article  Google Scholar 

  • Wang Y, Hasani J (2022) Energy generation from a system based on solar energy and fuel cell technology with the option of storing electrical energy. Energy Rep 8:4988–5004

    Article  Google Scholar 

  • Wang H, Su Z, Abed AM, Nag K, Deifalla A, Marefati M, Mahariq I, Wei Y (2023) Multi-criteria evaluation and optimization of a new multigeneration cycle based on solid oxide fuel cell and biomass fuel integrated with a thermoelectric generator, gas turbine, and methanation cycle. Process Saf Environ Prot 170:139–156

    Article  CAS  Google Scholar 

  • Yodwong B, Guilbert D, Phattanasak M, Kaewmanee W, Hinaje M, Vitale G (2020) Faraday’s efficiency modeling of a proton exchange membrane electrolyzer based on experimental data. Energies 13(18):4792

    Article  CAS  Google Scholar 

  • Zhang Y, Xu Y, Zhou X, Guo H, Zhang X, Chen H (2019) Compressed air energy storage system with variable configuration for accommodating large-amplitude wind power fluctuation. Appl Energy 239:957–968

    Article  Google Scholar 

Download references

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Public, private, or nonprofit funding organizations did not provide any special support for this study.

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Authors and Affiliations

  1. Department of Electrical and Electronics Engineering, Karpaga Vinayaga College of Engineering and Technology, Chengalpattu (D.T), 603308, Tamil Nadu, India

    K. E. Lakshmiprabha

  2. Department of Electrical and Electronics Engineering, Faculty of Engineering, Karpagam Academy of Higher Education (Deemed to Be University), Coimbatore, 641021, Tamil Nadu, India

    U. Arun Kumar

  3. Department of Information Technology, Symbiosis Institute of Digital and Telecom Management (SIDTM), Symbiosis International (Deemed University), Pune, India

    Pankaj Pathak

  4. Department of Electrical and Electronics Engineering, School of Electrical and Communication Sciences, B S Abdur Rahman Crescent Institute of Science and Technology, Chennai, India

    P. Elangovan

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  1. K. E. Lakshmiprabha
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  4. P. Elangovan
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Contributions

K.E. Lakshmiprabha contributed to the conceptualization, methodology, and original draft preparation; U. Arun Kumar was involved in the supervision; Pankaj Pathak assisted in the supervision; P. Elangovan was involved in the supervision.

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Correspondence to K. E. Lakshmiprabha.

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Lakshmiprabha, K.E., Kumar, U.A., Pathak, P. et al. Efficiency and economic assessment of wind turbine-powered pumped hydro-compressed air storage coupled with alkaline fuel cell using hybrid approach. Clean Techn Environ Policy (2024). https://doi.org/10.1007/s10098-024-02869-0

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