Evaluating the efficiency of CCHP systems in Xinjiang Uygur Autonomous Region: An optimal strategy based on improved mother optimization algorithm

Case Studies in Thermal Engineering, Год журнала: 2024, Номер 54, С. 104005 - 104005

Опубликована: Янв. 8, 2024

A novel approach is presented in this research to improve the design of a combined cooling, heating, and power (CCHP) system. The focus study on gas turbine system that can provide efficient power, heating. efficacy proposed technique evaluated based four parameters, namely energetic, exergetic, economic, environmental features. To achieve superior optimal results, an Improved Mother Optimization Algorithm (IMOA), recently developed metaheuristic algorithm, employed. This provides comprehensive guide for enhancing performance, efficiency, sustainability CCHP systems. practical case was conducted evaluate methodology rural areas Xinjiang Uygur Autonomous Region, China, over period one year. simulation results reveal Gas Engine (GE) boiler components play significant role utilizing fuel energy, contributing 65 % 35 %, respectively overall utilization. analysis destruction rate profile highlights heat dissipation, mechanical losses, electrical losses are primary sources energy within When comparing IMOA with existing techniques, it evident achieves noteworthy 10 reduction consumption remarkable 15 increase efficiency Furthermore, terms impact, leads substantial 20 carbon dioxide (CO2) emissions compared traditional optimization methods. economic demonstrate IMOA-based not only improves cost-effectiveness by 25 but also yields estimated return investment (ROI) 18 higher than alternative techniques. Moreover, method minimum usage 0.200 L/h, Butterfly Optimizer (IBO) 0.201 Modified Mayfly (MM) algorithm 0.205 Developed Owl Search (DOS) 0.211 (IOS) methods 0.207 better results.

Язык: Английский

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An innovative technique for optimization and sensitivity analysis of a PV/DG/BESS based on converged Henry gas solubility optimizer: A case study

IET Generation Transmission & Distribution, Год журнала: 2023, Номер 17(21), С. 4735 - 4749

Опубликована: Фев. 2, 2023

Abstract The construction of hybrid power plants with renewable resources can bring significant economic benefits if it is evaluated economically and technically. present study uses a novel optimum methodology for designing combined solar/battery/diesel system in Yarkant, Xinjiang Uyghur Autonomous Region China. In the desired system, green energy designed to reduce use diesel generators. generator has been used photovoltaic, diesel, battery support batteries, as well function backup critical times whenever production low or load demand high. amount CO2 emitted, probability shortage cost on yearly basis are major goals process optimization. Here, single‐objective problem created by using ε‐constraint technique combine many objectives. An improved Henry gas solubility optimizer handles To demonstrate superiority strategy, comparison conducted between simulation outcomes offered HOMER, particle swarm ‐based systems from literature. sensitivity each parameter also examined analysis.

Язык: Английский

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A deep learning outline aimed at prompt skin cancer detection utilizing gated recurrent unit networks and improved orca predation algorithm

Biomedical Signal Processing and Control, Год журнала: 2023, Номер 90, С. 105858 - 105858

Опубликована: Дек. 22, 2023

Язык: Английский

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Efficient design of energy microgrid management system: A promoted Remora optimization algorithm-based approach

Heliyon, Год журнала: 2023, Номер 10(1), С. e23394 - e23394

Опубликована: Дек. 10, 2023

Microgrids are a promising solution for decentralized energy generation and distribution, offering reliability, efficiency, resilience. These small-scale power systems can operate independently or connect to the main grid, providing greater reliability However, integrating renewable into microgrids presents challenges due their unpredictable nature fluctuating load of electricity. Energy management strategies play crucial role in optimizing operation microgrids, aiming balance electricity supply demand, maximize utilization, minimize operational costs. Various approaches have been proposed including optimization algorithms, machine learning techniques, intelligent control systems. This study proposes an optimized efficient strategy operating both independent grid-connected modes, focusing on that utilize combination solar green sources. The approach, based Promoted Remora Optimization (PRO) algorithm, aims meet requirements at lowest possible cost while ensuring constant DC bus voltage safeguarding batteries against overcharging depletion. CRO method effectively charging process, maintaining consistent level charge achieving final SoC 33.37 %-33.60 %. It also demonstrated high system with average 87.99 %, range 87.80 %-88.03 optimizer efficiency ranged from 83.12 % 86.52 86.46 achieved reasonable costs, per $0.1687/kW $0.1699/kW daily $1,379,595 $1,479,998. Overall, showed promise process terms cost-effectiveness. Comparative analysis existing literature is conducted evaluate effectiveness demonstrating its superior results compared other microgrids. contributes field microgrid by novel approach PRO algorithm through comparative analysis.

Язык: Английский

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Attack-defense strategy assisted osprey optimization algorithm for PEMFC parameters identification

Renewable Energy, Год журнала: 2024, Номер 225, С. 120211 - 120211

Опубликована: Фев. 23, 2024

Язык: Английский

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Improved chaos grasshopper optimizer and its application to HRES techno-economic evaluation

Heliyon, Год журнала: 2024, Номер 10(2), С. e24315 - e24315

Опубликована: Янв. 1, 2024

Current political and economic trends are moving more toward the use of renewable clean energy as a result rising diminishing fossil fuel supplies. In this paper, an improved chaos-based grasshopper optimizer used for techno-economic evaluation in integrated green power systems is investigated. The system consists cell system, wind farm, solar energy. solar, wind, hydrogen architectures increase effectiveness electrical output while needing less storage structures that unconnected from grid. optimization technique chaos theory have been combined to create suggested chaotic study. performance, precision, robustness were then assessed, using four benchmark tasks. ICGO model utilized assign suitable ratings all devices, thereby guaranteeing attainment optimal performance efficiency. Net Present Cost (NPC) analysis revealed algorithm attained lowest minimum NPC value 274.541E4 USD highest maximum 311.94E4 USD. average (289.176E4 USD) was found be comparable other algorithms examined These findings indicate outperformed minimizing cost system. can handle several targets, restrictions, variables with ease, results demonstrate it substantially efficient precise than standard techniques. It also quite durable, minimal degradation compared solutions. This study demonstrates HRES technique.

Язык: Английский

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SOFC stack modeling: a hybrid RBF-ANN and flexible Al-Biruni Earth radius optimization approach

International Journal of Low-Carbon Technologies, Год журнала: 2024, Номер 19, С. 1337 - 1350

Опубликована: Янв. 1, 2024

Abstract This study introduces a novel hybrid methodology for model identification of solid oxide fuel cell (SOFC) stacks by integrating radial basis function-based artificial neural network (RBF-ANN) with flexible Al-Biruni Earth radius optimizer (FA-BERO). The primary objective the proposed method is to augment precision and efficiency SOFC stack modeling considering advantages both RBF-ANN FA-BERO algorithms. main purpose using these two methods optimize structure based on suggested algorithm. other contribution this improving (A-BERO) applying improvements it, including constriction factor elimination phase increase exploration exploitation strength basic A-BERO. To validate effectiveness model, it compared some state-of-the-art models in field, such as multi-armed bandit algorithm (ANN/MABA) rotor Hopfield grey wolf optimization (RHNN/GWO). Furthermore, validated experimental data, final results demonstrate efficacy approach accurately representing intricate behavior stacks. achieves lower error rates (ERs) root mean squared errors (RMSEs) than comparative across different arrangements temperature conditions. show that, instance, 2/12/1 arrangement at 900°C, attains an ER 6.69% RMSE 2.13, while ANN/MABA RHNN/GWO obtain ERs 9.67% 8.54%, well values 24.48 9.23, respectively. also exhibits superior accuracy convergence speed methods, shown current–voltage curves analysis. Consequently, offers valuable tool researchers engineers working domain technology, enabling them better understand performance.

Язык: Английский

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An Accurate Parameter Estimation Method of the Voltage Model for Proton Exchange Membrane Fuel Cells

Energies, Год журнала: 2024, Номер 17(12), С. 2917 - 2917

Опубликована: Июнь 13, 2024

Accurate and reliable mathematical modeling is essential for the optimal control performance analysis of polymer electrolyte membrane fuel cell (PEMFC) systems, which are mainly implemented based on accurate parameter estimation. In this paper, a multi-strategy tuna swarm optimization (MS-TSO) proposed to estimate parameters PEMFC voltage models compare them with other optimizers such as differential evolution, whale approach, salp algorithm, particle optimization, Harris hawk slime mould algorithm. optimizing routine, unidentified factors PEMFCs used decision variables, optimized minimize sum square errors between estimated measured data. The examined three datasets including BCS500W, NedStackPS6 harizon500W well set experimental data using Greenlight G20 platform 25 cm2 single at 353 K. It confirmed that MS-TSO gives better in terms convergence speed accuracy than competing algorithms. Furthermore, results achieved by compared reported approaches literature. advantages ascertaining optimum various have been comprehensively demonstrated.

Язык: Английский

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Stochastic economic sizing of hydrogen storage-based renewable off-grid system with smart charge of electric vehicles according to combined hydrogen and power model

Journal of Energy Storage, Год журнала: 2025, Номер 108, С. 115171 - 115171

Опубликована: Янв. 5, 2025

Язык: Английский

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Accurate Key Parameters Estimation of PEMFCs’ Models Based on Dandelion Optimization Algorithm

Mathematics, Год журнала: 2023, Номер 11(6), С. 1298 - 1298

Опубликована: Март 8, 2023

With the increasing demand for electrical energy and challenges related to its production, along with need be environmentally friendly achieve sustainability future generations, proton exchange membrane fuel cells (PEMFCs) are emerging as a clean source that can effectively replace conventional sources, in various fields of application especially field transportation exploiting electric vehicles (EVs). To improve development control PEMFCs, precise determination mathematical model remains an essential task. Indeed, accuracy such depends on ability overcome constraints associated nonlinearity numerous involved unknown parameters. The present paper proposes new Dandelion Optimizer (DO) accurately identify, first time, parameters PEMFC model. DO addresses weaknesses majority metaheuristic algorithms self-adaptation parameters, stagnation convergence local minima, refer whole population. high proposed method is investigated using both steady-state dynamic situations. DO-based estimation approach has been assessed through specific comparative study most recently published techniques including GWO, GBO, HHO, IAEO, VSDE, ABCDESC performed two typical modules, namely 250 W NedStack PS6. results obtained proved promising achievements better performances comparatively well-recognized competitive methods.

Язык: Английский

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