Integration of Renewable Energy based Trigeneration Cycle: A Review

Kumar, Manish; Chandra, H.; Banchhor, Raghwendra; Aravind, Arun

doi:10.1007/s40032-021-00690-y

Cited by 9 publications

(3 citation statements)

References 55 publications

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“…The forecasting accuracy is directly dependent on the employed technique and error calculation method. Some previous studies have attempted to forecast residents’ habits, solar energy, wind speed, and water requirements for a complete day [60] , [198] .…”

Section: Challenges Associated With Shemsmentioning

confidence: 99%

Analysis of energy management schemes for renewable-energy-based smart homes against the backdrop of COVID-19

Ayub

Ayob

Tan

et al. 2022

Sustainable Energy Technologies and Assessments

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Section: Challenges Associated With Shemsmentioning

confidence: 99%

Analysis of energy management schemes for renewable-energy-based smart homes against the backdrop of COVID-19

Ayub

Ayob

Tan

et al. 2022

Sustainable Energy Technologies and Assessments

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“…The efficiency of the Brayton cycle is directly proportional to the pressure ratio, a higher-pressure ratio results in greater efficiency. A renewable-based trigeneration cycle is presented in Kumar et al (2021), Integration of Renewable Energy-based Trigeneration Cycle: A Review which examined all possible parameters while we integrate renewable energy into gas turbine (GT), Rankine cycle and Kalina cycle.…”

Section: Introductionmentioning

confidence: 99%

Energy and exergy analysis of hybridization of solar, intercooled reheated gas turbine trigeneration cycle

Kumar

Aravind

Banchhor

et al. 2022

WJE

Self Cite

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Purpose This paper aims to analyze energy and exergy analysis of solar-based intercooled and reheated gas turbine (GT) trigeneration cycle using parabolic trough solar collectors (PTC) with the use of MATLAB 2018. Design/methodology/approach In the first section of this paper, the solar-based GT is validated with the reference paper. According to the reference paper, the solar field is comprising 30 modules in series and 35 modules in parallel series, where a total of 1,050 modules of PTC are taken into consideration. In the second part of this paper, the hybridization of the solar, GT trigeneration cycle is analyzed and optimized. In the last section of this paper, the hybridization of solar, intercooled and reheated GT trigeneration systems is examined and compared. Findings The results examined the first section, the power produced by the cycle will be 37.34 MW at 0.5270 kg/s mass flow rate of the natural gas consumption and the efficiencies of energy and exergy will be 38.34% and 39.76%, respectively. The results examined in the second section, the power produced by the cycle will be 38.4 MW at 0.5270 kg/s mass flow rate of the natural gas consumption and accordingly the efficiency of energy and exergy is found to be 40.011% and 41.763%. Where in the last section, the power produced by the cycle will be 41.43 MW at 0.5270 kg/s mass flow rate of the natural gas consumption and the energy and exergy efficiencies will be 39.76% and 40.924%, respectively. Originality/value The author confirms that this study is original and has neither been published elsewhere nor it is currently under consideration for publication elsewhere.

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“…Common energy consumption diagnosis methods are usually divided into two categories: the heat method and exergy method, based on the first law of thermodynamics and the second law of thermodynamics, respectively [1]. The heat method is used to evaluate the unit economy efficiency from the perspective of energy conversion quantity, such as the equivalent enthalpy drop method [2], heat balance method, cyclic function method [3], matrix method, and so on. An improved equivalent enthalpy drop method was proposed to determine the equivalent enthalpy drop through the isentropic expansion process of steam [4].…”

Section: Introductionmentioning

confidence: 99%

Multivariate State Estimation Technique Combined with Modified Information Entropy Weight Method for Steam Turbine Energy Efficiency Monitoring Study

Zhu

Cui

2021

Energies

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An energy efficiency monitoring method of the steam turbine system is studied in this paper. Multivariate state estimation technique (MSET) is utilized to compare the actual monitoring parameters and the healthy data of the equipment in normal working condition with a multi parameter estimation model. Due to the limitation of a single heat rate index in evaluating energy efficiency variation, the energy efficiency deviation degree combined with improved information entropy weight is proposed to judge the steam turbine’s operation condition levels. The index value in the modified weight method has been searched for more steady weight values calculated by information entropy values with small variation. Taking a 600 MW unit as an example, the energy efficiency levels of the unit under a 550 MW normal working condition are clustered into four groups, testifying the MSET model correctness and calculating the deviation degree value. Then, the energy efficiency status monitoring model is utilized to record residuals of actual data and estimated data during abnormal energy efficiency period. The residuals over deviation degree are then marked and judged as related with the abnormal data. The results show that the MSET model can timely and accurately judge the change of unit operation state, and the deviation degree calculated by the modified information entropy weight method can provide earlier warnings for the abnormal energy efficiency working conditions.

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Integration of Renewable Energy based Trigeneration Cycle: A Review

Cited by 9 publications

References 55 publications

Analysis of energy management schemes for renewable-energy-based smart homes against the backdrop of COVID-19

Analysis of energy management schemes for renewable-energy-based smart homes against the backdrop of COVID-19

Energy and exergy analysis of hybridization of solar, intercooled reheated gas turbine trigeneration cycle

Multivariate State Estimation Technique Combined with Modified Information Entropy Weight Method for Steam Turbine Energy Efficiency Monitoring Study

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