Risk assessment, dynamic analysis and multi-objective optimization of a solar-driven hybrid gas/steam power plant
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Risk assessment, dynamic analysis and multi‑objective optimization of a solar‑driven hybrid gas/steam power plant F. Amini Hajibashi1 · A. Arabkoohsar2 · M. Babaelahi1 Received: 10 June 2020 / Accepted: 29 August 2020 © Akadémiai Kiadó, Budapest, Hungary 2020
Abstract One of the critical issues in the design and optimization of power systems is considering the performance indices and safety problems simultaneously. In this paper, a new optimization procedure based on energy, exergy, and risk analyses of a solardriven combined gas/steam cycle power plant has been proposed and investigated. In the first step, the first and second laws of thermodynamics are used to evaluate the thermal and exergetic efficiencies of the plant. For this, precise modeling of the parabolic solar collectors and all the other components of the system has been performed. For the validation of thermodynamic modeling, the ThermoFlex simulation tool is employed. Then, the risk identification process has been performed considering the jet fire, the jet of combustion gas, and over-pressure as the main sources of risk in the power plant. To quantify each of these risks, appropriate correlations are presented, and the risk values are calculated as a function of the operational parameters of the cycle. In the next step, different multi-objective optimizations have been performed to achieve a configuration that has the highest efficiency and lowest risk. The results of optimizations show a good improvement in the thermodynamic efficiencies and risks of the system by 10.7%, 10.2%, and 1.21%, respectively. In the end, the dynamic analysis of the considered power plant is performed for optimal and base-case design. Keywords Thermodynamic analysis · Risk analysis · Solar combined power cycle · Multi-objective optimization · Pseudodynamic model List of symbols Aa Concentrated area/m2 Ar Receiver area/m2 AC Air compressor BFP–ECO Boiler feed pump, economizer side BFP–EVA Boiler feed pump, evaporator side CC Combustion chamber CEP Condensate extraction pump Cp Specific heat difference/J(kg °C)−1 Dc Cover diameter/m Dr Receiver diameter/m dp Pressure drop/kpa DEA Deaerator ECO Economizer FR Flow factor * A. Arabkoohsar [email protected] 1
Department of Mechanical Engineering, Qom University, Qom, Iran
Department of Energy Technology, Aalborg University, Aalborg, Denmark
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GT Gas turbine h Enthalpy/J hw External convection coefficient HRSG Heat recovery steam generator H-EVA High-pressure evaporator H-SH High-pressure superheater Kc Cover conduction coefficient Keff Convection coefficient L Collector length/m L-EVA Low-pressure evaporator L-SH Low pressure superheater LHV Lower heating value ma Air mass flow rate (kg s−1) mECO Economizer mass flow rate mEVA High-pressure evaporator mass flow rate mEVA2 Low-pressure evaporator mass flow rate mfg Flue gas mass flow rate mfw Feedwater mass flow rate mfuel Fuel mass flow rate mSHE Solar heat exchanger mass flow rate OILP Oil pump p Pressure (kpa)
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