Modeling and optimization of a binary geothermal power plant

被引:80
|
作者
Ghasemi, Hadi [1 ]
Paci, Marco [2 ]
Tizzanini, Alessio [2 ]
Mitsos, Alexander [1 ]
机构
[1] MIT, Dept Mech Engn, Cambridge, MA 02139 USA
[2] ENEL Ingn & Innovaz SpA, Area Tecn Ric, I-56122 Pisa, Italy
基金
加拿大自然科学与工程研究理事会;
关键词
Geothermal energy; Organic Rankine cycle; Optimization; Binary plant; ORGANIC RANKINE-CYCLE; WORKING FLUIDS; TEMPERATURE; DESIGN; ORC; SELECTION; RECOVERY;
D O I
10.1016/j.energy.2012.10.039
中图分类号
O414.1 [热力学];
学科分类号
摘要
A model is developed for an existing organic Rankine cycle (ORC) utilizing a low temperature geothermal source. The model is implemented in Aspen Plus (R) and used to simulate the performance of the existing ORC equipped with an air-cooled condensation system. The model includes all the actual characteristics of the components. The model is validated by approximately 5000 measured data in a wide range of ambient temperatures. The net power output of the system is maximized. The results suggest different optimal operation strategies based on the ambient temperature. Existing literature claims that no superheat is optimal for maximum performance of the system; this is confirmed only for low ambient temperatures. For moderate ambient temperatures (T-amb >= 1.7 degrees C) superheat maximizes net power output of the system. The value of the optimal superheat increases with increasing ambient temperature. The optimal operation boosts the total power produced in a year by 9%. In addition, a simpler and semi-analytic model is developed that enables very quick optimization of the operation of the cycle. Based on the pinch condition at the condenser, a simple explicit formula is derived that predicts the outlet pressure of the turbine as a function of mass flow rate of working fluid. (C) 2012 Elsevier Ltd. All rights reserved.
引用
收藏
页码:412 / 428
页数:17
相关论文
共 50 条
  • [41] Multiple regression analysis of performance parameters of a binary cycle geothermal power plant
    Karadas, Murat
    Celik, H. Murat
    Serpen, Umran
    Toksoy, Macit
    [J]. GEOTHERMICS, 2015, 54 : 68 - 75
  • [42] Environmental assessment of a binary geothermal sourced power plant accompanied by exergy analysis
    Basogul, Yusuf
    [J]. ENERGY CONVERSION AND MANAGEMENT, 2019, 195 : 492 - 501
  • [43] Multi-objective particle swarm optimization of binary geothermal power plants
    Clarke, Joshua
    McLeskey, James T., Jr.
    [J]. APPLIED ENERGY, 2015, 138 : 302 - 314
  • [44] Thermodynamic analysis and optimization of a flash-binary geothermal power generation system
    Wang, Jianyong
    Wang, Jiangfeng
    Dai, Yiping
    Zhao, Pan
    [J]. GEOTHERMICS, 2015, 55 : 69 - 77
  • [45] Thermodynamic Optimization of a Geothermal Power Plant with a Genetic Algorithm in Two Stages
    Ehyaei, Mehdi A.
    Ahmadi, Abolfazl
    Rosen, Marc A.
    Davarpanah, Afshin
    [J]. PROCESSES, 2020, 8 (10) : 1 - 16
  • [46] Thermodynamic analysis and optimization of an ORC hybrid geothermal–solar power plant
    Rafika Maali
    Tahar Khir
    [J]. Euro-Mediterranean Journal for Environmental Integration, 2023, 8 : 341 - 352
  • [47] Thermodynamic re-assessment of a geothermal binary power plant operated in a moderate-temperature geothermal field
    Ozcan, Zeynep
    Akkurt, Gulden Gokcen
    [J]. INTERNATIONAL JOURNAL OF EXERGY, 2023, 40 (02) : 162 - 181
  • [48] Optimization of thermodynamic performance with simulated annealing algorithm: A geothermal power plant
    Cetin, Gurcan
    Kecebas, Ali
    [J]. RENEWABLE ENERGY, 2021, 172 : 968 - 982
  • [49] The 125 MW Upper Mahiao geothermal power plant - Largest geothermal steam/binary combined cycle plant starts-up
    Forte, N
    [J]. GEOTHERMAL DEVELOPMENT IN THE PACIFIC RIM, 1996, 20 : 743 - 747
  • [50] Modeling and simulation of the production process of electrical energy in a geothermal power plant
    Sanchez, Eduardo
    Torres, Carlos F.
    Guillen, Pablo
    Larrazabal, German
    [J]. MATHEMATICAL AND COMPUTER MODELLING, 2013, 57 (9-10) : 2140 - 2148