scholarly journals Parametrized Analysis and Multi-Objective Optimization of Supercritical CO2 (S-CO2) Power Cycles Coupled with Parabolic Trough Collectors

2020 ◽  
Vol 10 (9) ◽  
pp. 3123 ◽  
Author(s):  
Lei Sun ◽  
Yuqi Wang ◽  
Ding Wang ◽  
Yonghui Xie
Keyword(s):  
Solar Energy ◽  
Supercritical Co2 ◽  
Inlet Temperature ◽  
Specific Work ◽  
Parabolic Trough ◽  
Turbine Inlet Temperature ◽  
Power Cycles ◽  
Multi Objective ◽  
Temperature And Pressure ◽  
Recompression Cycle

Supercritical CO2 (S-CO2) Brayton cycles have become an effective way in utilizing solar energy, considering their advantages. The presented research discusses a parametrized analysis and systematic comparison of three S-CO2 power cycles coupled with parabolic trough collectors. The effects of turbine inlet temperature and pressure, compressor inlet temperature, and pressure on specific work, overall efficiency, and cost of core equipment of different S-CO2 Brayton cycles are discussed. Then, the two performance criteria, including specific work and cost of core equipment, are compared, simultaneously, between different S-CO2 cycle layouts after gaining the Pareto sets from multi-objective optimizations using genetic algorithm. The results suggest that the simple recuperation cycle layout shows more excellent performance than the intercooling cycle layout and the recompression cycle layout in terms of cost, while the advantage in specific work of the intercooling cycle layout and the recompression cycle layout is not obvious. This study can be useful in selecting cycle layout using solar energy by the parabolic trough solar collector when there are requirements for the specific work and the cost of core equipment. Moreover, high turbine inlet temperature is recommended for the S-CO2 Brayton cycle using solar energy.

Thermodynamic and Economic Analysis and Multi-Objective Optimization of Supercritical CO2 Brayton Cycles

2015 ◽  
Author(s):  
Hang Zhao ◽  
Qinghua Deng ◽  
Wenting Huang ◽  
Zhenping Feng
Keyword(s):  
Supercritical Co2 ◽  
Exergy Efficiency ◽  
Temperature Cycle ◽  
Inlet Temperature ◽  
Brayton Cycle ◽  
Multi Objective Optimization ◽  
Turbine Inlet Temperature ◽  
Multi Objective ◽  
Turbine Inlet ◽  
Thermodynamic Performance

Supercritical CO2 Brayton cycles (SCO2BC) offer the potential of better economy and higher practicability due to their high power conversion efficiency, moderate turbine inlet temperature, compact size as compared with some traditional working fluids cycles. In this paper, the SCO2BC including the SCO2 single-recuperated Brayton cycle (RBC) and recompression recuperated Brayton cycle (RRBC) are considered, and flexible thermodynamic and economic modeling methodologies are presented. The influences of the key cycle parameters on thermodynamic performance of SCO2BC are studied, and the comparative analyses on RBC and RRBC are conducted. Based on the thermodynamic and economic models and the given conditions, the Non-dominated Sorting Genetic Algorithm II (NSGA-II) is used for the Pareto-based multi-objective optimization of the RRBC, with the maximum exergy efficiency and the lowest cost per power ($/kW) as its objectives. In addition, the Artificial Neural Network (ANN) is chosen to establish the relationship between the input, output, and the key cycle parameters, which could accelerate the parameters query process. It is observed in the thermodynamic analysis process that the cycle parameters such as heat source temperature, turbine inlet temperature, cycle pressure ratio, and pinch temperature difference of heat exchangers have significant effects on the cycle exergy efficiency. And the exergy destruction of heat exchanger is the main reason why the exergy efficiency of RRBC is higher than that of RBC under the same cycle conditions. Compared with the two kinds of SCO2BC, RBC has a cost advantage from economic perspective, while RRBC has a much better thermodynamic performance, and could rectify the temperature pinching problem that exists in RBC. Therefore, RRBC is recommended in this paper. Furthermore, the Pareto front curve between the cycle cost/ cycle power (CWR) and the cycle exergy efficiency is obtained by multi-objective optimization, which indicates that there is a conflicting relation between them. The optimization results could provide an optimum trade-off curve enabling cycle designers to choose their desired combination between the efficiency and cost. Moreover, the optimum thermodynamic parameters of RRBC can be predicted with good accuracy using ANN, which could help the users to find the SCO2BC parameters fast and accurately.

Multi-Objective Optimisation of the Humid Air Turbine

2007 ◽  
Author(s):  
Ronan M. Kavanagh ◽  
Geoffrey T. Parks ◽  
Mitsuru Obana
Keyword(s):  
Inlet Temperature ◽  
System Control ◽  
Primary System ◽  
Specific Work ◽  
Control Variables ◽  
Humid Air ◽  
Power Cycle ◽  
Multi Objective ◽  
Air Turbine ◽  
The Impact

Optimisation of the Humid Air Turbine (HAT) power cycle has proven an interesting challenge in multi-variate and multi-objective optimisation. A multi-objective Tabu Search optimisation algorithm, developed in the Cambridge Engineering Design Centre, has been applied to this humid power cycle. A tradeoff surface is generated to investigate the impact of nine primary system control variables on the performance (efficiency, specific work and cost of electricity) of the system. This optimisation tool was chosen for its proven robustness and flexibility in handling highly constrained, multi-variate problems. The algorithm generates a Pareto-set of optimal candidate designs, allowing the designer to analyse the trade-off between performance measures such as efficiency and cost when selecting the ultimate system operating point. The study is primarily a global optimisation, with attention being paid to the primary system control variables: pressure ratio, turbine inlet temperature, IP/HP pressure split, water flowrate distribution and heat exchanger effectiveness.

A Systematic Comparison and Multi-Objective Optimisation of Humid Power Cycles: Part II—Economics

2008 ◽  
Author(s):  
Ronan M. Kavanagh ◽  
Geoffrey T. Parks
Keyword(s):  
Power Systems ◽  
Gas Turbine ◽  
Search Algorithm ◽  
Working Fluid ◽  
Specific Work ◽  
Power Cycles ◽  
System Parameters ◽  
Multi Objective ◽  
Fluid Properties ◽  
The Impact

The STIG, HAT and TOPHAT cycles lie at the centre of the debate on which humid power cycle will deliver optimal performance when applied to an aero-derivative gas turbine and, indeed, when such cycles will be implemented. Of these humid cycles, it has been claimed that the TOPHAT cycle has the highest efficiency and specific work, followed closely by the HAT (Humid Air Turbine) and then the STIG (STeam Injected Gas turbine) cycle. In this study, the systems have been simulated using consistent thermodynamic and economic models for the components and working fluid properties, allowing a consistent and non-biased appraisal of these systems. Part 1 of these two papers focussed on the thermodynamic performance and the impact of the system parameters on the performance, part 2 studies the economic performance of these cycles. The three humid power systems and up to ten system parameters are optimised using a multi-objective Tabu Search algorithm, developed in the Cambridge Engineering Design Centre.

Thermodynamic and Economic Analysis and Multi-objective Optimization of Supercritical CO2 Brayton Cycles

2016 ◽  
Vol 138 (8) ◽  
Author(s):  
Hang Zhao ◽  
Qinghua Deng ◽  
Wenting Huang ◽  
Dian Wang ◽  
Zhenping Feng
Keyword(s):  
Supercritical Co2 ◽  
Pressure Ratio ◽  
Economic Modeling ◽  
Exergy Efficiency ◽  
Temperature Cycle ◽  
Inlet Temperature ◽  
Brayton Cycle ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Thermodynamic Performance

Supercritical CO2 Brayton cycles (SCO2BC) including the SCO2 single-recuperated Brayton cycle (RBC) and recompression recuperated Brayton cycle (RRBC) are considered, and flexible thermodynamic and economic modeling methodologies are presented. The influences of the key cycle parameters on thermodynamic performance of SCO2BC are studied, and the comparative analyses on RBC and RRBC are conducted. Nondominated Sorting Genetic Algorithm II (NSGA-II) is selected for the Pareto-based multi-objective optimization of the RRBC, with the maximum exergy efficiency and the lowest cost per power (k$/kW) as its objectives. Artificial neural network (ANN) is chosen to accelerate the parameters query process. It is shown that the cycle parameters such as heat source temperature, turbine inlet temperature, cycle pressure ratio, and pinch temperature difference of heat exchangers have significant effects on the cycle exergy efficiency. The exergy destruction of heat exchanger is the main reason why the exergy efficiency of RRBC is higher than that of the RBC under the same cycle conditions. RBC has a cost advantage from economic perspective, while RRBC has a much better thermodynamic performance, and could rectify the temperature pinching problem that exists in RBC. It is also shown that there is a conflicting relationship between the cycle cost/cycle power (CWR) and the cycle exergy efficiency. The optimization results could provide an optimum tradeoff curve enabling cycle designers to choose their desired combination between the efficiency and cost. ANN could help the users to find the SCO2BC parameters fast and accurately.

scholarly journals Multi-objective optimization on supercritical CO2 recompression brayton cycle using Kriging surrogate model

2017 ◽  
Vol 21 (suppl. 1) ◽  
pp. 309-316
Author(s):  
Lei Sun ◽  
Chongyu Wang ◽  
Di Zhang
Keyword(s):  
Supercritical Co2 ◽  
Thermodynamic Cycle ◽  
Brayton Cycle ◽  
Time Cost ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Research Fields ◽  
Cycle Efficiency ◽  
Recompression Cycle ◽  
Selection Of

Supercritical CO2 cycle has become one of the most popular research fields of thermal science. The selection of operation parameters on thermodynamic cycle process is an important task. The computational model of supercritical CO2 recompression cycle is built to solve the multi-objective problem in this paper. Then, the optimization of parameters is performed based on genetic algorithm. Several Kriging models are also used to reduce the quantity of samples. According to the calculation, the influence of sample quantity on the result and the time cost is obtained. The results show that it is required to improve the heat transfer when improvement of the cycle efficiency is desired.

scholarly journals 100s and 1000s Mw Open and Semi-Closed Cycle Gas Turbines for Base and Peak Operation

1974 ◽  
Author(s):  
V. V. Uvarov ◽  
V. S. Beknev ◽  
E. A. Manushin
Keyword(s):  
Gas Turbine ◽  
Gas Turbines ◽  
Pressure Ratio ◽  
Simple Cycle ◽  
Inlet Temperature ◽  
Closed Cycle ◽  
Turbine Inlet Temperature ◽  
Unit Capacity ◽  
Temperature And Pressure ◽  
Different Levels

There are two different approaches to develop the gas turbines for power. One can get some megawatts by simple cycle or by more complex cycle units. Both units require very different levels of turbine inlet temperature and pressure ratio for the same unit capacity. Both approaches are discussed. These two approaches lead to different size and efficiencies of gas turbine units for power. Some features of the designing problems of such units are discussed.

A Systematic Comparison and Multi-Objective Optimisation of Humid Power Cycles: Part I—Thermodynamics

2008 ◽  
Author(s):  
Ronan M. Kavanagh ◽  
Geoffrey T. Parks
Keyword(s):  
Power Systems ◽  
Gas Turbine ◽  
Search Algorithm ◽  
Working Fluid ◽  
Specific Work ◽  
Power Cycles ◽  
System Parameters ◽  
Multi Objective ◽  
Fluid Properties ◽  
The Impact

The STIG, HAT and TOPHAT cycles lie at the centre of the debate on which humid power cycle will deliver optimal performance when applied to an aero-derivative gas turbine and, indeed, when such cycles will be implemented. Of these humid cycles, it has been claimed that the TOPHAT cycle has the highest efficiency and specific work, followed closely by the HAT (Humid Air Turbine) and then the STIG (STeam Injected Gas turbine) cycle. In this study, the systems have been simulated using consistent thermodynamic and economic models for the components and working fluid properties, allowing a consistent and non-biased appraisal of these systems. Part 1 of these two papers focusses purely on the thermodynamic performance and the impact of the system parameters on the performance, part 2 will study the economic performance. The three humid power systems and up to ten system parameters are optimised using a multi-objective Tabu Search algorithm, developed in the Cambridge Engineering Design Centre.

Effects of Steam Injection on the Performance of Gas Turbine Power Cycles

1979 ◽  
Vol 101 (2) ◽  
pp. 217-227 ◽  
Author(s):  
W. E. Fraize ◽  
C. Kinney
Keyword(s):  
Gas Turbine ◽  
Waste Heat ◽  
Steam Injection ◽  
Combined Cycle ◽  
Thermodynamic Efficiency ◽  
Inlet Temperature ◽  
Exhaust Gas ◽  
Turbine Inlet Temperature ◽  
Power Cycles ◽  
Determine Effect

The effect of injecting steam generated by exhaust gas waste heat into a gas turbine with 3060°R turbine inlet temperature has been analyzed. Two alternate steam injection cycles are compared with a combined cycle using a conventional steam bottoming cycle. A range of compression ratios (8, 12, 16, and 20) and water mass injection ratios (0 to 0.4) were analyzed to determine effect on net turbine power output per pound of air and cycle thermodynamic efficiency. A water/fuel cost tradeoff analysis is also provided. The results indicate promising performance and economic advantages of steam injected cycles relative to more conventional utility power cycles. Application to coal-fired configuration is briefly discussed.

scholarly journals Diurnal Temperature and Pressure Effects on Axial Turbomachinery Stability in Solid Oxide Fuel Cell-Gas Turbine Hybrid Systems

2011 ◽  
Vol 8 (3) ◽  
Author(s):  
James D. Maclay ◽  
Jacob Brouwer ◽  
G. Scott Samuelsen
Keyword(s):  
Fuel Cell ◽  
Ambient Temperature ◽  
Gas Turbine ◽  
Solid Oxide ◽  
Inlet Temperature ◽  
Electrolyte Temperature ◽  
Turbine Inlet Temperature ◽  
Compressor Surge ◽  
Turbine Shaft ◽  
Temperature And Pressure

A dynamic model of a 100 MW solid oxide fuel cell-gas turbine hybrid system has been developed and subjected to perturbations in diurnal ambient temperature and pressure as well as load sheds. The dynamic system responses monitored were the fuel cell electrolyte temperature, gas turbine shaft speed, turbine inlet temperature, and compressor surge. Using a control strategy that primarily focuses on holding fuel cell electrolyte temperature constant and secondarily on maintaining gas turbine shaft speed, safe operation was found to occur for expected ambient pressure variation ranges and for ambient temperature variations up to 28 K when tested nonsimultaneously. When ambient temperature and pressure were varied simultaneously, stable operation was found to occur when the two are in phase but not when the two are out of phase. The latter case leads to shaft overspeed. Compressor surge was found to be more likely when the system is subjected to a load shed initiated at minimum ambient temperature rather than at maximum ambient temperature. Fuel cell electrolyte temperature was found to be well-controlled except in the case of shaft overspeeds. Turbine inlet temperature remained in safe bounds for all cases.

The STEP 10 MWe sCO2 Pilot Demonstration Status Update

2020 ◽  
Author(s):  
John Marion ◽  
Brian Lariviere ◽  
Aaron McClung ◽  
Jason Mortzheim ◽  
Robin Ames
Keyword(s):  
Power Generation ◽  
Supercritical Co2 ◽  
Elevated Temperatures ◽  
Waste Heat ◽  
San Antonio ◽  
Test Facility ◽  
Working Fluid ◽  
Inlet Temperature ◽  
Power Cycles ◽  
Wide Range

Abstract A team led by Gas Technology Institute (GTI®), Southwest Research Institute® (SwRI®) and General Electric Global Research (GE-GR), along with the University of Wisconsin and Natural Resources Canada (NRCan), is actively executing a project called “STEP” [Supercritical Transformational Electric Power project], to design, construct, commission, and operate an integrated and reconfigurable 10 MWe sCO2 [supercritical CO2] Pilot Plant Test Facility. The $122* million project is funded $84 million by the US DOE’s National Energy Technology Laboratory (NETL Award Number DE-FE0028979) and $38* million by the team members, component suppliers and others interested in sCO2 technology. The facility is currently under construction and is located at SwRI’s San Antonio, Texas, USA campus. This project is a significant step toward sCO2 cycle based power generation commercialization and is informing the performance, operability, and scale-up to commercial plants. Significant progress has been made. The design phase is complete (Phase 1) and included procurements of long-lead time deliver components. Now well into Phase 2, most major equipment is in fabrication and several completed and delivered. These efforts have already provided valuable project learnings for technology commercialization. A ground-breaking was held in October of 2018 and now civil work and the construction of a dedicated 25,000 ft2 building has progressed and is largely completed at the San Antonio, TX, USA project site. Supercritical CO2 (sCO2) power cycles are Brayton cycles that utilize supercritical CO2 working fluid to convert heat to power. They offer the potential for higher system efficiencies than other energy conversion technologies such as steam Rankine or Organic Rankine cycles this especially when operating at elevated temperatures. sCO2 power cycles are being considered for a wide range of applications including fossil-fired systems, waste heat recovery, concentrated solar power, and nuclear power generation. By the end of this 6-year STEP pilot demo project, the operability of the sCO2 power cycle will be demonstrated and documented starting with facility commissioning as a simple closed recuperated cycle configuration initially operating at a 500°C (932°F) turbine inlet temperature and progressing to a recompression closed Brayton cycle technology (RCBC) configuration operating at 715°C (1319 °F).

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