Optimal Unit Sizing of Gas Turbine Cogeneration Systems Based on Mixed-Integer Bilinear Programming

2003 ◽  
Vol 2003.13 (0) ◽  
pp. 325-328
Author(s):  
Satoshi GAMOU ◽  
Koichi ITO ◽  
Ryohei YOKOYAMA ◽  
Takanori YOKOYAMA
Keyword(s):  
Gas Turbine ◽  
Bilinear Programming ◽  
Mixed Integer

Multi-objective optimization of a recuperative gas turbine cycle using non-dominated sorting genetic algorithm

2011 ◽  
Vol 225 (8) ◽  
pp. 1041-1051 ◽  
Author(s):  
H Sayyaadi ◽  
H R Aminian
Keyword(s):  
Genetic Algorithm ◽  
Gas Turbine ◽  
Heat Exchangers ◽  
Mixed Integer ◽  
Design Stage ◽  
Tube Length ◽  
Pareto Optimal ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Gas Turbine Cycle

A regenerative gas turbine cycle with two particular tubular recuperative heat exchangers in parallel is considered for multi-objective optimization. It is assumed that tubular recuperative heat exchangers and its corresponding gas cycle are in design stage simultaneously. Three objective functions including the purchased equipment cost of recuperators, the unit cost rate of the generated power, and the exergetic efficiency of the gas cycle are considered simultaneously. Geometric specifications of the recuperator including tube length, tube outside/inside diameters, tube pitch, inside shell diameter, outer and inner tube limits of the tube bundle and the total number of disc and doughnut baffles, and main operating parameters of the gas cycle including the compressor pressure ratio, exhaust temperature of the combustion chamber and the air mass flowrate are considered as decision variables. Combination of these objectives anddecision variables with suitable engineering and physical constraints (including NO x and CO emission limitations) comprises a set of mixed integer non-linear problems. Optimization programming in MATLAB is performed using one of the most powerful and robust multi-objective optimization algorithms, namely non-dominated sorting genetic algorithm. This approach is applied to find a set of Pareto optimal solutions. Pareto optimal frontier is obtained, and a final optimal solution is selected in a decision-making process.

Optimal Sizing of a Gas Turbine Cogeneration Plant in Consideration of Its Operational Strategy

1994 ◽  
Vol 116 (1) ◽  
pp. 32-38 ◽  
Author(s):  
R. Yokoyama ◽  
K. Ito ◽  
Y. Matsumoto
Keyword(s):  
Programming Problem ◽  
Gas Turbine ◽  
Mixed Integer ◽  
Turbine Plant ◽  
Operational Strategies ◽  
Integer Linear Programming Problem ◽  
Energy Demands ◽  
Annual Total ◽  
Planning Problems ◽  
Annual Total Cost

An optimal planning method is proposed for the fundamental design of cogeneration plants. Equipment capacities and utility maximum demands are determined so as to minimize the annual total cost in consideration of the plants’ annual operational strategies for the variations of both electricity and thermal energy demands. These sizing and operational planning problems are formulated as a nonlinear programming problem and a mixed-integer linear programming problem, respectively. They are solved efficiently in consideration of their hierarchical relationship by a penalty method. A numerical example about a gas turbine plant is given to ascertain the validity and effectiveness of the proposed method.

Short-Term Optimization of a Combined Cycle Power Plant Integrated With an Inlet Air Conditioning Unit

2020 ◽  
Author(s):  
Weimar Mantilla ◽  
José García ◽  
Rafael Guédez ◽  
Alessandro Sorce
Keyword(s):  
Power Plant ◽  
Gas Turbine ◽  
Gas Turbines ◽  
Air Conditioning ◽  
Combined Cycle ◽  
Plant Performance ◽  
Mixed Integer ◽  
Environmental Load ◽  
Turbine Inlet ◽  
The Impact

Abstract Under new scenarios with high shares of variable renewable electricity, combined cycle gas turbines (CCGT) are required to improve their flexibility, in terms of ramping capabilities and part-load efficiency, to help balance the power system. Simultaneously, liberalization of electricity markets and the complexity of its hourly price dynamics are affecting the CCGT profitability, leading the need for optimizing its operation. Among the different possibilities to enhance the power plant performance, an inlet air conditioning unit (ICU) offers the benefit of power augmentation and “minimum environmental load” (MEL) reduction by controlling the gas turbine inlet temperature using cold thermal energy storage and a heat pump. Consequently, an evaluation of a CCGT integrated with this inlet conditioning unit including a day-ahead optimized operation strategy was developed in this study. To establish the hourly dispatch of the power plant and the operation mode of the inlet conditioning unit to either cool down or heat up the gas turbine inlet air, a mixed-integer linear optimization (MILP) was formulated using MATLAB, aiming to maximize the operational profit of the plant within a 24-hours horizon. To assess the impact of the proposed unit operating under this dispatch strategy, historical data of electricity and natural gas prices, as well as meteorological data and CO2 emission allowances price, have been used to perform annual simulations of a reference power plant located in Turin, Italy. Furthermore, different equipment capacities and parameters have been investigated to identify trends of the power plant performance. Lastly, a sensitivity analysis on market conditions to test the control strategy response was also considered. Results indicate that the inlet conditioning unit, together with the dispatch optimization, increases the power plant’s operational profit by achieving a wider operational range, particularly important during peak and off-peak periods. For the specific case study, it is estimated that the net present value of the CCGT integrated with the ICU is 0.5% higher than the power plant without the unit. In terms of technical performance, results show that the unit reduces the minimum environmental load by approximately 1.34% and can increase the net power output by 0.17% annually.

Mixed-integer bilinear programming problems

1993 ◽  
Vol 59 (1-3) ◽  
pp. 279-305 ◽  
Author(s):  
Warren P. Adams ◽  
Hanif D. Sherali
Keyword(s):  
Bilinear Programming ◽  
Mixed Integer

Sizing of a Gas Turbine for Repowering of Cogeneration Power Plant Ljubljana by Mathematical Optimisation

1996 ◽  
Author(s):  
Mihael Gabriel Tomšič ◽  
Olgica Perović
Keyword(s):  
Power Plant ◽  
Gas Turbine ◽  
Optimal Operation ◽  
Hot Water ◽  
Mixed Integer ◽  
Heat Recovery Boiler ◽  
Continuous Variables ◽  
District Heating System ◽  
Operational Strategy ◽  
Steam Extraction

The paper deals with optimal sizing of a gas turbine for repowering of cogeneration power plant Ljubljana considering possible plant operational strategy with respect to variations of electric and heat loads and energy costs. CHP plant is a main source for the Ljubljana town district heating system. Existing plant consists of two condensing steam turbines with steam extraction, back pressure turbine with steam extraction, auxiliary steam and hot water boilers for peak heat load production. This system delivers up to 111 MW into the power grid and up to 348 MW of heat. Repowering with gas turbine generator set with additionally fired heat recovery boiler is considered. For uncoupling heat and power generation a heat storage tank is assumed. For sizing of new equipment and plant operational strategy a model based on mixed-integer linear programming was developed. Zero - one integer variables are adopted to indicate the on/off status of operation, continuous variables to indicate the operational level of each constituent equipment and an optimal solution is derived by branch and bound method. Two prospective sizes of TG sets were tested for range of assumptions regarding power purchase tariff schedules. Different optimal operation policies resulted. The study provides background for contract negotiation and for investment decisions.

Robust Optimal Operation of a Gas Turbine Cogeneration Plant Under Uncertain Energy Demands

2014 ◽  
Vol 137 (2) ◽  
Author(s):  
Ryohei Yokoyama ◽  
Masashi Ohkura ◽  
Tetsuya Wakui
Keyword(s):  
Gas Turbine ◽  
Energy Supply ◽  
Numerical Study ◽  
Optimization Method ◽  
Optimal Operation ◽  
Mixed Integer ◽  
Cogeneration Plant ◽  
Co2 Emission Reduction ◽  
Operational Strategy ◽  
Energy Demands

Some optimal operation methods based on the mixed-integer linear programming (MILP) have been proposed to operate energy supply plants properly from the viewpoints of economics, energy saving, and CO2 emission reduction. However, most of the methods are effective only under certain energy demands. In operating an energy supply plant actually, it is necessary to determine the operational strategy properly based on predicted energy demands. In this case, realized energy demands may differ from the predicted ones. Therefore, it is necessary to determine the operational strategy so that it is robust against the uncertainty in energy demands. In this paper, an optimization method based on the MILP is proposed to conduct the robust optimal operation of energy supply plants under uncertain energy demands. The uncertainty in energy demands is expressed by their intervals. The operational strategy is determined to minimize the maximum regret in the operational cost under the uncertainty. In addition, a hierarchical relationship among operation modes and on/off states of equipment, energy demands, and energy flow rates of equipment is taken into account. First, a general formulation of a robust optimal operation problem is presented, which is followed by a general solution procedure. Then, in a numerical study, the proposed method is applied to a gas turbine cogeneration plant for district energy supply. Through the study, some features of the robust optimal operation are clarified, and the validity and effectiveness of the proposed method are ascertained.

Part Load Behavior Optimization of Hybrid Coal and Gas Fired Combined Cycles Including Deactivation of Components

2002 ◽  
Author(s):  
Janpeter Ku¨hnel ◽  
Reza S. Abhari
Keyword(s):  
Power Plant ◽  
Objective Function ◽  
Gas Turbine ◽  
Mixed Integer ◽  
Operation Strategy ◽  
Part Load ◽  
Optimization Parameters ◽  
Cycle Efficiency ◽  
Load Behavior ◽  
Fuel Costs

This paper presents a methodology to optimize the part load behavior of complex power plant cycles. As free optimization parameters the traditional continuous control parameter and the activation/deactivation of defined plant components are considered resulting in a mixed integer non-linear programming problems (MINLP). The procedure starts with a continuous process on either side of the non-linearity in part load, while refining the steps as it approaches the discontinuity. It is shown that good convergence around the non-linearity can be found with the present scheme. For part load operation a number of continuous and binary free optimization parameters are available creating a challenging optimization problem. The developed procedure is applied to a conventional steam cycle power plant, which is parallel repowered with a modern gas turbine. The resulting power plant layout is a hybrid coal and gas fired combined cycle. As objective function the maximized overall thermal efficiency and the minimized fuel costs are two examples chosen. Investigating the minimized fuel costs as the objective function the optimized operation strategy is found to be an unique function of the fuel price ratio between coal and gas for the chosen layout. Finally we show, that the operation strategy can be notably improved by considering the deactivation of cycle components for minimizing the fuel costs and for maximizing the cycle efficiency. For example the cycle efficiency can be improved up to 2% by deactivating the high pressure feed water preheating. The fuel costs are reduced by 20% for a particular load point by deactivating the gas turbine.

Effect of Inlet Air Cooling by Ice Storage on Unit Sizing of a Gas Turbine Cogeneration Plant

2004 ◽  
Vol 126 (2) ◽  
pp. 351-357 ◽  
Author(s):  
Ryohei Yokoyama ◽  
Koichi Ito
Keyword(s):  
Gas Turbine ◽  
Power Output ◽  
Gas Turbines ◽  
Maximum Power ◽  
Mixed Integer ◽  
Ice Storage ◽  
Air Cooling ◽  
Cogeneration Plant ◽  
Maximum Heat ◽  
Maximum Power Output

In the commercial sector, heat and power demands peak in the summer daytime because of high space cooling demands, and cogeneration plants are required to produce maximum heat and power to meet their demands. However, gas turbine cogeneration plants have the disadvantage of decreases in maximum power output in the summer daytime, which reduces the availability of gas turbines. One of the ways to avoid the aforementioned disadvantage is to cool inlet air and augment maximum power output. In addition, one of the ways for inlet air cooling is to make ice by driving electric compression refrigerators using off-peak power generated during the nighttime, store it in ice banks, and use its heat for inlet air cooling during the on-peak period. The objective of this paper is to investigate the effect of inlet air cooling by ice storage on the unit sizing and cost of a gas turbine cogeneration plant. An optimal unit sizing method based on the mixed-integer linear programming is used to rationally determine equipment capacities and operational strategies of the plant. A numerical study is conducted, in which the gas turbine cogeneration plants with and without inlet air cooled by ice storage are compared with each other, and the effect of inlet air cooling on the equipment capacities as well as the annual total cost and its items is clarified.

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