1990
DOI: 10.1115/1.2906466
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Influence of Fuel Cost on the Operation of a Gas Turbine-Waste Heat Boiler Cogeneration Plant

Abstract: The influence of fuel cost on the operation is investigated for a gas turbine-waste heat boiler cogeneration plant by an optimal operational planning method. A planning method is first presented by which the operational policy of each piece of constituent equipment is determined so as to minimize the operational cost. Then, a case study is performed for a cogeneration plant used for district heating and cooling. Through the study, it is made clear how the optimal operational policy and the economic or energy c… Show more

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Cited by 31 publications
(12 citation statements)
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“…In the operational planning problem at the lower level, for a system with the equipment capacities and maximum contract demands of utilities given at each searching step, the optimal values of the variables y R ( R ) and z R ( R ) expressing the operational strategy are determined for each combination R at the sampling time t so as to minimize the hourly energy charge included in Equation (1) subject to Equation (2), and the annual energy charge is evaluated. Here, the optimal values of the variables y R ( R ) and z R ( R ) are determined using the optimal operational planning method proposed by the authors (Ito et al, 1990). Note that the constraints of Equations (3)}(5) are not explicitly considered at this level.…”
Section: Solution Methods Of the Problemmentioning
confidence: 99%
“…In the operational planning problem at the lower level, for a system with the equipment capacities and maximum contract demands of utilities given at each searching step, the optimal values of the variables y R ( R ) and z R ( R ) expressing the operational strategy are determined for each combination R at the sampling time t so as to minimize the hourly energy charge included in Equation (1) subject to Equation (2), and the annual energy charge is evaluated. Here, the optimal values of the variables y R ( R ) and z R ( R ) are determined using the optimal operational planning method proposed by the authors (Ito et al, 1990). Note that the constraints of Equations (3)}(5) are not explicitly considered at this level.…”
Section: Solution Methods Of the Problemmentioning
confidence: 99%
“…As aforementioned, for the operation of cogeneration plants under certain energy demands, a method based on the MILP has been proposed to operate the plants rationally so that they attain the minimum operational cost for heat and power supply, and its effectiveness has been ascertained by comparing this cost minimizing strategy with conventional electric-/thermal-following ones [1]. In this method, however, dynamic characteristics of equipment are neglected, and the operational strategy of equip ment is determined statically and independently at each sampling time interval which is set to take account of variations in energy demands.…”
Section: Previous Researchmentioning
confidence: 99%
“…The hourly operational cost can be expressed by a linear equation with respect only to xik) as fi^(x(k)). For concrete forms of f/^ and h/¿, refer to the previous paper [1] and the Appendix. Equations (3) to (6) are applied to the pieces of equipment whose minimum up and down times are considered and are added to the basic constraints of Eq.…”
Section: Ar = T/kmentioning
confidence: 99%
“…For the operational planning of cogeneration plants, a method based on the mixed-integer linear programming (MILP) has been proposed to operate the plants rationally so that they attain the minimum operational cost for heat and power supply, and its effectiveness has been ascertained by comparing this costminimizing strategy with conventional electric/thermal-foUowing ones [1]. In this method, however, dynamic characteristics of equipment, by which states such as mass flow rates, pressures, and temperatures of equipment change transiently, are neglected, and the operational strategy of equipment is determined statically and independently at each sampling time interval that is set to take account of variations in energy demands.…”
Section: Introductionmentioning
confidence: 99%