Showing papers by "Umberto Desideri published in 1997"

Water recovery from HAT cycle exhaust gas: a possible solution for reducing stack temperature problems

Abstract: For several years the injection of steam into the combustion chamber has represented a common way to improve the performance of gas turbine power plants, increasing both the power output and the efficiency and reducing, at the same time, NOx emissions. Starting from the first STeam Injected Gas turbine (GE STIG) cycles, several types of gas turbine cycle with steam or water injection (dual fluid cycles) have been proposed. Among them, the most interesting results were obtained with the Cheng and the humid air turbine (HAT) cycles. In particular, the HAT cycle (which is a gas turbine cycle featuring intercooled compression, an air–water mixing evaporator before the combustion chamber, and a recovery system for the exhaust gases) has been identified as a promising way to generate electric power at high efficiency, low cost and with a system that is simple compared with the combined cycles (Stecco et al. and Gallo et al.). However the associated water consumption, about 1210–2420 m3 per day for a 100 MW unit, continues to represent a significant drawback to the spread of the HAT cycle, as well as of other steam injected cycles. In fact, such a high spread water consumption means high operational costs for water treatment, eventual legislative restrictions limiting the use of water, not to mention the environmental impact of the depletion of water resources. Some different solutions to those problems have been proposed, such as the introduction of a mixing exchanger (Bettagli and Facchini), or of a surface exchanger (Bombarda, Bidini et al.) on the exhaust of the cycle to recover water and heat from the flue gases. Further cooling of the exhaust gases, which is necessary to condense the stream fraction, lowers the stack temperature so much that the stack draft may become too low to prevent sufficient diffusion of the emission; this is one of the main drawbacks for large-scale water and heat recovery. One of the possible solutions is the introduction an induced draft fan (IDF), the other is recuperative heating of the exhaust gases after the condenser. The aim of this paper is to estimate the cycle performance with an IDF placed between the turbine and the stack. It is therefore important to take account of the reduction of the stack draft and find some means to overcome it. The results show that the IDF can increase the cycle efficiency and that a significant amount of heat and water can be recovered from the exhaust gases. © 1997 John Wiley & Sons, Ltd.

Use of Artificial Neural Networks for the Simulation of Combined Cycle Transients

Abstract: Due to techno-economic assets, the demand of combined cycles (CC) is currently growing. Nowadays, in a diversified electricity mix, these plants are often used on a load cycling duty or in the intermediate load range. The ability to start quickly and reliably may be a decisional criterion for the selection of the plant, in addition to the design performance, the cost and the pollutant emissions. Therefore, together with the simulation of CC transients, a proper monitoring system aimed at keeping high plant performance during the transients is required.With the help of advanced measurement and monitoring devices, artificial intelligence (AI) techniques as expert systems (ES) and neural networks (NN) can fulfill this duty.The goal of this paper is to show that a NN technique can be used reliably to obtain the response of a complex energetic system, such as CCs, during a slow transient and consequently as part of an on-line monitoring system.In this work, a CC power plant is simulated by dividing it into three blocks, which are representative of the three main elements of the CC: namely the gas turbine (GT), the heat recovery steam generator (HRSG) and the steam turbine (ST). To each of them a NN is associated. Once the training and testing of the NNs is carried out, the blocks are then arranged in a series cascade, the output of a block being the input of the subsequent one. With this solution, the NN-based system is able to produce the transient response of a CC plant when the input information are the GT inlet parameters.The transient data, not easy to obtain from measurements on existing plants, are provided by the CCDYN simulator (Dechamps, 1995). The performance obtained by the NN based system are observed to be in good agreement with those given by CCDYN, the latter being validated on the basis of measurements in an existing plant. The NN code, providing the departures of the measured data from the predicted ones, can be considered as a proper system for on-line monitoring and diagnosis.Copyright © 1997 by ASME