J. Ward

Modelling, optimisation and performance evaluation of a parabolic trough solar collector steam generation system

A parabolic trough collector (PTC) system used for steam generation is presented in this paper. PTCs are the preferred type of collectors used for steam generation due to their ability to work at high temperatures with a good efficiency. The modelling program developed called PTCDES is used to predict the quantity of steam produced by the system. The flash vessel size, capacity and inventory determines how much energy is used at the beginning of the day for raising the temperature of the circulating water to saturation temperature before effective steam production begins. Optimisation of the flash vessel presented here uses a simplified version of the program PTCDES. System performance tests indicate that the modelling program is accurate to within 1.2% which is considered very adequate. Finally, the theoretical system energy analysis is presented in the form of a Sankey diagram. The analysis shows that only 48.9% of the available solar radiation is used for steam generation. The rest is lost either as collector or thermal losses.

Design and performance characteristics of a parabolic-trough solar-collector system

A comparison of the advantages and disadvantages of concentrating collectors against conventional flat-plate collectors are presented. This is followed by the design of a parabolic-trough solar-collector system, due consideration having been given to collector-aperture and rim-angle optimisation, together with the receiver-diameter selection. The collector characteristic curve gives a test slope of 0·441 and a test intercept equal to 0·642. The value of the test slope differs considerably from the initially predicted value: this is attributed to the heat losses from the receiver support brackets. Subsequent allowance for these losses is presented: this reduces the difference from 24·9% to 5·7%. Other tests are presented, including the determination of the collectors incidence-angle modifier, time constant and acceptance angle.

Low cost high accuracy parabolic troughs construction and evaluation

This paper describes a low cost method for mass-production of parabolic surfaces with fibreglass. Cavities produced with plastic conduits, covered with fibreglass at the back of the collector surface, provide reinforcement in the longitudinal and transverse directions, to increase rigidity. This produces a low-cost high-rigidity structure that is an accurate copy of the mould. The accuracy of the parabolic surface depends on the accuracy of the mould. The details of the mould production and the procedure for producing the parabolic surface are presented. The total thickness of the fibreglass is 4mm (mean value). The inside surface where the reflector is fixed is manufactured to a high degree of surface finish. The cost of the surface is US

Use of artificial intelligence techniques for optimisation of co-combustion of coal with biomass

30 per square metre of aperture area for 90° rim angle. The standard deviation of the distribution of the parabolic surface errors is found equal to 4.7 mrad which indicates a very accurate surface. The deflection of the surface to a force corresponding to a wind velocity of 90 MPH is well within reasonable limits.

The Application of a Two-Dimensional Zone Model to the Design and Control of a Continuously Operated, Gas-Fired Furnace

AbstractThe optimisation of burner operation in conventional pulverised-coal-fired boilers for co-combustion applications represents a significant challenge This paper describes a strategic framework in which Artificial Intelligence (AI) techniques can be applied to solve such an optimisation problem. The effectiveness of the proposed system is demonstrated by a case study that simulates the co-combustion of coal with sewage sludge in a 500-kW pilot-scale combustion rig equipped with a swirl stabilised low-NOx burner. A series of Computational Fluid Dynamics (CFD) simulations were performed to generate data for different operating conditions, which were then used to train several Artificial Neural Networks (ANNs) to predict the co-combustion performance Once trained, the ANNs were able to make estimations of unseen situations in a fraction of the time taken by the CFD simulation. Consequently, the networks were capable of representing the underlying physics of the CFD models and could be executed efficien...

Development of an intelligent flame monitoring system for steel reheating burners

This paper describes the development of a two-dimensional zone model to predict the throughput and thermal performance of a continuously operated gas-fired furnace heating steel bars to a nominal discharge temperature of 1250°C. Ultimately the model is intended to be a tool which can be used for the design and control of industrial furnaces. Consequently relatively short computing times are necessary and this was achieved by employing an isothermal computational fluid dynamics simulation to estimate the relative mass flows, and hence enthalpy flows to or from adjacent volume zones in the overall model. This simplified approach, which utilises a single “once off” isothermal computation of the flows, was considered to be adequate since isothermal flow models have been used successfully in the past to study the flow related behaviour of combustion systems. The coupling of a multi-zone model with a single “once off” isothermal computation of the flows enables a wide range of furnace design modifications to be studied quickly and easily. To illustrate the potential use of the model in a furnace design application, it was then used to investigate the effects of inclining the burners downwards towards the load as well as those associated with increasing the length of the furnace.Copyright

An Improved Mathematical Model to Predict the Real Time Transient Performance of a Large Steel Reheating Furnace

This article describes the development of a system to indirectly monitor the combustion characteristics of individual burners based on measurement and analysis of the signals detected from photodiodes detecting flame radiation signals. A series of experiments were conducted on a 500 kW pilot-scale furnace and on two 4 MW industrial burners located in two steel reheating furnaces. The flame radiation signals were monitored using a lens that transmitted the flame radiation to ultraviolet, visible and infrared photodiodes through a trifurcated optical fibre. The experiments covered a wide range of burner operating conditions including; variations in the burner load and excess air levels and simulations of burner imbalance. The relationships between the dynamic flame radiation signals and the burner operating parameters and conditions were made off-line using neural network models. The present work indicates that the measurement of flame radiation characteristics, coupled with neural networks, provides a promising means of monitoring and adjusting burner performance.

Development of fuzzy based methodology to commission co-combustion of unprepared biomass on chain grate stoker fired boilers

This paper describes the development and application of a two-dimensional model based on the zone method of radiation analysis to simulate the thermal behaviour of a large steel reheating furnace at Tata Steel. The furnace has a maximum throughput of 160 t/hr of steel blooms and is equipped with a total of 75 burners firing a mixture of combustible fuel gases arising from the steelmaking process. The model was validated for two different furnace throughput rates using experimental and plant data supplied by Tata Steel. Following validation it was then used to assess the furnace performance at a wider range of throughputs as well as examining the effect of the distribution of heat input along the furnace on furnace efficiency and stock temperature uniformity. The model differs from previous work since it takes into account the radiation interchange between the top and bottom firing sections of the furnace and also allows for enthalpy exchange due to the flows of combustion products between these sections. The results to-date showed that the model predictions are in good agreement with typical heating profile of the stock encountered in the actual furnace and are potentially suitable for incorporation into a model based furnace control system due to its relatively fast computing time.Copyright

Development of a Spectral Radiation Model to Predict the Transient Performance of a Metal Reheating Furnace

AbstractThis paper describes the development of an intelligent commissioning system to enable operators to maximise the utilisation of unprepared biomass by combusting the biomass with the minimum amount of support fuel to achieve a desired boiler output and thermal efficiency on chain grate stoker fired boilers. Tests were conducted on a 0·8 MWth chain grate stoker fired hot water boiler to investigate the combustion of different types of biomass blended with a support fuel over a wide range of boiler operating conditions and biomass moisture contents. The commissioning system was developed using fuzzy logic and expert system type rules developed while gathering the experimental data. The system was validated on untested blends of unprepared biomass with two support fuels where it was shown that it is possible to efficiently burn unprepared, high moisture content biomass with a support fuel on a chain grate stoker. This system could enable operators of chain grate stoker fired boilers to maximise the use...

Combustion optimisation of stoker fired boiler plant by neural networks

The use of computational fluid dynamics for simulation of combustion processes has made significant advances in recent years particularly for the design of individual burners and the prediction of pollutant formation and emission. However, the computational requirements of these models can still be too great for overall furnace thermal design purposes particularly if the transient performance is required. Thermal radiation is usually the dominant mode of heat transfer to the load or stock in industrial fuel-fired furnaces since the contribution of convection is relatively small. Thus prediction of the thermal performance of a furnace requires an accurate calculation of the complex radiation interchange between the surfaces and the combustion products. This can be achieved by the so-called Hottel zone method of radiation analysis and as a result this method has been applied to a wide range of industrial heating processes. The method sub-divides the non-isothermal furnace enclosure into a series of isothermal volume and surface zones and energy balances are then formulated and solved simultaneously for each zone. The computational demands are modest so that the process can be repeated successively throughout a period of furnace operation to simulate the transient behaviour of the system. However in these models all the surfaces are usually assumed to be grey and the radiation properties of the combustion products are normally represented by a mixture of grey and clear gases. These assumptions can lead to errors in the predictions, in applications such as the installation of high emissivity coatings on the furnace lining, where it is necessary to allow for the spectral variation in surface emissivity and the banded nature of the radiation properties of carbon dioxide and water vapour in the combustion gases. Consequently the proposed paper describes the development of “spectral” zone model, which takes these effects into account, to predict the transient performance of a furnace heating steel bars to a discharge temperature of 1200°C. The model also allows for broadening of the spectral bands with changes in the temperature of the combustion products. The work differs from that in previous papers on this type of model, which have been confined to steady-state simulations and do not allow for broadening. Finally the model is applied to investigate the effect of coating the refractory lining of the furnace with high emissivity materials.Copyright