Shen Guo

Mathematic modeling and condition monitoring of power station tube-ball mill systems

The paper presents a newly developed nonlinear Tube-Ball mill model for model based on-line condition monitoring. This mathematical model is derived through analyzing energy transferring, heat exchange and mass flow balances. Evolutionary techniques are adopted to identify the unknown system parameters using the on-site measurement data. The identified system parameters are then validated using multiple on-line measurement data. Validation has been conducted by comparing the measured and simulated values. The results indicate that the model can represent the coal mill dynamics and can be used to predict the mill dynamic performance. Then the model is implemented on-line and it can run on-line along with the real milling process. It is then adopted for on-line condition and safety monitoring, fault detection, and control to improve the efficiency of combustion.

Generalized Predictive Control for superheated steam temperature regulation in a supercritical coal-fired power plant

The design and implementation of a Generalized Predictive Control (GPC) strategy for the superheated steam temperature regulation in a supercritical (SC) coal-fired power plant is presented. A Controlled Auto-Regressive MovingAverage (CARMA) model of the plant is derived from using the experimental data to approximately predict the plants future behavior. This model is required by the GPC algorithm to calculate the future control inputs. A new GPC controller is designed and its performance is tested through extensive simulation studies. Compared with the performance of the plant using a conventional PID controller, the steam temperature controlled by the GPC controller is found to be more stable. The stable steam temperature leads to more efficient plant operation and energy saving, as demonstrated by the simulation results. Plant performance improvement is also tested while the plant experiences the load demand changes and disturbances resulting from the malfunctioning of coal mills.

Dynamic modelling and simulation of IGCC process with Texaco gasifier using different coal

Integrated gasification combined cycle (IGCC) is considered as a viable option for low emission power generation and carbon dioxide sequestration. As a part of the process of IGCC plant design and development, modelling and simulation study of the whole IGCC process is important for thermodynamic performance evaluation, study of carbon capture readiness and economic analysis. The work presented in the paper is to develop such a whole system model and simulation platform. A simplified dynamic model for the IGCC process is developed, in which Texaco gasifier is chosen to give the basic representation for the IGCC process. The chemical equilibriums principle is used to predict the syngas contents in the modelling procedure. The influences of key parameters to regulate the input such as oxygen/coal ratio and water/coal ratio to syngas generation are studied. The simulation results are validated by comparing with the industry data provided by the Lu-nan fertilizer factory. Water-shift reactor, gas turbine and heat recovery steam-generation modules are modelled to study the dynamic performance with respect to the variation from the input of syngas stream. The simulation results reveal the dynamic changes in the plant outputs, including gas temperature, power output and mole percentages of hydrogen and carbon dioxide in the syngas. The process dynamic responses with three types of coal inputs are studied in the paper and their dynamic variation trends are presented via the simulation results.

Condition Monitoring of Power Plant Milling Process Using Intelligent Optimisation and Model Based Techniques

Coal preparation is the first step in the whole process of coal-fired power generation. A typical milling process is illustrated in Figure 1. Also, coal-fired power stations nowadays are required to operate more flexibly with more varied coal specifications and regularly use coal with higher volatile contents and Biomass materials (Livingston 2004); this greatly increases the risks of explosions or fires in milling plants. The power stations are also obliged to vary their output in response to the changes of electricity demands, which results in more frequent mill start-ups and shut-downs. In many cases, coal mills are shutdown and then restarted before they have cooled adequately, which creates a potential fire hazard within the mill. Frequent start-ups and shut-downs of mills will also have an impact on power plant operation safety. Mill fires could occur if the coal stops flowing in the mill and the static deposit is heated for a period of time. Fires in out-of-service mills can cause explosions on mill starts. Fires in running mills can cause explosions on shut-downs. The result of a study indicated that as many as 300 “explosions” were occurring annually in the US pulverized coal industry (Scott, 1995). Especially, adding higher volatile Biomass materials greatly increases the chance of mill fires and explosions. The UK PF Safety Forum had recently reported an increase in the frequency of mill explosions in the UK. Operational safety and efficient combustion require better understanding to the milling process. However, coal mills have been paid much less attention in research compared with boilers, generators, and other power generation system components. It is difficult to identify if there will be a fire in the mill. Outlet temperature and CO are established methods of detecting fires in mills, but at present they are not very effective for detecting small fires. The CO detection system becomes ineffective when the mill is in service due to dilution effects caused by primary air flow and associated oxygen content in the mill. A wide range of literature survey shows that there are only a few reports on mathematical models of milling processes. A detailed milling process description can be found in Scott et al. 1995. An approximated linear transfer function model was obtained by Bollinger et al, in 1983. Mill modelling using system identification method was reported in 1984 (Corti et al. 1984). With specially designed input signals, a linear discrete time model was obtained by Cheetham, et al in 1990, in which system time-delay was considered. An approximated 19

Mathematical Modelling for Coal Fired Supercritical Power Plants and Model Parameter Identification Using Genetic Algorithms

The paper presents the progress of our study of the whole process mathematical model for a supercritical coal-fired power plant. The modelling procedure is rooted from thermodynamic and engineering principles with reference to the previously published literatures. Model unknown parameters are identified using Genetic Algorithms (GAs) with 600MW supercritical power plant on-site measurement data. The identified parameters are verified with different sets of measured plant data. Although some assumptions are made in the modelling process to simplify the model structure at a certain level, the supercritical coal-fired power plant model reported in the paper can represent the main features of the real plant once-through unit operation and the simulation results show that the main variation trends of the process have good agreement with the measured dynamic responses from the power plants.

Study on a Wind Turbine in Hybrid Connection with a Energy Storage System

Wind energy has been focused as an inexhaustible and abundant energy source for electrical power generation and its penetration level has increased dramatically worldwide in recent years. However, its intermittence nature is still a universally faced challenge. As a possible solution, energy storage technology hybrid with renewable power generation process is considered as one of options in recent years. The paper aims to study and compare two feasible energy storage means—compressed air (CAES) and electrochemical energy storage (ECES) for wind power generation applications. A novel CAES structure in hybrid connection with a small power scale wind turbine is proposed. The mathematical model for the hybrid wind turbine system is developed and the simulation study of system dynamics is given. Also, a pneumatic power compensation control strategy is reported to achieve acceptable power output quality and smooth mechanical connection transition.