Neural network approach for predicting drum pressure and level in coal-fired subcritical power plant

There is increasing need for tighter controls of coal-fired plants due to more stringent regulations and addition of more renewable sources in the electricity grid. Achieving this will require better process knowledge which can be facilitated through the use of plant models. Drum-boilers, a key component of coal-fired subcritical power plants, have complicated characteristics and require highly complex routines for the dynamic characteristics to be accurately modelled. Development of such routines is laborious and due to computational requirements they are often unfit for control purposes. On the other hand, simpler lumped and semi empirical models may not represent the process well. As a result, data-driven approach based on neural networks is chosen in this study. Models derived with this approach incorporate all the complex underlying physics and performs very well so long as it is used within the range of conditions on which it was developed. The model can be used for studying plant dynamics and design of controllers. Dynamic model of the drum-boiler was developed in this study using NARX neural networks. The model predictions showed good agreement with actual outputs of the drum-boiler (drum pressure and water level)

Dynamic modelling, validation and analysis of coal-fired subcritical power plant

Coal-fired power plants are the main source of global electricity. As environmental regulations tighten, there is need to improve the design, operation and control of existing or new built coal-fired power plants. Modelling and simulation is identified as an economic, safe and reliable approach to reach this objective. In this study, a detailed dynamic model of a 500 MWe coal-fired subcritical power plant was developed using gPROMS based on first principles. Model validations were performed against actual plant measurements and the relative error was less than 5%. The model is able to predict plant performance reasonably from 70% load level to full load. Our analysis showed that implementing load changes through ramping introduces less process disturbances than step change. The model can be useful for providing operator training and for process troubleshooting among others

Flexible operation of supercritical power plant via integration of thermal energy storage

© 2018 The Author(s).This chapter presents the recent research on various strategies for power plant flexible operations to meet the requirements of load balance. The aim of this study is to investigate whether it is feasible to integrate the thermal energy storage (TES) with the thermal power plant steam-water cycle. Optional thermal charge and discharge locations in the cycle have been proposed and compared. Dynamic modeling and simulations have been carried out to demonstrate the capability of TES integration in supporting the flexible operation of the power plant. The simulation software named SimuEngine is adopted, and a 600 MW supercritical coal-fired power plant model is implemented onto the software platform. Three TES charging strategies and two TES discharging strategies are proposed and verified via the simulation platform. The simulation results show that it is feasible to extract steam from steam turbines to charge the TES and to discharge the stored thermal energy back to the power generation processes. The improved capability of the plant flexible operation is further studied in supporting the responses to the grid load demand changes. The results demonstrated that the TES integration has led to much faster and more flexible responses to the load demand changes.Peer reviewe

Dynamic modeling for assessment of steam cycle operation in waste-fired combined heat and power plants

As the share of non-dispatchable energy sources in power systems increases, thermal power plants are expected to experience load variations to a greater extent. Waste-fired combined heat and power has multiple products and is today primarily operated for waste incineration and to generate heat. To consider load variations in the power demand at these plants may be a way to provide system services and obtain revenue, however, the transient interaction between power and district heating generation for the type of steam systems used should be studied. This work describes the transient characteristics and timescales of cogeneration steam cycles to discuss the operational interactions between power and district heating generation. A dynamic model of the steam cycle of a 48 MW waste-fired combined heat and power plant is developed using physical equations and the modeling language Modelica. The model is successfully validated quantitatively for both steady-state and transient operation with data from a reference plant and is shown capable of characterizing the internal dynamics of combined heat and power plant processes. Simulations are performed to analyze steam cycle responses to step changes, ramps and sinusoidal disturbances of boiler load changes and variability in district heating inlet temperature and flow. The results give insight on the process timescales for the specific case studied; for example, with the present design a 10% boiler load change requires up to 15 min for responses to settle, while the corresponding time for a 10% change in district heating flow or temperature show settling times within 5 min. Furthermore, increasing the boiler ramp rate from 2 to 4%/min could reduce the rise time of power generation by 42%, which could be of economic significance in day-ahead power markets

Study of power plant, carbon capture and transport network through dynamic modelling and simulation

The unfavourable role of CO₂ in stimulating climate change has generated concerns as CO₂ levels in the atmosphere continue to increase. As a result, it has been recommended that coal-fired power plants which are major CO₂ emitters should be operated with a carbon capture and storage (CCS) system to reduce CO₂ emission levels from the plant. Studies on CCS chain have been limited except a few high profile projects. Majority of previous studies focused on individual components of the CCS chain which are insufficient to understand how the components of the CCS chain interact dynamically during operation. In this thesis, model-based study of the CCS chain including coal-fired subcritical power plant, post-combustion CO₂ capture (PCC) and pipeline transport components is presented. The component models of the CCS chain are dynamic and were derived from first principles. A separate model involving only the drum-boiler of a typical coal-fired subcritical power plant was also developed using neural networks.The power plant model was validated at steady state conditions for different load levels (70-100%). Analysis with the power plant model show that load change by ramping cause less disturbance than step changes. Rate-based PCC model obtained from Lawal et al. (2010) was used in this thesis. The PCC model was subsequently simplified to reduce the CPU time requirement. The CPU time was reduced by about 60% after simplification and the predictions compared to the detailed model had less than 5% relative difference. The results show that the numerous non-linear algebraic equations and external property calls in the detailed model are the reason for the high CPU time requirement of the detailed PCC model. The pipeline model is distributed and includes elevation profile and heat transfer with the environment. The pipeline model was used to assess the planned Yorkshire and Humber CO₂ pipeline network.Analysis with the CCS chain model indicates that actual changes in CO₂ flowrate entering the pipeline transport system in response to small load changes (about 10%) is very small (<5%). It is therefore concluded that small changes in load will have minimal impact on the transport component of the CCS chain when the capture plant is PCC

Evaluation of the potential of retrofitting a coal power plant to oxy-firing using CFD and process co-simulation

A new approach has been developed in order to estimate the potential of retrofitting an existing power plant to oxy-firing and the safe operation regime of the retrofitted boiler under oxy-combustion condition has been determined. Computational Fluid Dynamics (CFD) techniques have been employed to simulate the coal combustion and heat transfer to the furnace water walls and heat exchangers under air-firing and oxy-firing conditions. A set of reduced order models (ROM) has been developed to link the CFD predictions to the whole plant process model in order to simulate the performance of the power plant under different load and oxygen enrichment conditions in an efficient manner. Simulation results of a 500° MWe power plant unit indicate that it is possible to retrofit it to oxy-firing without affecting its overall performance. Further, the feasible range of oxygen enrichment for different power loads is identified to be between 25% and 27%. However, the peak temperature on the superheater platen 2 may increase in the oxy-coal mode at a high power load beyond 450° MWe

Dynamics and control of large-scale fluidized bed plants for renewable heat and power generation

As the share of variable renewable electricity increases, thermal power plants will have to adapt their operational protocols in order to remain economically competitive while also providing grid-balancing services required to deal with the inherent fluctuations of variable renewable electricity. This work presents a dynamic model of fluidized bed combustion plants for combined heat and power production. The novelty of the work lays in that (i) it provides an analysis of the transient performance of biomass-based fluidized bed combustion plants for combined heat and power production, (ii) the dynamic model includes a description of both the gas and water- steam sides and (iii) the model is validated against operational data acquired from a commercial-scale plant. The validated model is here applied to analyze the inherent dynamics of the investigated plant and to evaluate the performance of the plant when operated under different control and operational strategies, using a relative gain analysis and a variable ramping rate test.The results of the simulations reveal that the inherent dynamics of the process have stabilization times in the range of 5–25 min for all the step changes investigated, with variables connected to district heating production being the slowest. In contrast, variables connected to the live steam are the fastest, with stabilization times of magnitude similar to those of the in-furnace variables (i.e., around 10 min). Thus, it is concluded that the proper description of the dynamics in fluidized bed combustion plants for combined heat and power production requires modeling of both the gas and water sides (which is rare in previous literature). Regarding the assessment of control strategies, the boiler-following and hybrid control (combined fixed live steam and sliding pressure) strategies are found to be able to provide load changes as fast as 5%-unit/s, albeit while causing operational issues such as large pressure overshoots. The relative gain analysis outcomes show that these control structures do not have a steady-state gain on the power produced, and therefore it is the dynamic effect of the steam throttling that triggers the rapid power response. This study also includes the assessment of a turbine bypass strategy, the results of which show that it enables fast load-changing capabilities at constant combustion load, as well as decoupling power and heat production at the expense of thermodynamic losses

Integrated process and control modelling of water recirculation in once-through boilers during low load and transient operation

Power plant stability at lower loads is becoming ever more important, highlighting the increasing requirement for the development of advanced models and tools to analyse and design systems. Such tools enable a better understanding of the thermo-fluid processes and their dynamics, which improves the ability to specify and design better control algorithms and systems. During low load operation and transients, such as start-up and shutdown, the required water flow rate through the evaporator tubes of once-though boilers must be significantly higher than the evaporation rate to protect against overheating of the tubes until once-through operation is reached. Controlling the minimum required water flow rate through the evaporator and economiser is notoriously difficult. Within industry, strong emphasis is placed on maintaining the minimum required flow through the economiser and evaporator without adequate consideration of the potential thermal fatigue damage on the economiser, evaporator and superheater components and the risk of turbine quenching incidents. The purpose of this study was to develop an integrated process and control model that can be used to study transient events. The model developed in Flownex can simulate the complex thermo-fluid processes and associated controls of the feedwater start-up system. This includes the waterrecirculation loop, and allows for detailed transient analysis of the complete integrated system. The model was validated using data from an actual power plant in steady state as well as a transient cold start-up, up to once-through operation. Transient results from the model are also compared to the power plant unit during start-up for the addition or loss of mills using the existing control strategy. The model results compare well with the actual process behaviour. A new control strategy was then proposed and tested using the model. The results indicated significant improvement in control performance and overall controllability of the start-up system, and the large temperature fluctuations currently experienced at the economiser inlet during transients were significantly reduced. The new control strategy was also implemented on a real power plant unit undergoing commissioning. During all modes of start-ups (cold, warm and hot), as well as transients, the performance of the control system showed significant improvement, with a notable decline in instabilities of the feedwater flow. As predicted in the model, the large temperature fluctuations are significantly reduced. The new model therefore enabled the development of an improved control strategy that reduces damaging thermal fatigue. The general controllability of transients is also significantly improved, thereby minimizing risks of water carry-over, quenching and unit trips during start-up

Quantifying the Impact of Load-Following on Gas-fired Power Plants

Due to rapid penetration of renewables into the grid, natural gas combined cycle (NGCC) power plants are being forced to cycle their loads more frequently and rapidly than for which they were designed. However, the impact of load-following operation on plant efficiency and equipment health are currently poorly understood. The objective of this work is to quantify the impact of load-following on the gas-fired plants by developing high-fidelity multi-scale dynamic models. There are four main tasks in this project. First, dynamic model of an NGCC power plant has been developed. The main components of the NGCC plants are the gas turbine (GT), heat recovery steam generator (HRSG), and steam turbine (ST). The second task focuses on one of the undesired phenomena known as ‘spraying to saturation’ being faced by the NGCC plants during load-following, where the attemperator spray leads to saturation at the inlet of superheater and/or reheater causing damage and eventual failure of the superheater and/or reheater tubes due to two-phase flow. Different configurations of NGCC plants and operation strategies that can not only eliminate ‘spraying to saturation’ but can maximize the plant efficiency have been developed and evaluated. The third task focuses on modeling the unprecedented damages to the boiler components due to rapid load-following, which is leading to higher operation and maintenance (O&M) costs. Stress and wear models have been developed by accounting for creep and fatigue damages in key HRSG components. Multiple locations at the component junctions have been monitored and the most stressed part has been identified as the constraint in the dynamic optimization of the load-following operation. A multi-objective dynamic optimization algorithm has been developed for maximizing plant efficiency and minimizing deviation from desired ramp rates while satisfying operational constraints such as those due to stress and wear. The fourth task focuses on developing reduced order models. Since the modeling domain of interest includes multiple time scales and multiple spatial scales, it can be computationally intractable to use the iii detailed models for optimization/scheduling/control. Therefore, reduced order dynamic models have been developed for the NGCC system including the health models so that they can be computationally tractable for being used in dynamic optimization while providing desired accuracy