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Modelling, Simulation and Control of Thermal Energy Systems

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A special issue of Energies (ISSN 1996-1073).

Deadline for manuscript submissions: closed (1 March 2020) | Viewed by 41521

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Special Issue Editors

Prof. Dr. Kwang Y. Lee

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Guest Editor

Department of Electrical and Computer Engineering, Baylor University, Waco, TX 76798, USA
Interests: power systems control; power plant control; fuel cell power plants; renewable energy; intelligent control; modern heuristic optimization
Special Issues, Collections and Topics in MDPI journals

Dr. Damian Flynn

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Guest Editor

Electrical and Electronic Engineering, University College Dublin, Belfield, Dublin 4, Ireland
Interests: the flexibility of thermal power generation; thermal plant cycling; user comfort for discretionary load; state of charge of electric vehicles

Prof. Hui Xie

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Guest Editor

Vice-director, State Key Lab of Engines, School of Mechanical Engineering, Tianjin University, Tianjin, China
Interests: thermal engine modelling; thermal engine control; hybrid vehicles; advanced combustion and control

Dr. Li Sun

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Guest Editor

School of Energy and Environment, Southeast University, Nanjing, China
Interests: temperature modelling; power plant control; fuel cell modelling; distributed generation

Special Issue Information

Dear Colleagues,

Faced with an ever-growing resource scarcity and environmental regulations, the last 30 years have witnessed the rapid development of various renewable power sources, such as wind, tidal, and solar power generation. The variable and uncertain nature of these resources is well-known, while the utilization of power electronic converters presents new challenges for the stability of the power grid. Consequently, various control and operational strategies have been proposed and implemented by the industry and research community, with a growing requirement for flexibility and load regulation placed on conventional thermal power generation.

Against this background, the modelling and control of conventional thermal engines, such as those based on diesel and gasoline, are experiencing serious obstacles when facing increasing environmental concerns. Efficient control that can fulfill the requirements of high efficiency, low pollution, and long durability is an emerging requirement.

The modelling, simulation, and control of thermal energy systems is key to providing innovative and effective solutions. Through applying detailed dynamic modelling, a thorough understanding of the thermal conversion mechanism(s) can be achieved, based on which advanced control strategies can be designed to improve the performance of the thermal energy system, both in economic and environmental terms. Simulation studies, and test beds, are also of great significance for these research activities prior to proceeding to field tests.

This Special Issue will contribute a practical and comprehensive forum for exchanging novel research ideas or empirical practices that bridge the modelling, simulation, and control of thermal energy systems.

Papers that analyze particular aspects of thermal energy systems, involving, for example, conventional power plants, innovative thermal power generation, various thermal engines, thermal energy storage, and fundamental heat transfer management, on the basis of one or more of the following topics, are welcome in this Special Issue:

Power plant modelling, simulation, and control;
Thermal engines;
Thermal energy control in building energy systems;
Combined heat and power (CHP) generation;
Thermal energy storage systems;
Improving thermal comfort technologies;
Optimization of complex thermal systems;
Modelling and control of thermal networks;
Thermal management of fuel cell systems;
Thermal control of solar utilization;
Heat pump control;
Heat exchanger control.

Prof. Dr. Kwang Y. Lee
Dr. Damian Flynn
Prof. Hui Xie
Dr. Li Sun
Guest Editors

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

thermal management
dynamic modelling
feedback control
thermal power generation
fuel cell
thermal storage
heat pump

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Published Papers (12 papers)

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Research

18 pages, 1222 KiB

Open AccessArticle

Multi-Objective Optimal Operation for Steam Power Scheduling Based on Economic and Exergetic Analysis

by Yu Huang, Weizhen Hou, Yiran Huang, Jiayu Li, Qixian Li, Dongfeng Wang and Yan Zhang

Energies 2020, 13(8), 1886; https://doi.org/10.3390/en13081886 - 13 Apr 2020

Cited by 5 | Viewed by 2245

Abstract

Steam supply scheduling (SSS) plays an important role in providing uninterrupted reliable energy to meet the heat and electricity demand in both the industrial and residential sectors. However, the system complexity makes it challenging to operate efficiently. Besides, the operational objectives in terms of economic cost and thermodynamic efficiency are usually contradictory, making the online scheduling even more intractable. To this end, the thermodynamic efficiency is evaluated based on exergetic analysis in this paper, and an economic-exergetic optimal scheduling model is formulated into a mixed-integer linear programming (MILP) problem. Moreover, the ε-constraint method is used to obtain the Pareto front of the multi-objective optimization model, and fuzzy satisfying approach is introduced to decide the unique operation strategy of the SSS. In the single-period case results, compared with the optimal scheduling which only takes the economic index as the objective function, the operation cost of the multi-objective optimization is increased by 4.59%, and the exergy efficiency is increased by 9.3%. Compared with the optimal scheduling which only takes the exergetic index as the objective function, the operation cost of the multi-objective optimization is decreased by 19.83%, and the exergy efficiency is decreased by 2.39%. Furthermore, results of single-period and multi-period multi-objective optimal scheduling verify the effectiveness of the model and the solution proposed in this study. Full article

(This article belongs to the Special Issue Modelling, Simulation and Control of Thermal Energy Systems)

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28 pages, 6153 KiB

Open AccessArticle

Multiresolution GPC-Structured Control of a Single-Loop Cold-Flow Chemical Looping Testbed

by Shu Zhang, Joseph Bentsman, Xinsheng Lou, Carl Neuschaefer, Yongseok Lee and Hamza El-Kebir

Energies 2020, 13(7), 1759; https://doi.org/10.3390/en13071759 - 7 Apr 2020

Cited by 4 | Viewed by 2636

Abstract

Chemical looping is a near-zero emission process for generating power from coal. It is based on a multi-phase gas-solid flow and has extremely challenging nonlinear, multi-scale dynamics with jumps, producing large dynamic model uncertainty, which renders traditional robust control techniques, such as linear [...] Read more.

H_{\infty}

design, largely inapplicable. This process complexity is addressed in the present work through the temporal and the spatiotemporal multiresolution modeling along with the corresponding model-based control laws. Namely, the nonlinear autoregressive with exogenous input model structure, nonlinear in the wavelet basis, but linear in parameters, is used to identify the dominant temporal chemical looping process dynamics. The control inputs and the wavelet model parameters are calculated by optimizing a quadratic cost function using a gradient descent method. The respective identification and tracking error convergence of the proposed self-tuning identification and control schemes, the latter using the unconstrained generalized predictive control structure, is separately ascertained through the Lyapunov stability theorem. The rate constraint on the control signal in the temporal control law is then imposed and the control topology is augmented by an additional control loop with self-tuning deadbeat controller which uses the spatiotemporal wavelet riser dynamics representation. The novelty of this work is three-fold: (1) developing the self-tuning controller design methodology that consists in embedding the real-time tunable temporal highly nonlinear, but linearly parametrizable, multiresolution system representations into the classical rate-constrained generalized predictive quadratic optimal control structure, (2) augmenting the temporal multiresolution loop by a more complex spatiotemporal multiresolution self-tuning deadbeat control loop, and (3) demonstrating the effectiveness of the proposed methodology in producing fast recursive real-time algorithms for controlling highly uncertain nonlinear multiscale processes. The latter is shown through the data from the implemented temporal and augmented spatiotemporal solutions of a difficult chemical looping cold flow tracking control problem. Full article

(This article belongs to the Special Issue Modelling, Simulation and Control of Thermal Energy Systems)

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13 pages, 1959 KiB

Open AccessArticle

Uncertainties in the Testing of the Coefficient of Thermal Expansion of Overhead Conductors

by Miren T. Bedialauneta, Igor Albizu, Elvira Fernandez and A. Javier Mazon

Energies 2020, 13(2), 411; https://doi.org/10.3390/en13020411 - 14 Jan 2020

Cited by 4 | Viewed by 2760

Abstract

Overhead lines can be replaced by high temperature low sag (HTLS) conductors in order to increase their capacity. The coefficients of thermal expansion (CTE) of the HTLS conductors are lower than the CTE of conventional conductors. The utilities and conductor manufacturers usually carry out the verification of the CTE of the overhead conductors in an actual size span. The verification is based on the observation of the change of the conductor length as a result of the conductor temperature change. This process is influenced by the coefficient of thermal expansion to be verified. However, there are other factors that also affect it. This paper analyzes the effect of some of the uncertainty sources in the testing of the coefficient of thermal expansion of the overhead conductors. Firstly, the thermal expansion process is described and the uncertainty sources related to the conductor and the line section are identified. Then, the uncertainty sources and their effect on the CTE testing are quantified. Full article

(This article belongs to the Special Issue Modelling, Simulation and Control of Thermal Energy Systems)

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15 pages, 4165 KiB

Open AccessArticle

Supplementary Control of Air–Fuel Ratio Using Dynamic Matrix Control for Thermal Power Plant Emission

by Taehyun Lee, Eungsu Han, Un-Chul Moon and Kwang Y. Lee

Energies 2020, 13(1), 226; https://doi.org/10.3390/en13010226 - 2 Jan 2020

Cited by 10 | Viewed by 5575

Abstract

This paper proposes a supplementary control for tighter control of the air–fuel ratio (AFR), which directly affects the environmental emissions of thermal power plants. Dynamic matrix control (DMC) is applied to the supplementary control of the existing combustion control loops and the conventional double cross limiting algorithm for combustion safety is formulated as constraints in the proposed DMC. The proposed supplementary control is simulated for a 600-MW drum-type power plant and 1000 MW ultra-supercritical once-through boiler power plant. The results show the tight control of the AFR in both types of thermal power plants to reduce environmental emissions. Full article

(This article belongs to the Special Issue Modelling, Simulation and Control of Thermal Energy Systems)

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24 pages, 5765 KiB

Open AccessFeature PaperArticle

Modelling and Analysis of Plate Heat Exchangers for Flexible District Heating Systems

by Serafym Chyhryn

Energies 2019, 12(21), 4141; https://doi.org/10.3390/en12214141 - 30 Oct 2019

Cited by 3 | Viewed by 4013

Abstract

Seamless integration of district heating (DH) and power systems implies their flexible operation, which extends their typical operational boundaries and, thus, affects performance of key components, such as plate heat exchangers (PHXs). Despite that the heat transfer in a PHX is regulated by mass flows, flexible operation and demand variations cause shifts in temperature levels, which affects the system operation and must be efficiently accounted for. In this paper, an overall heat transfer coefficient (OHTC) model with direct relation to temperature is proposed. The model is based on a linear approximation of thermophysical components of the forced convection coefficient (FCC). On one hand, it allows to account for temperature variations as compared to mass flow-based models, thus, improving accuracy. On the other hand, it does not involve iterative lookup of thermophysical properties and requires fewer inputs, hence, reducing computational effort. The proposed linear model is experimentally verified on a laboratory PHX against estimated correlations for FCC. A practical estimation procedure is proposed based on component data. Additionally, binding the correlation to one of varying parameters shows reduction in the heat transfer error. Finally, operational optimization test cases for a basic DH system demonstrate better performance of the proposed models as compared to those previously used. Full article

(This article belongs to the Special Issue Modelling, Simulation and Control of Thermal Energy Systems)

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14 pages, 4191 KiB

Open AccessArticle

Stacked Auto-Encoder Modeling of an Ultra-Supercritical Boiler-Turbine System

by Hao Zhang, Xiangjie Liu, Xiaobing Kong and Kwang Y. Lee

Energies 2019, 12(21), 4035; https://doi.org/10.3390/en12214035 - 23 Oct 2019

Cited by 11 | Viewed by 2450

Abstract

The ultra-supercritical (USC) coal-fired boiler-turbine unit has been widely used in modern power plants due to its high efficiency and low emissions. Since it is a typical multivariable system with large inertia, severe nonlinearity, and strong coupling, building an accurate model of the system using traditional identification methods are almost impossible. In this paper, a deep neural network framework using stacked auto-encoders (SAEs) is presented as an effective way to model the USC unit. In the training process of SAE, maximum correntropy is chosen as the loss function, since it can effectively alleviate the influence of the outliers existing in USC unit data. The SAE model is trained and validated using the real-time measurement data generated in the USC unit, and then compared with the traditional multilayer perceptron network. The results show that SAE has superiority both in forecasting the dynamic behavior as well as eliminating the influence of outliers. Therefore, it can be applicable for the simulation analysis of a 1000 MW USC unit. Full article

(This article belongs to the Special Issue Modelling, Simulation and Control of Thermal Energy Systems)

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18 pages, 870 KiB

Open AccessArticle

Temperature Dependent Parameter Estimation of Electrical Vehicle Batteries

by Anna I. Pózna, Katalin M. Hangos and Attila Magyar

Energies 2019, 12(19), 3755; https://doi.org/10.3390/en12193755 - 30 Sep 2019

Cited by 4 | Viewed by 2886

Abstract

Parameter estimation of electrical vehicle batteries in the presence of temperature effect is addressed in this work. A simple parametric temperature dependent battery model is used for this purpose where the temperature dependence is described by static relationships. A two-step method is used that includes a parameter estimation step of the key parameters at different temperatures followed by a static optimization step that determines the temperature coefficients of the corresponding parameters. It was found that the temperature dependent parameter characteristics can be reliably estimated from charging profiles only. The proposed method can be used as a computationally effective way of determining the key battery parameters at a given temperature from their actual estimated values and from their previously determined static temperature dependence. The proposed parameter estimation method was verified by simulation experiments on a more complex battery model that also describes the detailed dynamic thermal behavior of the battery. Full article

(This article belongs to the Special Issue Modelling, Simulation and Control of Thermal Energy Systems)

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14 pages, 10234 KiB

Open AccessArticle

Development of Engine Efficiency Characteristic in Dynamic Working States

by Piotr Bera

Energies 2019, 12(15), 2906; https://doi.org/10.3390/en12152906 - 28 Jul 2019

Cited by 6 | Viewed by 3030

Abstract

The objective of this paper is to present a new approach to the problem of combustion engine efficiency characteristic development in dynamic working states. The artificial neural network (ANN) method was used to build a mathematical model of the engine comprising the following parameters: Engine speed, angular acceleration, engine torque, torque change intensity, and fuel mass flow, measured on a test bed on a spark ignition engine in static and dynamic working states. A detailed analysis of ANN design, data preparation, the training method, and the ANN model accuracy are described. The paper presents conducted calculations that clearly show the suitability of the approach in every aspect. Then, a simplified ANN was created, which allows a two dimensional characteristic in dynamic states, including 4 variables, to be determined. Full article

(This article belongs to the Special Issue Modelling, Simulation and Control of Thermal Energy Systems)

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13 pages, 6811 KiB

Open AccessArticle

Thermal Fatigue Modelling and Simulation of Flip Chip Component Solder Joints under Cyclic Thermal Loading

by Liangyu Wu, Xiaotian Han, Chenxi Shao, Feng Yao and Weibo Yang

Energies 2019, 12(12), 2391; https://doi.org/10.3390/en12122391 - 21 Jun 2019

Cited by 16 | Viewed by 4058

Abstract

Thermal Fatigue of flip chip component solder joints is widely existing in thermal energy systems, which imposes a great challenge to operational safety. In order to investigate the influential factors, this paper develops a model to analyze thermal fatigue, based on the Darveaux energy method. Under cyclic thermal loading, a theoretical heat transfer and thermal stress model is developed for the flip chip components and the thermal fatigue lives of flip chip component solder joints are analyzed. The model based simulation results show the effects of environmental and power parameters on thermal fatigue life. It is indicated that under cyclic thermal loading, the solder joint with the shortest life in a package of flip chip components is located at the outer corner point of the array. Increment in either power density or ambient temperature or the decrease in either power conversion time or ambient pressure will result in short thermal fatigue lives of the key solder joints in the flip chip components. In addition, thermal fatigue life is more sensitive to power density and ambient temperature than to power conversion time and ambient air pressure. Full article

(This article belongs to the Special Issue Modelling, Simulation and Control of Thermal Energy Systems)

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17 pages, 2466 KiB

Open AccessFeature PaperArticle

Transient Analysis and Execution-Level Power Tracking Control of the Concentrating Solar Thermal Power Plant

by Xiufan Liang and Yiguo Li

Energies 2019, 12(8), 1564; https://doi.org/10.3390/en12081564 - 25 Apr 2019

Cited by 4 | Viewed by 4425

Abstract

Concentrating solar power (CSP) is a promising technology for exploiting solar energy. A major advantage of CSP plants lies in their capability of integrating with thermal energy storage; hence, they can have a similar operability to that of fossil-fired power plants, i.e., their power output can be adjusted as required. For this reason, the power output of such CSP plants is generally scheduled to maximize the operating revenue by participating in electric markets, which can result in frequent changes in the power reference signal and introduces challenges to real-time power tracking. To address this issue, this paper systematically studies the execution-level power tracking control strategy of an CSP plant, primarily aiming at coordinating the control of the sluggish steam generator (including the economizer, the boiler, and the superheater) and the fast steam turbine. The governing equations of the key energy conversion processes in the CSP plant are first presented and used as the simulation platform. Then, the transient behavior of the CSP plant is analyzed to gain an insight into the system dynamic characteristics and control difficulties. Then, based on the step-response data, the transfer functions of the CSP plant are identified, which form the prediction model of the model predictive controller. Finally, two control strategies are studied through simulation experiments: (1) the heuristic PI control with two operation modes, which can be conveniently implemented but cannot coordinate the control of the power tracking speed and the main steam parameters, and (2) advanced model predictive control (MPC), which overcomes the shortcoming of PI (Proportional-Integral) control and can significantly improve the control performance. Full article

(This article belongs to the Special Issue Modelling, Simulation and Control of Thermal Energy Systems)

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16 pages, 4049 KiB

Open AccessArticle

Optimization of Dispatching Electricity Market with Consideration of a Solar-Assisted Coal-Fired Power Generation System

by Rongrong Zhai, Lingjie Feng, Hai Yu, Chao Li and Yongping Yang

Energies 2019, 12(7), 1284; https://doi.org/10.3390/en12071284 - 3 Apr 2019

Viewed by 2533

Abstract

This study investigates the multi-objective optimization of load dispatch of a solar-assisted coal-fired power generation system. The improved environmental/economic load dispatch model considers coal consumption, NO_x emissions, and power purchase cost. The singular weighted method is utilized to solve this multi-objective and multi-constraint optimization problem. A power system that includes five power generators, one of which is retrofitted to a solar-assisted coal-fired unit, is also analyzed. It can be concluded that the loads of solar-assisted coal-fired units are higher than the original coal-fired unit, and with the increase of solar radiation, the gap between the loads of two units also increases. In addition, after retrofitting, the coal consumption, the NO_x emission, and power costs of units reduce by about 2.05%, 0.45%, and 0.14%, respectively. From the study on the on-grid power tariff, where the tariff drops from 16.29 cents/kWh to 3.26 cents/kWh, NO_x emissions drop from 12.31 t to 11.28 t per day, a reduction of about 8.38%. The cost of purchasing electricity decreases from $ 2,982,161.8 to $ 2,020,505.0 per day, a decrease of 32.25%. Therefore, when both coal-fired units and solar-assisted coal-fired units exist in a region, the use of solar-assisted coal-fired power generation units should be prioritized. Full article

(This article belongs to the Special Issue Modelling, Simulation and Control of Thermal Energy Systems)

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18 pages, 8255 KiB

Open AccessArticle

On the Flexible Operation of Supercritical Circulating Fluidized Bed: Burning Carbon Based Decentralized Active Disturbance Rejection Control

by Fan Zhang, Yali Xue, Donghai Li, Zhenlong Wu and Ting He

Energies 2019, 12(6), 1132; https://doi.org/10.3390/en12061132 - 22 Mar 2019

Cited by 13 | Viewed by 3802

Abstract

Supercritical circulating fluidized bed (CFB) is one of the prominent clean coal technologies owing to the advantages of high efficiency, fuel flexibility, and low cost of emission control. The fast and flexible load-tracking performance of the supercritical CFB boiler-turbine unit presents a promising prospect in facilitating the sustainability of the power systems. However, features such as large inertia, strong nonlinearity, and multivariable coupling make it a challenging task to harmonize the boiler’s slow dynamics with the turbine’s fast dynamics. To improve the operational flexibility of the supercritical CFB unit, a burning carbon based decentralized active disturbance rejection control is proposed. Since burning carbon in the furnace responds faster than throttle steam pressure when the fuel flow rate changes, it is utilized to compensate the dynamics of the corresponding loop. The parameters of the controllers are tuned by optimizing the weighted integrated absolute error index of each loop via genetic algorithm. Simulations of the proposed method on a 600 MW supercritical CFB unit verify the merits of load following and disturbance rejection in terms of less settling time and overshoot. Full article

(This article belongs to the Special Issue Modelling, Simulation and Control of Thermal Energy Systems)

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