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Advanced Control of Thermal Power Plants for Safe, Economic and Flexible Operation under High Penetration of Renewable Energy Sources

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "J: Thermal Management".

Deadline for manuscript submissions: closed (21 March 2022) | Viewed by 6972

Special Issue Editors

Prof. Dr. Kwang Y. Lee

E-Mail Website
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. Yrjö Majanne

E-Mail Website
Guest Editor
Faculty of Engineering and Natural Sciences, Tampere University, FI-33014 Tampere, Finland
Interests: thermal system modelling; power plant control
Dr. Xiao Wu

E-Mail Website
Guest Editor
National Engineering Research Center of Power Generation Control and Safety, School of Energy and Environment, Southeast University, Nanjing 210096, China
Interests: optimization and control of low-carbon energy system
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Facing with an ever-growing resource scarcity and environmental regulations, the last 30 years have witnessed the rapid development of various renewable energy sources, such as wind, hydro 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 resiliency, flexibility and load regulation placed on conventional thermal power generation. 

Against this background, the modelling and control of conventional thermal plants, such as those based on diesel, natural gas, and coal, 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. 

Advanced Modelling, Simulation, and Control of Thermal Power Plants is key to providing innovative and effective solutions. Through applying advanced system identification, modern heuristic optimization and machine learning, a thorough understanding of the thermal energy conversion systems can be achieved, based on which advanced control strategies can be designed to improve the performance of the thermal energy system, in terms of economic, environmental, safe, and resilient operation. 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. Articles that analyze aspects of thermal energy systems, involving, for example, conventional power plant, innovative thermal power generation, fuel-cell plants, hybrid power and heat energy systems, coupled energy and transportation systems, and battery, flywheel, and pumped-hydro energy storage systems, on the basis of one or more of the following topics, are welcome in this Special Issue: 

  • Power plant modelling, simulation, and control
  • Advanced control and optimization
  • Artificial intelligence and machine learning
  • Combined heat and power (CHP) generation
  • Cyclic operation of thermal power plants
  • Modelling and control of thermal networks
  • Multi-energy hub modeling and operation
  • Integrated operation of thermal power plants with renewable generation and energy storage systems
  • Coupled power and transportation systems via electric vehicles
  • Carbon capture systems
  • Fuel-cell power plants
  • Energy storage systems
  • Advance pumped-storage hydro plants 

Prof. Dr. Kwang Y. Lee
Dr. Yrjö Majanne
Dr. Xiao Wu
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

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

  • dynamic modelling
  • advanced control
  • thermal power generation
  • fuel cell
  • energy storage system
  • pumped-storage
  • carbon capture
  • combined heat and power
  • energy hub
  • coupled power and transportation, artificial intelligence
  • optimal operation

Published Papers (3 papers)

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Research

18 pages, 2506 KiB  
Article
Modeling of Large-Scale Thermal Power Plants for Performance Prediction in Deep Peak Shaving
by Sha Liu and Jiong Shen
Energies 2022, 15(9), 3171; https://0-doi-org.brum.beds.ac.uk/10.3390/en15093171 - 26 Apr 2022
Cited by 6 | Viewed by 1694
Abstract
To integrate more renewable energy into the power grid, large-scale thermal power plants have to extend their operating ranges and participating in deep peak shaving. In order to improve the thermal economy of large-scale thermal power plants participating in deep peak shaving, and [...] Read more.
To integrate more renewable energy into the power grid, large-scale thermal power plants have to extend their operating ranges and participating in deep peak shaving. In order to improve the thermal economy of large-scale thermal power plants participating in deep peak shaving, and to determine the performance of a thermal system under different conditions, a method of modeling for the performance prediction of large-scale thermal power plants in deep peak shaving is proposed. In the algorithm design of the model, a three-layer iterative cycle logic is constructed, and the coupling relationship between the parameters of the thermal system is analyzed from the mechanism level. All of the steam water parameters and the correction values of the flow rate at all levels of the system after the parameter disturbance are obtained. The algorithm can simulate the response of a thermal power plant under load variation and operation parameter variation. Compare the error between the data given by the prediction model and the test, the accuracy of the proposed prediction model is verified. When the unit participates in deep peak shaving, the prediction model is used to analyze the relative deviation of the unit thermal efficiency caused by cycle parameters and energy efficiency of equipment. It provides a date basis for the performance evaluation and multi-parameter coupling optimization. The research results can be used to determine the operation mode and equipment transformation scheme. Full article
(This article belongs to the Special Issue Advanced Control of Thermal Power Plants for Safe, Economic and Flexible Operation under High Penetration of Renewable Energy Sources)
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18 pages, 3269 KiB  
Article
Multivariate State Estimation Technique Combined with Modified Information Entropy Weight Method for Steam Turbine Energy Efficiency Monitoring Study
by Hui Gu, Hongxia Zhu and Xiaobo Cui
Energies 2021, 14(20), 6795; https://0-doi-org.brum.beds.ac.uk/10.3390/en14206795 - 18 Oct 2021
Cited by 8 | Viewed by 1962
Abstract
An energy efficiency monitoring method of the steam turbine system is studied in this paper. Multivariate state estimation technique (MSET) is utilized to compare the actual monitoring parameters and the healthy data of the equipment in normal working condition with a multi parameter [...] Read more.
An energy efficiency monitoring method of the steam turbine system is studied in this paper. Multivariate state estimation technique (MSET) is utilized to compare the actual monitoring parameters and the healthy data of the equipment in normal working condition with a multi parameter estimation model. Due to the limitation of a single heat rate index in evaluating energy efficiency variation, the energy efficiency deviation degree combined with improved information entropy weight is proposed to judge the steam turbine’s operation condition levels. The index value in the modified weight method has been searched for more steady weight values calculated by information entropy values with small variation. Taking a 600 MW unit as an example, the energy efficiency levels of the unit under a 550 MW normal working condition are clustered into four groups, testifying the MSET model correctness and calculating the deviation degree value. Then, the energy efficiency status monitoring model is utilized to record residuals of actual data and estimated data during abnormal energy efficiency period. The residuals over deviation degree are then marked and judged as related with the abnormal data. The results show that the MSET model can timely and accurately judge the change of unit operation state, and the deviation degree calculated by the modified information entropy weight method can provide earlier warnings for the abnormal energy efficiency working conditions. Full article
(This article belongs to the Special Issue Advanced Control of Thermal Power Plants for Safe, Economic and Flexible Operation under High Penetration of Renewable Energy Sources)
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17 pages, 1847 KiB  
Article
Influence of Fuel Type and Water Content Variation on Pollutant Emission Characteristics of a Biomass Circulating Fluidized Bed Boiler
by Jianjie He, Shanjian Liu, Di Yao, Ranran Kong and Yaya Liu
Energies 2021, 14(18), 5962; https://0-doi-org.brum.beds.ac.uk/10.3390/en14185962 - 20 Sep 2021
Cited by 3 | Viewed by 1918
Abstract
In general, the biomass raw materials burned by biomass power plants generally have the characteristics of variable fuel types, high moisture content, and high volatile content. In this paper, a 130 t/h biomass circulating fluidized bed (BCFB) model was established on the MWorks [...] Read more.
In general, the biomass raw materials burned by biomass power plants generally have the characteristics of variable fuel types, high moisture content, and high volatile content. In this paper, a 130 t/h biomass circulating fluidized bed (BCFB) model was established on the MWorks platform with Modelica language. The influence of biomass type changes on operation parameters, the corresponding steady-state characteristics, and the dynamic characteristics of the BCFB were carried out. The temperature corresponding to the combustion of pine was overall higher than that of the other fuels, and the flue gas from the combustion of pine had the highest concentration of SO2, up to 520.49 mg/Nm3. The flue gas from the combustion of pure cotton sticks had the highest concentration of NO, up to 254.34 mg/Nm3. The changes of fuel type and moisture content all have a great influence on the operation of BCFBs. The emission of pollutants was not only related to the element content of fuel, but also closely related to the furnace temperature. The fuel moisture content also indirectly affects the pollutant emission concentration and the steam-water system. Full article
(This article belongs to the Special Issue Advanced Control of Thermal Power Plants for Safe, Economic and Flexible Operation under High Penetration of Renewable Energy Sources)
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