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Special Issue "Design, Development and Validation of Advanced Control Algorithms for Steam Turbines for Power Generation"

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "Electrical Power and Energy System".

Deadline for manuscript submissions: closed (30 November 2020).

Special Issue Editor

Prof. Dr. Valentina Colla
E-Mail Website
Guest Editor
ICT-COISP Center of Institute of Communication, lnformation and Perception Technologies TECIP, Scuola Superiore Sant'Anna, 56124 Pisa, Italy
Interests: modelling; simulation; monitoring and control of industrial processes; energy systems; process industry; data analytics; artificial intelligence; machine learning; hybrid intelligent systems for industrial applications; metallurgy and material science
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Special Issue Information

Dear Colleagues,

The power generation field has undergone a drastic evolution in the last decades. Interest in the use of renewable energy sources has grown significantly, since the supply of fossil hydrocarbon resources is decreasing as a consequence of the growing energy demand, but especially due to the ever-increasing need to reduce the relevant environmental impact of fossil-based energy systems. The growing exploitation of renewables has also increased the variability in the power availability, which pushes for an adaptation of systems for power generation based on fossil fuels. Moreover, there is an increasing demand in industries for improving energy efficiency through a better exploitation of alternative energy sources, such as process off-gases, whose production is not always stable.

As a consequence, nowadays, the application of steam turbines for power generation is facing new challenges and requires the implementation of novel and advanced control algorithms in order to obtain optimal performances.

Steam turbines were originally designed to produce energy from fossil fuels: Their mechanics and their control systems are designed assuming a quite stable steam production and few start-up and shut-down cycles. Therefore, the standard control techniques currently applied to turbomachinery are often unable to automatically adapt to changing operating conditions. Therefore, if such techniques are applied in particular domains, such as, for instance, concentrated solar power plants, which is always an increasing field of application, they cannot guarantee the desired performance. Moreover, even the most traditional power production technologies involving both gas and steam power, i.e., combined cycle plants, are facing more stringent requirements in terms of flexibility for the compensation of renewable energy source variability. Control system parameters are often set during the commissioning phase of the brand-new machine, through time-consuming and effort-intensive procedures. Afterwards, such parameters are only seldom readjusted based on semi-heuristic procedures. This implies that the machine should work in non-optimal efficiency conditions during its lifetime and in a responsive way with respect to the steam conditions’ variations. The control procedures need to also allow the correct and efficient operation of the turbomachine in transient conditions and without compromising its integrity. Additionally, the capability of simulating steam condition dynamics in transient scenarios is also impactful for the implementation of advanced steam turbines control logics.

The key aspects of the Special Issue are to present novel research developments related to advanced control algorithms targeted at the optimization of the performances of steam turbines for power generation in any feed condition, as well as throughout the lifetime of the system.

Prof. Dr. Valentina Colla
Guest Editor

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 papers will be 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 2000 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

  • advanced control schemes
  • distributed and networked control systems
  • smart grid applications
  • hybrid intelligent control
  • artificial intelligence and machine learning
  • optimal performances
  • management of transient conditions
  • advanced modeling approaches for control applications
  • predictive maintenance

Published Papers (2 papers)

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Research

Article
Risk-Based Planning of Diagnostic Testing of Turbines Operating with Increased Flexibility
Energies 2020, 13(13), 3464; https://doi.org/10.3390/en13133464 - 04 Jul 2020
Cited by 2 | Viewed by 586
Abstract
An increase in the share of renewable sources in the energy mix makes coal-fired power plants operate in new conditions that require more dynamic operation and adequate flexibility. The frequency of the power unit start-ups increases and so does the frequency of changes [...] Read more.
An increase in the share of renewable sources in the energy mix makes coal-fired power plants operate in new conditions that require more dynamic operation and adequate flexibility. The frequency of the power unit start-ups increases and so does the frequency of changes in loads. This intensifies some life consumption processes, such as low-cycle fatigue and crack propagation in the turbine components. Further operation of power unit elements that have already been in service for a long time has to be supplemented with new diagnostic and repair procedures that take into account the intensification of life consumption processes. This article gives predictions about the propagation rate of potential cracks in the turbine rotor for different scenarios of the power unit’s long-term operation. A method is presented of rational selection of the diagnostic testing time based on risk analysis. The method is used to estimate the optimal interval after which diagnostic testing of a 200 MW turbine rotor should be carried out. Changes in the rotor steel crack toughness are evaluated based on the results of testing of microspecimens cut out of the rotor. Turbines with more frequent start-ups and shorter start-up times necessitate performance of diagnostic testing of the rotor central bore after about 12 years of turbine operation. Full article
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Article
Risk Assessment of Smart Substation Relay Protection System Based on Markov Model and Risk Transfer Network
Energies 2020, 13(7), 1777; https://doi.org/10.3390/en13071777 - 07 Apr 2020
Cited by 4 | Viewed by 858
Abstract
To effectively guarantee a secure and stable operation of a smart substation, it is essential to develop a relay protection system considering the real-time online operation state evaluation and the risk assessment of that substation. In this paper, based on action data, defect [...] Read more.
To effectively guarantee a secure and stable operation of a smart substation, it is essential to develop a relay protection system considering the real-time online operation state evaluation and the risk assessment of that substation. In this paper, based on action data, defect data, and network message information of the system protection device (PD), a Markov model-based operation state evaluation method is firstly proposed for each device in the relay protection system (RPS). Then, the risk assessment of RPS in the smart substation is carried out by utilizing the risk transfer network. Finally, to highly verify the usefulness and the effectiveness of the proposed method, a case study of a typical 220 kV substation is provided. It follows from the case study that the developed method can achieve a better improvement for the maintenance plan of the smart substation. Full article
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