Integrated control system of the thermal power complex using the tensor analysis methods
/ 1
- Details
- Category: Information Technologies, Systems Analysis and Administration
- Last Updated on 10 November 2019
- Published on 26 October 2019
- Hits: 2574
Authors:
V.M.Sidletskyi, Cand. Sc. (Tech.), Assoc. Prof., orcid.org/0000-0003-2606-3651, National University of Food Technologies, Kyiv, Ukraine, e‑mail: This email address is being protected from spambots. You need JavaScript enabled to view it.; This email address is being protected from spambots. You need JavaScript enabled to view it.
I.V.Elperin, Cand. Sc. (Tech.), Prof., orcid.org/0000-0003-0475-5390, National University of Food Technologies, Kyiv, Ukraine, e‑mail: This email address is being protected from spambots. You need JavaScript enabled to view it.; This email address is being protected from spambots. You need JavaScript enabled to view it.
Abstract:
Solving the problem of energy consumption reducing in the industry is an urgent task. In turn, to reduce the use of fuel, it is necessary to increase the operation efficiency of areas that consume heat and electricity, which can only be achieved through their maximum coordinated work.
Purpose. To investigate tensor analysis methods in automation systems for controlling the heat and power complex.
Methodology. Methods of comparative analysis, mathematic simulation are used; experimental studies are conducted.
Findings. In the modern automation systems, the formation of a control action uses predicted values obtained from mathematical models and, therefore, the efficiency of the enterprise will depend on the adequacy of the developed mathematical model. If the mathematical model is formulated in a tensor form, then it will describe the process in an adequate way. The paper presents an example of developing a tensor model for the heat and power complex of an enterprise and its use on the example of a block diagram of a control system.
Originality. Substantiation of using tensor analysis methods in the heat and power complex control system consisting of the steam source and consumers is given. This approach allowed us to quickly (by measured data) identify the state of the technological process and to calculate its tensor model, which was later used for the formation of control action.
Practical value. The results of the work allow us to improve conventional automation systems by adding mechanisms, which enable us to simulate a technological process in a control system using a tensor analysis method and generate a control signal.
References.
1. Stanheev, К. О., Hrystynko, V. І., Vasylenko, Т. P., & Vasylenko, S. М. (2014). Energy efficient factors for improving the energy efficiency of the sugar industry. Ukrainian Sugar, 2(98), 14-17.
2. Luhtura, F. I., Pyzhykov, А. V., & Hlestova, О. А. (2014). About ways to improve the thermal efficiency and reliability of industrial CHP. Bulletin of Pryazovian State Technical University. Series: Technical sciences, 36, 88-100.
3. Bublikov, A., Tkachov, V., & Isakova, M. (2013). Control automation of shearers in term of auger gumming criterion. CRC Press/Balkema – Taylor & Francis Group: Energy efficiency improvement of geotechnical systems, 137-145. DOI: 10.1201/b16355-19.
4. Tkachov, V., Bublikov, A., & Gruhler, G. (2015). Automated stabilization of loading capacity of coal shearer screw with controlled cutting drive. In New Developments in Mining Engineering Theoretical and Practical Solutions of Mineral Resources Mining (pp. 465-477). London: Taylor & Francis Group. DOI: 10.1201/b19901-82.
5. Talebi, B., Mirzaei, P.A., Bastani, A., & Haghighat, F. (2016). A Review of District Heating Systems: Modeling and Optimization. Frontiers in Built Environment, 2. DOI: 10.3389/fbuil.2016.00022.
6. Haichao Wang, Risto Lahdelma, Xin Wang, Wenling Jiao, Chuanzhi Zhu, & Pinghua Zou (2015). Analysis of the location for peak heating in CHP based combined district heating systems Analysis of the location for peak heating in CHP based combined district heating systems. Applied Thermal Engineering, 87, 402-411.
7. Ahmadi, G., Toghraie, D., & Akbari, O.A. (2018). Technical and environmental analysis of repowering the existing CHP system in a petrochemical plant: A case study. Energy, Elsevier, 159, 937-949.
8. Weinberger, G., & Moshfegh, B. (2018). Investigating influential techno-economic factors for combined heat and power production using optimization and metamodeling. Applied Energy, Elsevier, 232, 555-571.
9. Soon-Young Choi, Kee-Youn Yoo, Jeong-Bin Lee, Chee Burm Shin, & Myung-June Park (2010). Mathematical modeling and control of thermal plant in the district heating system of Korea. Applied Thermal Engineering, Elsevier Science B.V., Amsterdam, 30, 2067-2072.
10. Skakovsky, Y., Babkov, A., & Mandro, E. (2017). Efficiency improvement for sugar plant boiler department work based on boiler units optimal loads distribution, Automation of technological and business processes, 9(3), 24-33.
11. Lapin, M. V., & Sidletskyi, V. M. (2016). Vykorystannia system nechitkoi lohiky dlia dynamichnoho upravlinnia potuzhnistiu parovykh kotloahrehativ. Naukovi pratsi Natsionalnoho Universytetu Kharchovykh Tekhnolohii, 22(4), 24-31.
12. Teran, P. (2010). On consistency of stationary points of stochastic optimization problems in a Banach space. J. Math. Anal. Appl., 363, 569-578.
13. Sidletskyy, V. М., Elperin, І. V., & Polupan, V. V. (2016). Analysis of non-measurement parameters at the level of distributed control for an automated system, objects and complexes of the food industry. Scientific works of the National Food Technologies University, 22(3), 7-15.
14. Lee, N., & Cichocki, A. (2018). Fundamental tensor operations for large-scale data analysis using tensor network formats. Multidimensional Systems and Signal Processing, 29(3), 921-960.
15. Younas, S., & Figley, C. (2018). Development, Implementation and Validation of an Automatic Centerline Extraction Algorithm for Complex 3D Objects. Journal of Medical and Biological Engineering, 39(2), 184-204.
16. Kuntanapreeda Suwat, Ronzhin, A., & Shishlakov, V. (2018). Control of shimmy vibration in aircraft landing gears based on tensor product model transformation and twisting sliding mode algorithm. Abstracts of Papers ‘18: 13th International Scientific-Technical Conference on Electromechanics and Robotics “Zavalishin’s Readings” (pp. 1-6). DOI: 10.2514/2.2744.
17. Sidletskyi, V. M., & Elperin, I. V. (2016). Expansion of functional possibilities of control systems of technological objects. Naukovyi zhurnal “Tekhnika ta enerhetyka”, 256, 113-121. Retrieved from http://journals.nubip.edu.ua/index.php/Tekhnica/article/view/8241.
Archive