The principle of preemptive control in Smart Grid

Abstract

In presented paper the main principles that influence the formation, existence and development of socio-technical structure of society are revealed. The conditions for preemptive control applying to Smart Grid energy and information platform are determined. The technical level of implementation of energy and information platforms in Smart Grid depends on the covered space, climatic conditions, quantity and density of the population. The community of many individuals who are both the owners and users of the separate technical components of distributed generation systems poses both to individual members of the community and to the community as a whole questions, on the solution of which depends not only on the wellbeing but also the existence of a new socio-technical system. Structuring a community is based on the formation of socio-technical groups, the dual structure of which determines the need for new approaches to system control. Formation, development and structuring of the community are determined by three components: physical and technical properties of energy and information platforms; social properties of individual; cognitive, psychological and emotional qualities of individuals who have access to energy and information tools. It is shown that sufficient conditions for the system operation as a whole are determined by the presence of a distributed in time and space control system that combines and implements three main principles of control: centralized, decentralized and combined. Three mentioned principles are based on: Heisenberg's uncertainty principle that indicates the limited accuracy of the decision making and the possibility of error accumulation during the prolonged operation; principle of synergistic development; principle of cognitive control. In distributed generation systems these principles determine the logic of construction and operation of general control. Five hierarchy levels of control in Smart Grid are described and control objects and strategies for each level are given. It is shown that preemptive control should be situated on the highest (fifth) level. If in the process of operation the system is approaching a critical point, preemptive control implements advanced way to eliminate the threat of destruction of the system and the localization of hazardous technical objects. Six main steps on changing the current state of the system are described. When implementing the preemptive control to maintain the system stability it is necessary to pay attention to the theory of Robert Adams, according to which the "arm race" is one of the most important factors in stability ensuring. The main personal qualities, which determines the level of influence of the actions of individuals on the state of the system are listed. The formulas are given that allow by estimating the rate of increments of the magnitude of emotion to predict the appearance of critical points when making decisions on changing the system structure or tariffs. It is shown that preemptive control, as the system of the highest hierarchy level: blocks the threatening nodes; changes the structure of the system if necessary; passes to other control tasks. It is shown that the implementation of preemptive control at all levels of the hierarchy allows to ensure the necessary freedom of movement of the social and technical structure of society on the basis of the Smart Grid with ensuring its positive social development and blocking the negative impacts of individuals or social groups. Ref. 15, tabl. 1.

Keywords

References

1. I. Dumitrache and D. I. Dogaru, “Smart Grid Overview: Infrastructure, Cyber-Physical Security and Challenges,” in 2015 20th International Conference on Control Systems and Computer Science, 2015, pp. 693–699, DOI: 10.1109/CSCS.2015.80.
2. M. Z. Jacobson et al., “100% clean and renewable wind, water, and sunlight (WWS) all-sector energy roadmaps for the 50 United States,” Energy Environ. Sci., vol. 8, no. 7, pp. 2093–2117, 2015, DOI: 10.1039/C5EE01283J.
3. K. S. Osypenko, “Keruvannya rezhymamy roboty peretvoryuvachiv avtonomnyh system elektrozhyvlennya [The control of operating modes of autonomous power system converters],” National Technical University of Ukraine “Kyiv Polytechnic Institute,” 2016.
4. M. Aminu and K. Solomon, “A Review of Control Strategies for Microgrids,” Adv. Res., vol. 7, no. 3, pp. 1–9, 2016, DOI: 10.9734/AIR/2016/25722.
5. W. Heisenberg, “Uber den anschaulichen Inhalt der quantentheoretischen Kinematik und Mechanik,” Zeitschrift fur Phys., vol. 43, no. 3–4, pp. 172–198, 1927, DOI: 10.1007/BF01397280.
6. S. P. Kapitsa, S. P. Kurdyumov, and G. G. Malinetskiy, Sinergetika i prognozy buduschego [Synergetics and forecasts of the future]. Moscow:, Russia: Editorial, 2003, ISBN: 5-354-00296-6.
7. S. Li, X. Fu, I. Jaithwa, E. Alonso, M. Fairbank, and D. C. Wunsch, “Control of three-phase grid-connected microgrids using artificial neural networks,” in 7th International Joint Conference on Computational Intelligence, 2015, vol. 3, pp. 58–69, URL: http://ieeexplore.ieee.org/document/7533390/.
8. X. Zhang, P. Chen, C. Yu, F. Li, H. T. Do, and R. Cao, “Study of a Current Control Strategy Based on Multisampling for High-Power Grid-Connected Inverters With an LCL filter,” IEEE Trans. Power Electron., vol. 32, no. 7, pp. 5023–5034, 2017, DOI: 10.1109/TPEL.2016.2606461.
9. V. Salas, E. Olías, A. Barrado, and A. Lázaro, “Review of the maximum power point tracking algorithms for stand-alone photovoltaic systems,” Sol. Energy Mater. Sol. Cells, vol. 90, no. 11, pp. 1555–1578, 2006, DOI: 10.1016/j.solmat.2005.10.023.
10. H. Liu, P. C. Loh, X. Wang, Y. Yang, W. Wang, and D. Xu, “Droop Control With Improved Disturbance Adaption for a PV System With Two Power Conversion Stages,” IEEE Trans. Ind. Electron., vol. 63, no. 10, pp. 6073–6085, 2016, DOI: 10.1109/TIE.2016.2580525.
11. D. Wu, F. Tang, T. Dragicevic, J. C. Vasquez, and J. M. Guerrero, “A Control Architecture to Coordinate Renewable Energy Sources and Energy Storage Systems in Islanded Microgrids,” IEEE Trans. Smart Grid, vol. 6, no. 3, pp. 1156–1166, 2015, DOI: 10.1109/TSG.2014.2377018.
12. H. Cai, G. Hu, F. L. Lewis, and A. Davoudi, “A Distributed Feedforward Approach to Cooperative Control of AC Microgrids,” IEEE Trans. Power Syst., vol. 31, no. 5, pp. 4057–4067, 2016, DOI: 10.1109/TPWRS.2015.2507199.
13. E. V. Verbitski, A. G. Kyselova, and K. S. Osypenko, Kontekstno-zalezhne keruvannya avtonomnymy systemamy elektrozhyvlennya [Context-aware control of autonomous power supply systems]. Kyiv, Ukraine: Avers, 2015, ISBN: 978-966-8777-13-4.
14. D. S. Perlo-Freeman, D. A. Fleurant, P. D. Wezeman, and S. T. Wezeman, “Trends in world military expenditure, 2014,” 2015, URL: https://www.sipri.org/publications/2015/sipri-fact-sheets/trends-world-military-expenditure-2014.
15. V. Y. Zhuikov, “Silovaya elektronika v smart-setyah [Power electronics in smart-networks],” Tech. Electrodyn., no. 3, pp. 49–50, 2012.

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Copyright (c) 2018 Катерина Сергіївна Осипенко, Валерій Якович Жуйков (Автор)