Abstract
This paper is devoted to the development of information technology for decision making support when controlling the parameters of the hybrid power grid (HPG), considering the meteorological forecast and changes in the required level electricity generation and consumption in the HPG. The problem of decision making in the HPG management is formed under conditions of uncertainty and incompleteness of input information, therefore, it cannot be considered as an optimization problem, but should be considered as a multidimensional and multiscale problem. In this study, models for the collection and preliminary processing of information, models for determining the level of generation from renewable energy sources (RES), models for forecasting electricity consumption, a model for assessing the quality of electricity and a decision-making model are formed, which constitute the algorithmic and information support of information technology for decision support. Management decisions are made using additional current information on the effectiveness of the established regime, as well as forecast information obtained based on the proposed models.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Daniele, M., Anna, P.: A method to improve microgrid reliability by optimal sizing PV wind plants and storage systems. In: 20th International Conference on Electricity Distribution, pp. 8–16. CIRED, Prague Czech (2009)
Shendryk, V., Shulyma, O., Parfenenko, Y.: The topicality and the peculiarities of the renewable energy sources integration into the Ukrainian power grids and the heating system. In: González-Prida, V., Raman, A. (eds.) Promoting Sustainable Practices through Energy Engineering and Asset Management, pp. 162–192. IGI Global, Hersey PA (2015)
Analysis of the market “day ahead” and the intraday market for 2019 (6 months). https://www.oree.com.ua/index.php/web/65
Menniti, D., Pinnarelli, A., Sorrentino, N.: A method to improve microgrid reliability by optimal sizing PV/wind plants and storage systems. In.: CIRED 2009 - The 20th International Conference and Exhibition on Electricity Distribution, Prague, Part 2, pp. 1–4 (2009)
Ali, A., Li, W., Hussain, R., He, X., Williams, B.W., Memon, A.H.: Overview of current microgrid policies, incentives and barriers in the European Union, United States and China. Sustainability 9 (2017). https://www.mdpi.com/2071-1050/9/7/1146/pdf
Object Management Group: A standard Business Process Model and Notation (BPMN). http://www.bpmn.org/
Dodonov, O.G., Putyatin, V.G., Valetchik, V.O.: Information, and analytical support for management decisions. Registration Storage Data Process. 7(2), 77–93 (2005)
Schahovska, N.: Datawarehouse and dataspace information base of decision support system. In: 11th International Conference - The Experience of Designing and Application of CAD Systems in Microelectronics, CADSM 2011, pp. 170–173, 5744419 (2011)
Dotsenko, S.I., Tymchuk, S.O., Shendryk, S.O., Shulyma, O.V.: Calculation of capacity insolation for forecasting the production of electrical energy by photovoltaic panels. Bull. Petro Vasylenko Kharkiv Natl. Tech. Univ. Agric. 176, 8–11 (2016)
Shendryk, V., Boiko, O., Parfenenko, Y., Shendryk, S., Tymchuk, S.: Decision making for energy management in smart grid. In: Diaz, V.G.-P., Bonilla, J.P.Z. (eds.) Handbook of Research on Industrial Advancement in Scientific Knowledge, pp. 264–297. IGI Global (2019)
Arcos-Aviles, D., Pascual, J., Marroyo, L., Sanchis, P., Guinjoan, F.: Fuzzy logic-based energy management system design for residential grid-connected microgrids. In.: IEEE Transactions on Smart Grid, pp. 530–543 (2016). https://doi.org/10.1109/TSG.2016.2555245
Tymchuk, S., Shendryk, S., Shendryk, V., Piskarov, O., Kazlauskayte, A.: Fuzzy predictive model of solar panel for decision support system in the management of hybrid grid. In: Damaševičius, R., Vasiljevienė, G. (eds.) ICIST 2019. CCIS, vol. 1078, pp. 416–427. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-30275-7_32
Tymchuk, S., Shendryk, S., Shendryk, V., Abramenko, I., Kazlauskaite, A.: The methodology of obtaining power consumption fuzzy predictive model for enterprises. In: Ivanov, V., Trojanowska, J., Pavlenko, I., Zajac, J., Peraković, D. (eds.) DSMIE 2020. LNME, pp. 210–219. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-50794-7_21
EN 50160:2010 Voltage Characteristics of electricity supplied by public distribution networks. https://infostore.saiglobal.com/preview/98699522296.pdf?sku=859794_saig_nsai_nsai_2045468
Tymchuk, S., Miroshnyk, O., Shendryk, S., Shendryk, V.: Integral fuzzy power quality assessment for decision support system at management of power network with distributed generation. In: Damaševičius, R., Vasiljevienė, G. (eds.) ICIST 2018. CCIS, vol. 920, pp. 88–97. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-99972-2_7
Orlovsky, S.A.: Decision-making problems with fuzzy initial information. In: Science, p. 206 (1981)
Bellman, R.E., Zadeh, L.A.: Decision-making in a fuzzy environment. Manag. Sci. 17(4), B-141 (1970). https://doi.org/10.1287/mnsc.17.4.B141
Tymchuk, S., Shendryk, S., Shendryk, V., Panov, A., Kazlauskaite, A., Levytska, T.: Decision-making model at the management of hybrid power grid. In: Lopata, A., Butkienė, R., Gudonienė, D., Sukackė, V. (eds.) ICIST 2020. CCIS, vol. 1283, pp. 60–71. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-59506-7_6
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 Springer Nature Switzerland AG
About this paper
Cite this paper
Shendryk, S., Shendryk, V., Tymchuk, S., Parfenenko, Y. (2021). Information Technology of Decision-Making Support on the Energy Management of Hybrid Power Grid. In: Lopata, A., Gudonienė, D., Butkienė, R. (eds) Information and Software Technologies. ICIST 2021. Communications in Computer and Information Science, vol 1486. Springer, Cham. https://doi.org/10.1007/978-3-030-88304-1_6
Download citation
DOI: https://doi.org/10.1007/978-3-030-88304-1_6
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-88303-4
Online ISBN: 978-3-030-88304-1
eBook Packages: Computer ScienceComputer Science (R0)