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Assessment of Risks of Voltage Quality Decline in Load Nodes of Power Systems

Author

Listed:
  • Pylyp Hovorov

    (Department of Electric Power Supply and Lighting Cities O.M., Beketov National University of Urban Economy in Kharkiv, 61108 Kharkiv, Ukraine)

  • Roman Trishch

    (Department of Mechatronics and Electrical Engineering, Ukraine National Aerospace University “Kharkiv Aviation Institute”, 61070 Kharkiv, Ukraine)

  • Romualdas Ginevičius

    (Faculty of Engineering Management, Bialystok University of Technology, 15-351 Bialystok, Poland)

  • Vladislavas Petraškevičius

    (Department of Economic Engineering, Faculty of Business Management, Vilnius Gediminas Technical University, Saulėtekio al. 11, LT–10223, 08303 Vilnius, Lithuania)

  • Karel Šuhajda

    (Institute od Building Construction, Faculty of Civil Engineering, Brno University of Technology, Veveří 95, 602 00 Brno, Czech Republic)

Abstract

The results of numerous studies show that the control of power grid modes is carried out mainly using a technical criterion. The economic criterion is taken into account through the use of complex and inaccurate models that do not accurately predict the result. The emergence of market relations in the energy sector makes power systems economic entities in terms of production and satisfaction of demand for electricity by various economic entities (industry, households, businesses, etc.). Under these conditions, electricity is a commodity with a corresponding price and quality indicators. This requires the application of the risk assessment methodology as an economic category in the activities of power systems as a business entity. The methodology of risk assessment in market conditions requires business entities to search for methods to minimize risk as a possibility of adverse events. Under these conditions, it becomes possible to make the best management decisions regarding the most important criterion that reflects the interests of business entities at a given time. However, the imperfection of the relevant methodology for risk assessment in the energy sector delays their application in the industry. At the same time, when making management decisions, three possible levels can be distinguished: decision-making in conditions of certainty, when the result is presented in a deterministic form and can be determined in advance; decision-making under conditions of risk, when the outcome cannot be determined in advance, but there is information on the probability of distribution of possible consequences; decision-making in conditions where the outcome is random and there is no information about the consequences of the decision. An analysis of scientific publications shows that some authors’ works are devoted to solving the issues of applying the theory and principles of risks in the energy sector, in which the problem is solved only at the first two levels. At the same time, the operation of energy facilities is characterized by a high level of uncertainty and incomplete information about the consequences of such decisions. Therefore, the development of a methodology for making management decisions in the energy sector based on the theory and practice of risks, taking into account the high level of uncertainty and incomplete information, is an urgent scientific task. Implementation of algorithms and programs for controlling the modes of power grids based on them can meet the requirements for reliable and high-quality energy supply to the most demanding consumers and create favorable conditions for their business. This work is devoted to the development of scientific and methodological foundations for determining the voltage risk in power system networks, taking into account the uncertain nature of the loads and its impact on consumers. Based on the results of the study, a mathematical model of the risk of voltage collapses in networks, an algorithm and a methodology for its calculation were proposed.

Suggested Citation

  • Pylyp Hovorov & Roman Trishch & Romualdas Ginevičius & Vladislavas Petraškevičius & Karel Šuhajda, 2025. "Assessment of Risks of Voltage Quality Decline in Load Nodes of Power Systems," Energies, MDPI, vol. 18(7), pages 1-16, March.
  • Handle: RePEc:gam:jeners:v:18:y:2025:i:7:p:1579-:d:1617657
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    References listed on IDEAS

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    1. Ahmad, Tanveer & Zhang, Dongdong & Huang, Chao, 2021. "Methodological framework for short-and medium-term energy, solar and wind power forecasting with stochastic-based machine learning approach to monetary and energy policy applications," Energy, Elsevier, vol. 231(C).
    2. Ali, Mumtaz & Prasad, Ramendra & Xiang, Yong & Deo, Ravinesh C., 2020. "Near real-time significant wave height forecasting with hybridized multiple linear regression algorithms," Renewable and Sustainable Energy Reviews, Elsevier, vol. 132(C).
    3. Ramirez, A.D. & Boero, A. & Rivela, B. & Melendres, A.M. & Espinoza, S. & Salas, D.A., 2020. "Life cycle methods to analyze the environmental sustainability of electricity generation in Ecuador: Is decarbonization the right path?," Renewable and Sustainable Energy Reviews, Elsevier, vol. 134(C).
    4. Shi, Zhongtuo & Yao, Wei & Li, Zhouping & Zeng, Lingkang & Zhao, Yifan & Zhang, Runfeng & Tang, Yong & Wen, Jinyu, 2020. "Artificial intelligence techniques for stability analysis and control in smart grids: Methodologies, applications, challenges and future directions," Applied Energy, Elsevier, vol. 278(C).
    5. Kharrazi, A. & Sreeram, V. & Mishra, Y., 2020. "Assessment techniques of the impact of grid-tied rooftop photovoltaic generation on the power quality of low voltage distribution network - A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 120(C).
    6. Raquel Martinez & Pablo Castro & Alberto Arroyo & Mario Manana & Noemi Galan & Fidel Simon Moreno & Sergio Bustamante & Alberto Laso, 2022. "Techniques to Locate the Origin of Power Quality Disturbances in a Power System: A Review," Sustainability, MDPI, vol. 14(12), pages 1-27, June.
    7. Wayes Tushar & Tapan K. Saha & Chau Yuen & David Smith & Peta Ashworth & H. Vincent Poor & Subarna Basnet, 2020. "Challenges and prospects for negawatt trading in light of recent technological developments," Nature Energy, Nature, vol. 5(11), pages 834-841, November.
    8. Štefan Markulik & Marek Šolc & Peter Blaško, 2024. "Use of Risk Management to Support Business Sustainability in the Automotive Industry," Sustainability, MDPI, vol. 16(10), pages 1-24, May.
    9. Ruhnau, Oliver & Hennig, Patrick & Madlener, Reinhard, 2020. "Economic implications of forecasting electricity generation from variable renewable energy sources," Renewable Energy, Elsevier, vol. 161(C), pages 1318-1327.
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