 IMPLEMENTATION OF ARTIFICIAL INTELLIGENCE IN ENERGY CONSUMPTION CALCULATIONS TO REDUCE EXCESS GENERATION IN THE CONTEXT OF UKRAINE'S RECOVERYOksana Kuzmenko (),
Viktoriia Chorna () and
Lyudmyla Kozhura ()
Baltic Journal of Economic Studies, 2024, vol. 10, issue 1 Abstract: In authors' opinion, the relevance of implementing artificial intelligence in the calculation of energy consumption in order to reduce excess generation lies in several key aspects: 1) efficient use of resources (by analysing data and predicting energy consumption patterns using artificial intelligence, the operation of the energy system can be optimised, ensuring efficient use of energy resources and avoiding excessive electricity generation); 2) reduction of losses (artificial intelligence can help identify and eliminate problematic segments in energy systems, leading to a reduction in energy losses during transport and distribution); 3) consumption forecasting (artificial intelligence can predict and respond to energy consumption peaks, ensuring the stability of energy supply and avoiding overloading of energy systems); 4) resource conservation and emissions reduction (efficient management of energy consumption using artificial intelligence can lead to reduced fuel consumption and greenhouse gas emissions, promoting more sustainable and environmentally friendly development). Artificial intelligence is a field of computer science that deals with the creation of programs and systems capable of performing tasks that typically require human intellectual abilities. These systems can exhibit cognitive functions such as image recognition, language understanding, decision making, self-learning and planning. Artificial intelligence uses methods and techniques from computer science, mathematics, linguistics, philosophy and other fields to design and implement intelligent systems. Artificial intelligence in the energy sector is the application of AI methods and technologies to optimise energy production, transmission, distribution and consumption. This includes the development of algorithms and systems that can automatically analyse large amounts of data, predict energy demand, optimise energy processes, maintain the stability of energy networks and reduce energy losses. The application of artificial intelligence to energy can help increase the efficiency of energy production, reduce environmental impact and improve the reliability of energy systems. The subject of the study is the introduction of artificial intelligence in the calculation of energy consumption in order to reduce excess generation in the context of Ukraine's recovery. The research methods for introducing artificial intelligence into the calculation of energy consumption in order to reduce excess generation in the context of Ukraine's recovery are a system of general scientific and special methods of scientific knowledge. The purpose of the study is to determine the possibilities of introducing artificial intelligence into the calculation of energy consumption to reduce excess generation in the context of Ukraine's recovery. Results. Investing in the use of artificial intelligence to calculate energy consumption in order to reduce excess generation in the context of Ukraine's recovery can be done through various investment instruments, including: venture capital (investments in start-ups and companies developing artificial intelligence technologies to optimise energy consumption); project financing (financing of specific projects using artificial intelligence to analyse and optimise energy consumption); corporate investments (investments in the development of in-house artificial intelligence systems for energy efficiency management at industrial enterprises); stock market (investments in shares and bonds of companies specialising in the development and implementation of innovative technologies for the energy sector); crowdfunding (raising funds from individual investors on platforms dedicated to the development of artificial intelligence projects in the field of energy efficiency). Keywords: artificial intelligence; post-war reconstruction; energy sector recovery; energy consumers; energy efficiency; energy system optimisation (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:bal:journl:2256-0742:2024:10:1:18 DOI: 10.30525/2256-0742/2024-10-1-153-162 Access Statistics for this article Baltic Journal of Economic Studies is currently edited by Anita Jankovska, Managing Editor More articles in Baltic Journal of Economic Studies from Publishing house "Baltija Publishing" |
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