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Abstract

The evolution of the economy and the formation of Industry 4.0 lead to an increase in the importance of intangible assets and the digitization of all processes at energy enterprises. This involves the use of technologies such as the Internet of Things, Big Data, predictive analytics, cloud computing, machine learning, artificial intelligence, robotics, 3D printing, augmented reality etc. Of particular interest is the use of artificial intelligence in the energy sector, which opens up such prospects as increased safety in energy generation, increased energy efficiency, and balanced energy-generation processes. The peculiarity of this particular instrument of Industry 4.0 is that it combines the processes of digitalization and intellectualization in the enterprise and forms a new part of the intellectual capital of the enterprise. The implementation of artificial intelligence in the activities of energy companies requires consideration of the features and stages of implementation. For this purpose, a conceptual model of artificial intelligence implementation at energy enterprises has been formed, which contains: the formation of the implementation strategy; the design process; operation and assessment of artificial intelligence. The introduction of artificial intelligence is a large-scale and rather costly project; therefore, it is of interest to assess the effectiveness of using artificial intelligence in the activities of energy companies. Efficiency measurement is proposed in the following areas: assessment of economic, scientific and technical, social, marketing, resource, financial, environmental, regional, ethical and cultural effects as well as assessment of the types of risks associated with the introduction of artificial intelligence.
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Authors and Affiliations

Hanna Doroshuk
1
ORCID: ORCID

  1. Department of Menegement, Odessa Polytechnic State University, Ukraine
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Abstract

Solar collectors are used increasingly in single-family housing. Their popularity depends on many factors, including the price-to-productivity ratio, which in turn results from the development of solar collector technology as well as entire systems. This development consists of many aspects, including those related to the modernization of control systems and measuring of solar collector systems. Currently used systems offer, among others, the ability to determine the approximate solar heat gains using the sensors necessary for normal control of the sensor system. The paper analyzes, on the example of one facility, how such installations work in Polish conditions. An installation consisting of 3 solar collectors has been selected for analysis, supporting the preparation of hot utility water for a single-family residential building. The detailed analysis concerned days with high heat gains compared to the average heat demand for hot water preparation in the building. The temperature verification method (TVM) of the calculated solar heat gains by the solar system controller has been proposed. Then, differences in measurements according to two methods (controller and TVM) have been presented at various characteristic moments of the installation’s operation (start- -up, stop) and during continuous operation. It has been shown that during the day gains measured by the controller can be 15% lower than gains measured by the TVM method. The check has been carried out at a daily sunlight value higher than 4.8 kWh/m2 measured on a horizontal plane. The ratio of heat energy supplied to the domestic hot water storage tank to the measured insolation has been 34%. The sum of annual solar heat gains measured by the controller and TVM differed by 5.2%.
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Authors and Affiliations

Piotr Olczak
1
ORCID: ORCID

  1. Mineral and Energy Economy Research Institute of the Polish Academy of Sciences, Kraków, Poland

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