How can new technologies of artificial intelligence and Big Data Analytics help optimize the production and use of energy generated from different energy sources within the existing specific structure of the mix of energy sources in the national energy sector?

How can new technologies of artificial intelligence and Big Data Analytics help optimize the production and use of energy generated from different energy sources within the occurring specific structure of the mix of energy sources in the domestic energy sector and optimize investment processes for the construction of specific types of power plants, energy generating power plants, investments in the development of transmission networks, energy storage, etc.?

In recent days (end of May 2024) in the country where I operate, weather aura conditions have been favorable for the production of clean energy generated mainly through renewable and emission-free energy sources. Accordingly, it was reported that a record amount of clean, emission-free energy was generated in Poland on 27.5.2024 from renewable and emission-free energy sources, including mainly photovoltaics and wind. It's just a pity that much of this energy has gone to waste, as the dominant companies in the energy market have for many years ignored the need to invest in the development of transmission grids and storage facilities for energy from new photovoltaic and windmill installations put up on rooftops by prosumer citizens. Paradoxically, however, the share of renewable and zero-emission energy in the overall energy mix in Poland is still relatively low, amounting to only about 1/4 of the energy source mix, as a result of years of subsidizing from the state's public finance system the development of dirty combustion energy based on the generation of energy from the combustion of fossil fuels while blocking and restricting the development of RES. Paradoxically, when the development of onshore wind energy was blocked in Poland in 2016, it was already clear from a number of analyses and studies conducted in various research centers operating in different parts of the world that since the middle of the 2nd decade of the 21st century, clearly the cheapest energy is wind and solar energy, and the most expensive energy production is dirty combustion energy based on burning coal and lignite. Since the middle of the 2nd decade of the 21st century, the aforementioned gap between steadily, year by year cheap photovoltaic technology and other energy eco-technologies, cheap RES energy production and more expensive energy produced from burning fossil fuels has been growing steadily. This issue is particularly important because there may be further energy crises in the future, such as those that occurred in the 1970s and in 2022. The demand for electricity production will also grow in the future. Paradoxically, the ongoing process of global warming will also contribute to an increase in energy demand in the future. The various types of projects, processes and activities that are being launched to reduce the scale of the negative effects of the progressive global warming process, such as the production and use of refrigeration equipment, equipment for obtaining clean water in the situation of increasingly frequent periods of drought, desalination of seawater, in addition to the development of electromobility, etc., will consume large amounts of additional energy, which is already starting to run out at times. In the context of these aggravating problems, there is a growing importance of systems and instruments to help and/or facilitate the management of energy production and use, taking into account the optimization of production from specific, different types of energy sources, under conditions of changing weather and climatic conditions and the existing structure of different energy sources, including renewable and non-renewable, sustainable and combustion, emission-free and emission-free energy, etc., within a specific, occurring mix of energy sources in the country. The various different energy sources are significantly different in terms of various determinants, which include varying levels of variability in energy production caused by objective external factors, e.g. changes in weather conditions, significant variation in the necessary financial outlays that are incurred in the investment processes for the construction of a particular type of power plant or electric and/or thermal power plant, variation in the period of implementation of investment projects for the construction of power plants generating energy within the framework of renewable or non-renewable energy sources, local and national natural and geological conditions conditioning the possibility of building a particular type of power plant, variation in the economic and technological development of the country, equipment of the financial system with financial capital that can be applied to support the development of investments in the energy sector, etc. In view of the above, new ICT and Industry 4.0/5.0 information technologies, including but not limited to generative artificial intelligence and Big Data Analytics technologies, may prove helpful in optimizing energy production under different types of energy sources and optimizing the investment processes carried out within the power sector. The research shows that new technologies of artificial intelligence and Big Data Analytics can help optimize the production and use of energy generated from various energy sources within the existing specific structure of the mix of energy sources in the national energy sector, as well as optimize investment processes for the construction of specific types of power plants, energy-generating power plants, investments in the development of transmission networks, energy storage, etc. The key issue, therefore, will be how the integrated information systems built from modules equipped with the aforementioned new technologies will be designed and built so that the processes of optimizing the level of energy production from certain different sources operating within the national energy source mix; optimizing energy transmission, consumption and storage; and optimizing the investment processes in which various investment projects for the construction of power plants and energy-generating power plants within different types of energy sources are implemented simultaneously.

I described the key issues of opportunities and threats to the development of artificial intelligence technology in my article below:

OPPORTUNITIES AND THREATS TO THE DEVELOPMENT OF ARTIFICIAL INTELLIGENCE APPLICATIONS AND THE NEED FOR NORMATIVE REGULATION OF THIS DEVELOPMENT

Article OPPORTUNITIES AND THREATS TO THE DEVELOPMENT OF ARTIFICIAL I...

I described the applications of Big Data technologies in sentiment analysis, business analytics and risk management in my co-authored article:

APPLICATION OF DATA BASE SYSTEMS BIG DATA AND BUSINESS INTELLIGENCE SOFTWARE IN INTEGRATED RISK MANAGEMENT IN ORGANIZATION

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I described the key issues concerning the problem of green transformation of the economy in the following article:

IMPLEMENTATION OF THE PRINCIPLES OF SUSTAINABLE ECONOMY DEVELOPMENT AS A KEY ELEMENT OF THE PRO-ECOLOGICAL TRANSFORMATION OF THE ECONOMY TOWARDS GREEN ECONOMY AND CIRCULAR ECONOMY

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The key issues of the problematic sources of Poland's exceptionally deep energy cross in 2022 are described in my co-authored article below:

POLAND'S 2022 ENERGY CRISIS AS A RESULT OF THE WAR IN UKRAINE AND YEARS OF NEGLECT TO CARRY OUT A GREEN TRANSFORMATION OF THE ENERGY SECTOR

Article POLAND'S 2022 ENERGY CRISIS AS A RESULT OF THE WAR IN UKRAIN...

I invite you to familiarize yourself with the issues described in the above-mentioned publications and to scientific cooperation in these issues.

In view of the above, I address the following question to the esteemed community of scientists and researchers:

How can the new technologies of artificial intelligence and Big Data Analytics help optimize the production and use of energy generated from various energy sources within the framework of the occurring specific structure of the mix of energy sources in the national energy sector, as well as optimize investment processes for the construction of specific types of power plants, energy-generating power plants, investments in the development of transmission networks, energy storage, etc.?

How can the new technologies of artificial intelligence and Big Data Analytics help optimize the production and use of energy generated from different energy sources within the framework of the occurring specific structure of the mix of energy sources in the national energy sector?

What do you think about this topic?

What is your opinion on this issue?

Please answer,

I invite everyone to join the discussion,

Thank you very much,

Best wishes,

Dariusz Prokopowicz

The above text is entirely my own work written by me on the basis of my research.

In writing this text, I did not use other sources or automatic text generation systems.

Copyright by Dariusz Prokopowicz

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