| Title | Energy Trading Perspectives in the Digital Era |
|---|---|
| ID_Doc | 75417 |
| Authors | Puskás-Tompos, A |
| Title | Energy Trading Perspectives in the Digital Era |
| Year | 2020 |
| Published | Proceedings Of The International Conference On Business Excellence, 14, 1 |
| Abstract | The aim of the paper research is to identify and improve business models in energy trading by analyzing the current situation and developing scenarios for the evolution of business models in the Digital Era. It is very important to analyze, identify and track those directions that we believe will drive energy trading in order to be able to design and create new sustainable business models. We highlight the possibilities and ways of improving the energy trading, analyzing the rapid evolution of the field, generated by the emergence of several new factors that can influence this industry. Beside those directions at which electricity trading is heading in the Digital Era, the research also describes main innovations in the field such as Smart Grids, Blockchain Technology, Peer-to-peer trading platforms and Demand Response through which the purpose is to attract final consumers to the energy trading on web platforms or mobile applications with which they can properly control their electric appliances and self-generation units in their homes, all these supervised and guided by artificial intelligence. The type of research proposed to identify the current condition and to be able to develop new trading models is empirical research through qualitative analysis. Beyond incentives and monetary benefits, the focus is on final consumer education and increased awareness towards a more conscious, optimal and rational consumption of electricity that can lead to both a better use of the energy production from renewable sources and a reduction of pollutant fossil fuel electricity generation and carbon dioxide emissions without endangering the proper functioning of the electricity systems. Previous researches are based more on incentivizing or penalizing end consumers in present paper, more emphasis is placed on attracting the end consumer to his own electricity trading through mentioned innovation, but also supervised and guided by artificial intelligence. |
| https://www.sciendo.com/pdf/10.2478/picbe-2020-0003 |
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