Neuro-Fuzzy Modeling Techniques in Economics

Neuro-Fuzzy Modeling Techniques in Economics

Forecasting electricity generation from renewable sources in developing countries (on the example of Ukraine)

DOI:

10.33111/nfmte.2021.164

Анотація:
Abstract: Electricity generation forecasting is a common task that helps power generating companies plan capacity, minimize costs, and detect anomaly. Despite its importance, there are serious challenges associated with obtaining reliable and high-quality forecasts, especially when it comes to the newly created renewable electricity market.
A practical approach to predicting the generation of electricity from alternative sources in developing countries (on the example of Ukraine) based on the use of classical (ARIMA, TBATS) and modern (Prophet, NNAR) approaches is proposed.
The legal framework regulating the process of Ukraine's entry into the pan-European energy market and its functioning was analyzed: the weak points of the legislation on responsibility, the permissible accuracy of weather conditions data, and the lack of data on the monitoring infrastructure are indicated.
Among all the proposed alternatives, the Prophet model was the most accurate, since it allows you to simultaneously take into account several seasonalities (hourly, daily, weekly, monthly, and holidays).
According to this, for an operational forecast (6 hours) the best model is the one that takes into account hourly seasonality, and for shortterm forecasts (24 and 48 hours) and medium-term forecast (72 hours) the most accurate models are those taking into account hourly, daily, weekly seasonality and weather conditions.
The obtained forecasts and model quality indicators approve the feasibility of applying the proposed approach and the constructed models that can be used in a wide range of economic problems.
Ключові слова:
Key words: alternative energy, forecasting, Prophet model, neural network autoregression
УДК:
UDC:

JEL: C45 C6 C8 Q42 Q47

To cite paper
In APA style
Miroshnychenko, I., Kravchenko, Т., & Drobyna, Y. (2021). Forecasting electricity generation from renewable sources in developing countries (on the example of Ukraine). Neuro-Fuzzy Modeling Techniques in Economics, 10, 164-198. http://doi.org/10.33111/nfmte.2021.164
In MON style
Мірошниченко І., Кравченко Т., Дробина Ю. Forecasting electricity generation from renewable sources in developing countries (on the example of Ukraine). Нейро-нечіткі технології моделювання в економіці. 2021. № 10. С. 164-198. http://doi.org/10.33111/nfmte.2021.164 (дата звернення: 22.02.2024).
With transliteration
Miroshnychenko, I., Kravchenko, Т., Drobyna, Y. (2021) Forecasting electricity generation from renewable sources in developing countries (on the example of Ukraine). Neuro-Fuzzy Modeling Techniques in Economics, no. 10. pp. 164-198. http://doi.org/10.33111/nfmte.2021.164 (accessed 22 Feb 2024).
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