Abstract

The significant increase in the installed capacity of power plants with renewable energy sources and the imbalance of the financial system of the wholesale electricity market of Ukraine prompted the Ministry of Energy to develop an alter-native support mechanism for RES producers. The introduction of a feed-in tariff (FIP), which compensates for the difference between the actual sale price of electricity and the "green" tariff, can help producers receive more money immediately after the electricity is released. However, studies have shown that exiting a balancing group without form-ing a new one can lead to increased costs associated with forecasting error. It is important for manufacturers to form independent balancing groups to compensate for negative consequences. The findings of the article show that there is no single optimal balancing group for all manufacturers, but some groups are often repeated. Switching to a separate balancing group can have a significant economic effect for the manufacturer, reducing the cost of forecasting error compared to being solely responsible for the imbalance. However, the balancing group determined by the method of retrospective calculation of the cost of the forecast error is not stable in the long term. Ref. 8, fig. 2, tab. 3 Key words: renewable sources, electricity market, short-term forecasting, forecast interval, deep learning neural net-works, cost estimation.

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