Models for Long-Term Time-Series Forecasting and Pattern Recognition

I'm trying to find a solution for long-term electricity hourly prices forecasting. Explaining simply, I have some data from 2018 - 2021 containing Demand, Renewable Generation, Hydropower Generation, System Losses, Energy Exchange, and Electricity Prices for each Energy Submarket (all this in hourly format). What I want to answer is: is possible to create a model to predict the prices for long-term or mid-term forecasting that identify the correlation on the Data?

For example, if I increase the Renewable Generation over the next ten years and maintain the other input variables as it is, what's the electricity hourly price?

Is there any model that can identify, learn, and understand the data pattern and achieve this prediction? I had looked into LSTM and RNNs but sounds like that they are used in short-term forecasting.