Okes2024/Renewable-Energy-Demand-Forecasting-Using-Time-Series ? reverse-engineered prompt

Build me a simple Python project that forecasts renewable energy demand from historical data using an LSTM time series model.

It should load the dataset in this repo, clean and prepare the time series, train a model, then show predictions against the real values and plot future demand trends. I want it to be easy to run from one main script, with clear functions for preparing the data, building the model, training it, and making forecasts. If the spreadsheet needs to be converted or the data shape needs fixing, handle that in the code. Please also make sure the output is understandable, like a chart of the forecast and basic evaluation so I can tell how well it worked.

Use the current best practices for TensorFlow, Keras, pandas, matplotlib, and scikit learn, and look up current docs online if you need to. If anything in the repo is broken or missing, just make it work in a straightforward way.