Machine Learning-Based Day-Ahead Prediction of Price-Setting Scheduled Energy in the Korean Electricity Trading Mechanism.
Donghun LeeKwanho KimSang Hwa SongPublished in: IEEE Access (2023)
Keyphrases
- electricity markets
- machine learning
- electricity consumption
- power generation
- electric power
- short term
- prediction accuracy
- market clearing
- load forecasting
- unit commitment
- scheduling problem
- machine learning algorithms
- energy consumption
- solar energy
- prediction error
- market participants
- predictive modeling
- data mining
- software agents
- long term
- multi agent systems
- wind power
- competitive market
- market prices
- renewable energy
- power distribution systems
- morphological analysis
- prediction model
- natural language processing
- information extraction
- active learning
- feature selection
- stochastic programming
- bidding strategies
- energy saving
- business models
- foreign exchange
- power system
- computational intelligence
- np hard
- reinforcement learning
- forecast models