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A Machine Learning Based Framework For Load Forecasting And Optimal Operation Of Power Systems With Distributed Generation, Tairen Chen
Electrical and Computer Engineering ETDs
The fast development and wide utilization of distributed generations (DGs), such as Photovoltaic panels and wind turbines, provide environmentally friendly renewable energy. However, inappropriate operation, sizing, and placement of DGs could increase the power losses and reduce the stability of the power network. Load forecasting is critical to the electrical utilities to schedule power generation and distribution. In this dissertation, a framework is proposed for load forecasting and optimal operation of power system with DGs in the distribution feeder-level.
In the first part, a nonparametric method, the Bayesian Additive Regression Trees (BART), is introduced for day-ahead peak load forecasting. The …