Thesis Work - Identifying distributed energy resources from consumption patterns

The thesis will investigate how distributed energy resources can be identified from electricity consumption data using data-driven and machine learning approaches. The project will explore load disaggregation and classification techniques to detect characteristic consumption patterns associated with specific energy resources. Improved visibility of customer assets can support applications such as load forecasting, grid planning, flexibility markets, and customer-centric energy services.

The purpose of this thesis is to evaluate the feasibility and accuracy of identifying distributed energy resources from electricity consumption data. The student will:

Review relevant literature on load disaggregation and energy asset identification.
Develop and evaluate machine learning and statistical models for detecting distributed energy resources from consumption patterns.
Assess model performance, limitations, and uncertainty.
Provide recommendations for future implementation and research.