In Harmony. Virtual Power Plants: Predicting, Optimising and Leveraging Residential Electrical Flexibility for Local and Global Benefit

Abstract

Electrical demand flexibility is a key component to enabling a low cost, low carbon grid. In this study, residential electricity demand and flexibility is explored from the lens of a virtual power plant operator. Individual and aggregate asset consumption is analysed using a pool of >10,000 household assets over 6 years. Key safety, comfort and availability limitations are identified per asset type. Pool flexibility is analysed using a combination of past data and principled calculations, with flexibility quantified for different products and methods of control. A machine learning model is built for a small pool of 200 assets, predicting consumption 24 hours in advance. Calculated flexibility and asset limitations are then used within an optimisation model, leveraging flexibility and combining the value of self consumption and day ahead price optimisation for a residential home.