Behind the Meter Forecasting & Optimisation

Chief Investigators

Dr. Frits de Nijs  (Monash University)

Purpose of project

The electricity grid has seen a significant rise in the integration of prosumers, households and small business connections acting as both a producer and a consumer of electricity, as a means of mitigating rising energy costs. However, their increasing involvement in the grid introduces inherent instabilities, particularly in relation to grid frequency.  

To maintain stability, a concerted response is required and Virtual Power Plants (VPPs), being a single software-defined entity from the perspective of the market, action those responses by internally distributing controls to the individual prosumer assets. This arrangement benefits both the wider grid through increased flexibility and the individual prosumers through reduced costs for services provided. 

The real-time control system of such a VPP faces a difficult prediction and optimisation problem due to the large number of entities. This project develops and evaluates the potential of solutions that jointly tackle the prediction and optimisation problem, to improve the effectiveness of VPP control. 

Impact of project

There is evidence that savings of up to 20% (in terms of lost energy production) may be achieved through accurate forecasting and optimisation methods when applied to behind the meter assets with fixed tariff structures in homes.  

Project partners – industry and research

Monash University (Lead), SwitchDin  

Industry Reference Group members

Ausgrid, Gridsight, Synergy