ANDES: grid capacity planning using a bottom-up, profile-based load forecasting approach

Abstract

Liander, a distribution network operator (DNO) in the Netherlands, faces potential challenges due to changing behaviour of its customers. New techniques such as electrical vehicles, solar photovoltaic (PV), and heat pumps (HPs) can have a huge impact on the loads in the grid. This study evaluates ANDES, a load forecast model developed by Alliander that can make forecasts of future grid load for 40 years ahead, for multiple scenarios and from low-voltage feeders up to high-voltage/medium-voltage substations. In contrast with traditional load forecasting methods, the results of ANDES give insight into future peak loads and new load profiles due to an increased amount of EV, PV, and HP in the grid. These results can be used to identify future bottlenecks in the grid and design the appropriate measures.