Electrical Flexibility Forecasting and Assessment for Heat-Pump-Based District Heating Systems
Abstract
Nowadays, simple and cost-effective solutions to extract flexibility from any possible energy asset are being heavily investigated, along with optimal strategies to offer flexibility in different markets. In this context, this work proposes an Electrical Flexibility Forecasting Engine (EFFE) conceived for district heating systems based on centralised heat pumps. The idea is implemented in the case study of Culemborg (ND), demo site of the H2020-ACCEPT project. Here, the engine is run in a typical winter day to forecast and asses both upwards and downwards flexibility, along with the minimum economically viable bids for a local market.