AI-based Process Control c/o Armac BV

The aim of the Experiment is to improve the heat demand prediction and valve settings in the substations, based on the weather predictions of the district heating (DH) system of Stadsverwarming Purmerend. The weather conditions (apart from the behaviour of the users / clients of the DH) are one of the main variables used to plan demand of heat temperature and temperatures across the distribution network. Such an approach requires a very accurate estimation of needed heat for safe securing their operation in advance. In other words, they need accurate prediction for planning not only energy supply, but all other activities connected with this one as its purchase and preparing technology as well. The DH at Purmerend has a historical data from 10 years of operations. Moreover, the forecast of weather conditions is a non-linear problem by nature. Additional to that, the weather conditions are not limited to only temperature, but to humidity, precipitation and wind speed. Thus, due the multivariate characteristics of data, the seasonality, the need to forecast the weather conditions into different time basis, from minutes to days ahead, taking also into account the lag time in the heat distribution, the need of AI is imperative in this kind of problem, to increase the efficiency of Purmerend DH system.