District heating network Mümmelmannsberg (Hamburg) - URBANA
Together with URBANA, a GETEC Group company, we implemented automated optimization and marketing of the cogeneration units. Two engines with an electrical output of 4.4 MW each are operated at the site. Our algorithms plan daily operation schedules and optimize electricity sales in the spot market. Through our modeling, the thermal storage can be optimally used based on forecasts. Read more in our project report.

Drayton Garden Village (London) – E.ON UK
Drayton Garden Village is an ecologically oriented housing development in west London. Here, E.ON operates a heating network that supplies the district with heat using CHP plants and gas boilers. To increase the cost-effectiveness of plant operation, our algorithms deliver the optimized operating schedules every day. The software takes into account the weather-dependent heat load, the storage potential of the buffer storage tanks as well as current spot market prices for electricity and natural gas. This leads to the most economical use of the existing plants.

Pioneer Park Hanau - GETEC
Together with Stadtwerke Hanau, GETEC is supplying heat to the innovative Pioneer Park Hanau urban quarter. A combination of three CHP plants and a heat pump ensures an efficient and future-oriented supply. An ice storage tank serves as the heat source for the heat pump. Our software service optimizes the daily use of all heat generators based on forecasts. Storage capacities and the alternative heat generators are scheduled on a quarter-hourly basis, depending on the current situation in electricity trading, in order to cover the heat demand efficiently and economically.

Heating centre Besenhorst - Stadtwerke Geesthacht
The Besenhorst heating centre supplies a new housing district in Geesthacht via a local heating network. Thanks to a large storage capacity in relation to the generation capacity, the 800kW engine can flexibly cover the heat demand of the housing district and at the same time generate additional revenue in a market-orientated manner. As heat distribution continues to expand, our forecasting algorithm adapts and updates the models for forecasting heat sales accordingly.