GridPenguin: A District Heating Network Simulator

District heating system (DHS) optimization is becoming an increasingly important problem because of the unused potential in flexibility that could allow less energy being wasted and the integration of renewable energy. While new optimization methods are proposed every year to tackle this problem, the literature lacks a good way to benchmark...

Unlocking the Flexibility of District Heating Pipeline Energy Storage with Reinforcement Learning

Unlocking the Flexibility of District Heating Pipeline Energy Storage with Reinforcement Learning

The integration of pipeline energy storage in the control of a district heating system can lead to profit gain, for example by adjusting the electricity production of a combined heat and power (CHP) unit to the fluctuating electricity price. The uncertainty from the environment, the computational complexity of an accurate model, and the scarcity...