Stochastic model predictive control for optimal energy management of district heating power plants

In this paper a control strategy for the optimal energy management of a district heating power plant is proposed. The main goal of the control strategy is to reduce the running costs by optimally managing the boilers, the thermal energy storage and the flexible loads while satisfying a time-varying request and operation constraints. The optimization model includes a detailed modeling of boilers operating constraints, energy thermal energy exchange and the operating modes of the power plant layout. Furthermore, the uncertainty in power demand and renewable power output, as well as in weather conditions, is handled by formulating a two-stage stochastic problem and incorporating it into a model predictive control framework. A simulation evaluation based on the real data and the layout of a Finnish power plant is conducted to assess the performance of our proposed framework.