Stochastic Model Predictive Control for Integrated Energy System to Manage Real-Time Power Imbalances: Case of Denmark

As the installed capacity of renewable energy sources has been increasing, a mismatch between production and consumption is more likely to happen in real-time. Therefore, in order to settle the power imbalances in real-time and to achieve an energy efficient system, a coupling of different energy sectors and implementation of model predictive control are promising solutions. This paper explores the flexibility and synergy of the Danish energy system. Moreover, the benefits of stochastic model predictive control implemented in the real Danish energy system are shown. Danish energy system includes electric power, natural gas and district heating system. Stochastic model predictive control based on Scenario Generation Method considers several uncertainties. The simulation results have shown the larger wind utilization by power-to-gas units, an increase in energy efficiency and cost savings.