Optimal load dispatch of energy hub based on distributionally robust optimization approach in energy internet environment

The development of the energy internet has continuously strengthened the coupling relationship among different forms of energy sources. Energy hub (EH) is an important system form of multi-energy coordination and complementation in the environment of energy internet. In this regard, an optimal load dispatch model of EH with electricity, gas, heat and hydrogen is proposed, which aims to reduce the total cost of EH by optimizing the output of each unit under various operating constraints. The proposed EH model includes wind turbine (WT), combined heat and power (CHP) unit, gas boiler, electrolytic cell (EC), hydrogen storage unit (HS), thermal energy storage unit (TES) and electrical energy storage unit (EES). Then, a data-driven two-stage distributionally robust optimization (DRO) method is used to deal with the uncertainty of wind energy. And the column and constraint generation algorithm (C&CG) is used to solve the proposed two-stage DRO model. The results show that the proposed data-driven DRO method has better robustness than that of stochastic programming method in dealing with wind power output uncertainty. And compared to the traditional robust optimization method, the proposed method can better realize the economy of load optimal dispatch of EH. Therefore, the proposed optimal load dispatch model plays an important role in coordinating the economy and robustness of EH in energy Internet environment.