Day-ahead Chance-constrained Energy Management of Energy Hubs: A Distributionally Robust Approach

The day-ahead management schedules of hybrid energy hubs are intricate and usually exposed to various uncertainties with the penetration of renewable sources and different demands. Furthermore, it is difficult to access to precise probability distribution functions and exact moment information of uncertain variables. To cope with these issues, an energy management scheme based on the distributionally robust optimization approach is developed for the energy hub. It makes no assumptions of certain probability distributions and can be implemented with limited empirical data and partial information of underlying uncertainties. The operational strategy can provide decision makers with a preliminary and robust optimal solution in the day-ahead market. Numerical results illustrate the economical benefit of the energy model, and the effectiveness of the proposed approach in chance-constrained energy management is demonstrated by comparing with other cases.