A medium-term hybrid IGDT-Robust optimization model for optimal self scheduling of multi-carrier energy systems

Introducing new technologies in co-generation and tri-generation systems has led to a rapid growth toward the energy hubs (EHs) as an effective way for coupling among various types. On other hand, have usually been exposed uncertain environments due presence of renewable sources (RESs) interaction with electricity markets. Hence, this paper develops novel optimization framework based on hybrid information gap decision theory (IGDT) robust (RO) handle optimal self-scheduling EH within medium-term horizon large consumers. The proposed mixed-integer linear programming (MILP) aims capture advantages both IGDT RO techniques dealing complicated binary variables achieving worst-case realization arisen from wind turbine generation day-ahead (DA) market uncertainties. approach is presented model DA price uncertainty while related generations taken into account by IGDT. Numerical results validate capability facing amount total operation cost increases 8.6 % taking uncertainties through IGDT-RO compared case considering perfect information. Besides, reveal that decisions can be operator using model.