A robust optimization framework for scheduling of active distribution networks considering DER units and demand response program

The widespread penetration of new resources of electricity and thermal generation and storage in active distribution networks (ADNs) has affected many issues of the distribution network, such as generation scheduling. In consideration of that, in this paper, a problem of simultaneous scheduling of CHP units, electrical and thermal storage, auxiliary boilers, distributed generation system, and responsive loads is studied considering the uncertainties of the network. In this situation, the operator of the ADN performs day-ahead optimal scheduling of the electrical and heat generation units, taking into account the possibility of participation of responsive loads and exchanging electricity with the upstream market to minimize operating costs. Moreover, the uncertainty of energy market prices is also modeled using information-gap decision theory (IGDT) and robustness and opportuneness functions. To solve the problem, a mixed-integer linear programming is proposed. Furthermore, the proposed model is implemented on the IEEE standard 18-bus system, and its efficiency is evaluated by using various scenarios and sensitivity analyses of the optimization problem.