Optimal Scheduling of Distribution Network With Autonomous Microgrids: Frequency Security Constraints and Uncertainties

Widespread integration of autonomous microgrids (MGs) into the distribution network (DN) makes the scheduling of distribution systems challenging. Especially, the uncertainties of renewable energy sources (RESs) and load demand put the MG frequency at the risk of violation for its low inertia and the high penetration of RESs. To address the schedule problems associated with uncertainties and frequency security, a day-ahead scheduling optimization model is proposed based on the chance-constrained programming (CCP) theory. The frequency security constraints and uncertainties of RESs/load demand associated with MGs are considered during the development of the proposed model. The total operation cost of the distribution system consisting of DN and MGs is minimized, while the MG frequency deviations caused by uncertainties are restricted in the predefined safe range by the proposed CCP-based model. Besides, a linearization method is presented and used to transform the proposed model into a mixed-integer linear program to determine the efficiency of the CCP-based model. Finally, numerous case studies are conducted to illustrate the effectiveness and good scalability of the proposed model and understand the advantages of using the model. The RT-LAB hardware-in-loop tests are carried out to study the real-time performance under the scheduling solved by the proposed model. Simulation and experimental results validate that the proposed model can be used to minimize the total operation cost of the DN system integrated with MGs while ensuring that the MG frequency deviations are operated within an acceptable range.