Abstract
Nowadays, due to the high penetration of renewable energy sources such as wind generation and PV in the distribution network and the possibility of their outage, the optimal operation of the distribution grid has faced challenges. In this paper, a bi-level model based on mixed integer quadratic programming (MIQP) is proposed for the optimal operation of smart distribution networks under the worst case of the outage of renewable energy resources. At the upper-level problem, minimization of the energy losses, energy purchase, and load shedding in the demand side management program is formulated, and at the lower-level problem, the maximization of output and curtailment of renewable energy resources is modeled. At the lower level, the worst-case realization of the renewable outage is derived and at the upper level, optimal operation of the distribution network is done under the worst-case realization of renewable resources. The reformulation method based on Karush–Kuhn–Tucker (KKT) conditions is considered to solve the proposed bi-level model, which is faster and less complicated than similar algorithms. The IEEE 33-bus distribution grid is considered for the analysis of the proposed model and method, which proves the accuracy and optimal performance of the proposed model and method. The findings indicate that, with the implementation of the suggested model, the smart distribution network successfully avoided load-shedding even when various renewable resources were disconnected. Also, the proposed model in operation under normal conditions has caused a 56% reduction in losses and a 53% reduction in energy purchases compared to the outage of 6 renewable units in the distribution network.
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.