عنوان	Soft-switching predictive Type-3 fuzzy control for microgrid energy management
نوع پژوهش	مقاله چاپ‌شده در مجلات علمی
کلیدواژه‌ها	Economic Optimization, Soft Switching, Fuzzy Control, Machine Learning, Artificial Intelligence, SMC
چکیده	Because each mode has distinct optimization requirements, optimizing the economic performance of microgrids (MGs) in grid-connected and islanded modes presents unique issues. This research offers a novel methodology to overcome this difficulty and better use renewable resources while satisfying the growing needs of the energy market. To maximize the MG’s performance, this approach combines fuzzy control, machine learning, and artificial intelligence with soft switching technologies. Two predictive rules are used in the design of the control system to handle the particular requirements of either the grid-connected or islanded mode depending on the MG’s operational condition. The study’s findings demonstrate that, in addition to lowering energy expenses in large commercial buildings, the suggested strategy optimizes the use of renewable energy sources and storage capacity in a range of network scenarios. This method offers more flexibility in response to network changes and greatly improves energy efficiency.
پژوهشگران	والید ایادی (نفر اول)، جعفر طاووسی (نفر دوم)، امیرحسین خسروی سرونوئی (نفر سوم)، اردشیر محمدزاده (نفر چهارم)