Akademik Veri Yönetim Sistemi
Diğer Ülkelerdeki Kamu Kurumları Tarafından Desteklenmiş Proje, 2018 - 2019
Canada and worldwide are moving towards deploying clean energy systems in urban, remote
communities, and providing resilient energy systems for harsh environments and emergencies.
The deployment of off-grid energy solutions is essential for a number of installations such as
remote communities, mining, and emergencies. MOBISMART developed MOBISUN as an off-
grid solution by integrating solar, wind, battery, and traditional generators to offer off-grid
energy supply. The system can be expanded by integrating multiple units with efficient energy
management to offer high performance charging/discharging capabilities using intelligent control
with optimization algorithm. This technology has potential deployment in Canada and worldwide
for remote communities, harsh and extreme environment, and number of applications to replace
gas-based energy supply such as communications, railways, construction, pipeline, and mining
installations. There are extended user requirements to integrate large number of battery systems
in multiple MOBISUN units to increase the scale and enhance charging/discharging performance
to meet target loads. The proposed research is led by Dr. Hossam Gaber at UOIT and have the
main objective is to conduct research to enhance the design configuration and technology of
energy storage systems, and integrate intelligent control and optimization algorithms to improve
the performance of one unit and allow the integration of multiple MOBISUN units with
increased profit and ROI. Multiple MOBISUN will offer larger capacity to meet target loads and
enhanced performance. The modeling and simulation should be performed accurately, and
integrated control system will be tested for different design configuration and operation
scenarios, including different weather conditions and load profiles. Intelligent algorithms will be
developed to optimize the overall performance in terms of lifecycle cost, performance,
reliability, and safety in view of Key Performance Indicators-KPIs. The proposed control
technique will be optimized based on dynamic load and mobility models, for the selected KPIs of
multiple microgrids and storage systems and technologies.