An advanced real time energy management system for microgrids. (1st November 2016)

• Record Type: Journal Article
• Authors: Elsied, Moataz; Oukaour, Amrane; Youssef, Tarek; Gualous, Hamid; Mohammed, Osama
• Is Part Of: Energy. Volume 114(2016)
• Page Start: 742
• Page End: 752
• Publication Date: 2016-11-01
• Subjects: Distributed Energy Resources (DERs) -- MicroGrid (MG) -- Energy Management System (EMS) -- Genetic Algorithm (GA); Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2016.08.048
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: This paper presents an advanced Real-Time Energy Management System (RT-EMS) for Microgrid (MG) systems. The proposed strategy of RT-EMS capitalizes on the power of Genetic Algorithms (GAs) to minimize the energy cost and carbon dioxide emissions while maximizing the power of the available renewable energy resources. MATLAB-dSPACE Real-Time Interface Libraries (MLIB/MTRACE) are used as new tools to run the optimization code in Real-Time Operation (RTO). The communication system is developed based on ZigBee communication network which is designed to work in harsh radio environment where the control system is developed based on Advanced Lead-Lag Compensator (ALLC) which its parameters are tuned online to achieve fast convergence and good tracking response. The proposed RT-EMS along with its control and communication systems is experimentally tested to validate the results obtained from the optimization algorithm in a real MG testbed. The simulation and experimental results using real-world data highlight the effectiveness of the proposed RT-EMS for MGs applications. Highlights: Real-time energy management system of a typical MG is developed, and analyzed. RT-EMS considered the nonlinear cost function and emission constraints. MLIB/MTRACE libraries in dSPACE are used as new tools to run the optimization code. The communication system is developed based on a Zigbee communication network. Control system parameters are tuned online to achieve good tracking response.