GridMat: Matlab toolbox for GridLAB-D to analyze grid impact and validate residential microgrid level energy management algorithms

Residential microgrid has the capability to participate in the distribution grid as a very flexible and dynamic component for demand side energy management (energy efficiency, peak-load reduction, and demand response). Various hierarchical (appliance, home, and neighborhood level) advanced control algorithms need to be developed and validated for such residential microgrids. GridLAB-D is the most promising tool for power system modeling of a microgrid. However, it is limited in supporting advanced control algorithm development with debugging support and does not provide a user friendly interface for modeling the structural and behavioral aspects of a residential microgrid. Therefore, in this paper, we present a new Matlab toolbox (GridMat) to integrate the capabilities of domain-specific modeling & simulation tools from power system (GridLAB-D) and control (Matlab). The GridMat tool supports user friendly model creation, robust debugging, and intelligent grid impact analysis utilities. To demonstrate the capability of GridMat, we have implemented three different levels of energy management controllers (including direct load control) for a residential microgrid using this tool to reduce and shift peak load according to Time-Of-Use (TOU) electricity rate.

[1]  R D Zimmerman,et al.  MATPOWER: Steady-State Operations, Planning, and Analysis Tools for Power Systems Research and Education , 2011, IEEE Transactions on Power Systems.

[2]  Peter Palensky,et al.  Modelica-enabled rapid prototyping of cyber-physical energy systems via the functional mockup interface , 2013, 2013 Workshop on Modeling and Simulation of Cyber-Physical Energy Systems (MSCPES).

[3]  Tullie Circle,et al.  AMERICAN SOCIETY OF HEATING, REFRIGERATING AND AIR-CONDITIONING , 2013 .

[4]  Mohammad Abdullah Al Faruque,et al.  A model-based design of Cyber-Physical Energy Systems , 2014, 2014 19th Asia and South Pacific Design Automation Conference (ASP-DAC).

[5]  Yanan Wang,et al.  Research on component-based approach load modeling based on energy management system and load control system , 2012, IEEE PES Innovative Smart Grid Technologies.

[6]  Lan Zhu,et al.  Design and Simulation for Microgrid System Based on Homer Software , 2011 .

[7]  Saifur Rahman,et al.  Impact of TOU rates on distribution load shapes in a smart grid with PHEV penetration , 2010, IEEE PES T&D 2010.

[8]  Amit Narayan,et al.  GridSpice: A Distributed Simulation Platform for the Smart Grid , 2013, IEEE Transactions on Industrial Informatics.

[9]  Arquimedes Canedo,et al.  Intelligent and collaborative embedded computing in automation engineering , 2012, 2012 Design, Automation & Test in Europe Conference & Exhibition (DATE).

[10]  W. H. Kersting,et al.  Radial distribution test feeders , 1991, 2001 IEEE Power Engineering Society Winter Meeting. Conference Proceedings (Cat. No.01CH37194).

[11]  A.P.S. Meliopoulos.  Challenges in simulation and design of /spl mu/Grids , 2002, 2002 IEEE Power Engineering Society Winter Meeting. Conference Proceedings (Cat. No.02CH37309).

[12]  Truong Nghiem,et al.  MLE+: a tool for integrated design and deployment of energy efficient building controls , 2012, SIGBED.

[13]  Simon Parkinson,et al.  A test bed for self-regulating distribution systems: Modeling integrated renewable energy and demand response in the GridLAB-D/MATLAB environment , 2012, 2012 IEEE PES Innovative Smart Grid Technologies (ISGT).

[14]  K. Schneider,et al.  GridLAB-D: An open-source power systems modeling and simulation environment , 2008, 2008 IEEE/PES Transmission and Distribution Conference and Exposition.

[15]  Martin Maier,et al.  Communications and power distribution network co-simulation for multidisciplinary smart grid experimentations , 2012, SpringSim.

[16]  Mohsen Jafari,et al.  Optimal energy management in community micro-grids , 2012, IEEE PES Innovative Smart Grid Technologies.

[17]  Amit Narayan,et al.  GridSpice: A distributed simulation platform for the smart grid , 2013 .

[18]  J. C. Fuller,et al.  Communication simulations for power system applications , 2013, 2013 Workshop on Modeling and Simulation of Cyber-Physical Energy Systems (MSCPES).