Title :
GridSpice: A Distributed Simulation Platform for the Smart Grid
Author :
Anderson, Kyle ; Du, Jinyang ; Narayan, Ananth ; El Gamal, Abbas
Author_Institution :
Dept. of Electr. Eng., Stanford Univ., Stanford, CA, USA
Abstract :
This paper describes GridSpice, a scalable open-source simulation framework for modeling, designing, and planning of the smart grid. GridSpice seamlessly integrates existing electric power simulation tools to enable modeling of large electric networks that blur the boundaries between generation, transmission, distribution, and markets. This is achieved via a cloud-based architecture that allows for parallelizing large simulation jobs across many virtual machines using a pay-as-you-go model. GridSpice simulations can be managed through a Representational State Transfer (REST) application programming interface (API), or through a Python library, allowing users to run simulations programmatically and interface with disparate data inputs, energy management systems (EMS), distribution management systems (DMS), and postprocessing tools. These capabilities make GridSpice an ideal tool for the development and testing of new grid control and optimization algorithms. GridSpice also provides an easy-to-use browser-based interface to allow novice users to begin without any setup or configuration on their local PC. A first implementation of the GridSpice framework integrates Gridlab-D and MATPOWER as simulation tools, and has been used for projects including optimizing the placement of distributed generation and developing optimal dispatch schedules for flexible loads. The GridSpice framework and Gridlab-D are freely available in open-source under the BSD license.
Keywords :
application program interfaces; cloud computing; distributed power generation; energy management systems; power generation dispatch; power generation scheduling; power system simulation; public domain software; smart power grids; software architecture; virtual machines; BSD license; DMS; EMS; GridSpice simulations; Gridlab-D; MATPOWER; Python library; REST API; cloud-based architecture; disparate data inputs; distributed generation placement; distributed simulation platform; distribution management systems; easy-to-use browser-based interface; electric network modeling; electric power simulation tools; energy management systems; grid control algorithm; open-source simulation framework; optimal dispatch schedule development; optimization algorithm; pay-as-you-go model; postprocessing tools; representational state transfer application programming interface; simulation job parallelization; smart grid; virtual machines; Electric vehicles; Load modeling; Multi-agent systems; Power system simulation; Smart grids; Virtual machining; Electric vehicles; multiagent systems; power system simulation;
Journal_Title :
Industrial Informatics, IEEE Transactions on
DOI :
10.1109/TII.2014.2332115