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CETC Number 2011-137 / 2012-03-19
Marc-André Moffet and Frédéric Sirois, École polytechnique de Montréal
David Beauvais, CanmetENERGY
New grid simulation tools are required for the progressive development of a Smart Grid able to manage distributed generation, charging of electric cars or of many special protection systems. Properly modelling and simulating the grid is among some of the challenges posed by the progressive deployment of a large number of distributed resources, including infrastructure related to flexible loads and storage. What is basically needed is greater granularity of information, as well as better performing analysis tools that are capable of processing a larger quantity of information over time.
The advent of smart grids has led to new grid functions that bring with them their own challenges for the planner. Integrating the decentralized generation of renewable energy may reverse loadflow direction and send power to the transmission network. A high penetration of this resource on a weak grid may result in voltage surges at the end of the distribution line, and thereby require a review of the voltage regulation and grid protection. With the electrification of transportation, charging electric cars may overload grid components upstream from electric vehicle charging stations. Finally, managing peak demand brings about changes to the load profile, thereby affecting grid planning criteria and practices. In the mid‐term, the smart grid aims to take greater advantage of these distributed resources. In the event of a grid outage the goal is that, with distributed generation and additional support for storage, demand management and automated reconfiguration, it will be possible to island the load, in order to create an autonomous micro‐grid and thereby maintain a community’s power supply.
In order to address these numerous technical challenges, electrical distribution network engineers will need to add new techniques to their repertoire. They must be able to do "annual" type simulations (time series simulation), as well as long‐term transitory simulations (in minutes) to evaluate, for example, the effect of a drop in solar generation due to a passing cloud on grid voltage, or to optimize management of demand and power storage resources. It is in this perspective that we will present three recently developed electrical distribution network simulation tools: GridLAB‐D, OpenDSS and APREM. These software applications are first and foremost aimed at grid planners, not operators. They are open‐source code and available free of charge: online, in the case of OpenDSS and GridLAB‐D, or on request, in the case of APREM.
A description of these software applications and their functions is provided in this report. Two case studies are simulated with the software applications, and they serve as a basis for comparison concerning their respective performances.
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