Abstract:Many critical loads rely on simple backup generation to provide electricity in the event of a power outage. An Energy Surety Microgrid TM can protect against outages caused by single generator failures to improve reliability. An ESM will also provide a host of other benefits, including integration of renewable energy, fuel optimization, and maximizing the value of
“…• Sandia National Laboratory methodology (Jensen et al 2015): System requirements and threats should be defined early in the process. • U.S. Army Corps of Engineers process for SPIDERS (ERDC CERL 2011): DoD procurement is unique and requires specific procurement-related considerations.…”
“…• Sandia National Laboratory methodology (Jensen et al 2015): System requirements and threats should be defined early in the process. • U.S. Army Corps of Engineers process for SPIDERS (ERDC CERL 2011): DoD procurement is unique and requires specific procurement-related considerations.…”
“…MG electric system design: The design of MG is a broad topic covering: (1) the siting and sizing of MG assets, (2) the design of the control and communication system, and (3) the design of the protection strategy [7]. There are several existing software tools for conventional MG design, e.g., Hybrid Optimization of Multiple Energy Resources (HOMER) [8], Distributed Energy Resources Customer Adoption Model (DER-CAM) [9], MG Design Toolkit (MDT) [10], and Energy Surety MG [11]. However, none of them can be directly used to design flexible MG with dynamic boundary.…”
Section: Introductionmentioning
confidence: 99%
“…The Energy Surety MG software includes a design methodology with energy reliability and resiliency as top design priorities [11]. The method uses Monte-Carlo simulations to assess the reliability under equipment failures and attacks and has been applied in the design process of military base MGs.…”
In contrast with conventional microgrids (MGs) with fixed boundaries, a smart and flexible MG with dynamic boundary is introduced in this paper. Such a MG can dynamically change its boundary by picking up or shedding load sections of a distribution feeder depending on its available power, leading to more flexible operation, better utilization of renewables, smaller size of energy storage system, higher reliability, and lower cost. To achieve a flexible MG, the main challenges in MG design are addressed, including recloser placement, MG asset sizing considering resilience, system grounding design, and protection system design. Meanwhile, a hierarchical structure is employed to design and implement the MG controller. On top of the functions defined in IEEE 2030.7-2018, a few new functions, e.g., online topology identification and PQ balance, are added, while the planned/unplanned islanding and reconnection functions are enhanced. The controller is implemented on a CompactRIO, a general-purpose hardware platform provided by National Instruments (NI), and tested on a controller hardware-in-the-loop setup based on an OPAL-RT real-time simulator and a reconfigurable power electronic converter-based hardware testbed. The test results have validated the performance of the developed controllers. Such a flexible MG and its controller have been deployed at a municipal utility, and part of the controller's functions have been tested on-site.
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