This quick note outlines what we found after our conversion with you and your team. As suggested, we loaded 1547-2003 source requirements document (SRD) and then went back and loaded 1547-2018 SRD. This did result in implementing the new 1547-2018 settings. This short report focuses on the frequency-watt function and shows a couple of screen shots of the parameter settings via the Mojave HMI interface and plots of the results of the inverter with FW function enabled in both default and most aggressive settings response to frequency events. The first screen shot shows the 1547-2018 selected after selecting 1547-2003.
The inverter firmware was upgraded to version 1.09 and an initial assessment was conducted on the inverter using the equipment listed above and the response of the inverter can be seen in the following plots. This work is to base-line the response of the inverter to utility conditions and commands and further work will involve the interoperability aspect of the inverter using SunSpec dashboard to conduct the tests and configure the inverter.
Renewable energy has become a viable solution for reducing the harmful effects that fossil fuels have on our environment, prompting utilities to replace traditional synchronous generators (SG) with more inverter-based devices that can provide clean energy. One of the biggest challenges utilities are facing is that by replacing SG, there is a reduction in the systems' mechanical inertia, making them vulnerable to frequency instability. Grid-forming inverters (GFMI) have the ability to create and regulate their own voltage reference in a manner that helps stabilize system frequency. As an emerging technology, there is a need for understanding their dynamic behavior when subjected to abrupt changes. This paper evaluates the performance of a GFMI when subjected to voltage phase jump conditions. Experimental results are presented for the GFMI subjected to both balanced and unbalanced voltage phase jump events in both P/Q and V/f modes.
The high penetration of photovoltaic (PV) distributed energy resources (DER) facilitates the need for today's systems to provide grid support functions and ride-through voltage and frequency events to minimize the adverse impacts on the distribution power system. These new capabilities and its requirements have created concerns that autonomous unintentional islanding (UI) algorithms are not sufficient to prevent a condition were the loss of utility is detected. Type tests in IEEE 1547-2018 have evolved to thoroughly evaluate DER capabilities and a new method includes power hardware-in-the-loop (PHIL) testing. Sandia National Laboratories is performing a detailed laboratory comparison of the tuned Resistive, Inductive, Capacitive (RLC) circuit method using discrete elements andthe PHIL that applies the PV inverter equipment under test (EUT), real-time simulator, and a power amplifier. The PHIL method allows UI assessments without the need for potentially expensive, large,heat generating discrete loads.
The proliferation of photovoltaic (PV) distributed energy resources (DER) on distribution systems have caused concerns about electric power system (EPS) protection schemes, protection configurations, and device coordination. With the EPS designed for power to flow in one direction, the high penetration of PV-based DER has created concerns of grid reliability and protection scheme efficacy. The short-circuit current characteristics of the classical synchronous generator has been well characterized for symmetrical or unsymmetrical short circuit faults, but inverter-based DER dynamic models are not as wellknown and are generally specific to a single inverter manufacturer. There is also uncertainty in how advanced inverter controls like volt-var and low-voltage ride-through capabilities can impact the inverter fault currents. This paper performs laboratory tests to quantify the fault currents of single-phase, three-phase, and grid-forming inverters under a range of gridsupport function operating modes. The results characterize the PV DER sub-transient, transient, and steady-state equivalents. It was found that grid-support functions affect the current contribution from PV inverters.
Batteries are designed to store electrical energy. The increasing variation in time value of energy has driven the use of batteries as controllable distributed energy resources (DER). This is enabled though low-cost power electronic inverters that are able to precisely control charge and discharge. This paper describes the software implementation of an open-source battery inverter fleet models in python. The Sandia BatterylnverterFleet class model can be used by scientists, researchers, and engineers to perform simulations of one or more fleets of similar battery-inverter systems connected to the grid. The program tracks the state- of-charge of the simulated batteries and ensures that they stay within their limits while responding to separately generated service requests to charge or discharge. This can be used to analyze control and coordination, placement and sizing, and many other problems associated with the integration of batteries on the power grid. The development of these models along with their python implementation was funded by the Grid Modernization Laboratory Consortium (GMLC) project 1.4.2. Definitions, Standards and Test Procedures for Grid Services from Devices.
Most inverters for use in distribution-connected distributed energy resource applications (distributed generation and energy storage) are tested and certified to detect and cease to energize unintentional islands on the electric grid. The requirements for the performance of islanding detection methods are specified in IEEE 1547-2018, and specified conditions for certification- type testing of islanding detection are defined in IEEE 1547.1. Such certification-type testing is designed to ensure a minimum level of confidence that these inverters will not island in field applications. However, individual inverter certification tests do not address interactions between dissimilar inverters or between inverter and synchronous machines that may occur in the field. This work investigates the performance of different inverter island detection methods for these two circumstances that are not addressed by the type testing: 1) combinations of different inverters using different types of islanding detection methods, and 2) combinations of inverters and synchronous generators. The analysis took into consideration voltage and frequency ride- through requirements as specified in IEEE 1547-2018, but did not consider grid support functionality such as voltage or frequency response. While the risk of islanding is low even in these cases, it is often difficult to deal with these scenarios in a simplified interconnection screening process. This type of analysis could provide a basis to establish a practical anti- islanding screening methodology for these complex scenarios, with the goal of reducing the number of required detailed studies. Eight generic Groups of islanding detection behavior are defined, and examples of each are used in the simulations. The results indicate that islanding detection methods lose effectiveness at significantly different rates as the composition of the distributed energy resources (DERs) varies, with some methods remaining highly effective over a wide range of conditions.