Publications

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Distribution system analysis with ever increasing numbers of distributed energy resources (DER) requires quasistatic time-series (QSTS) analysis to capture the time-varying and time-dependent aspects of the system. Previous literature has demonstrated the benefits of QSTS, but there is limited information available for the requirements and standards for performing QSTS simulations. This paper provides a novel analysis of the QSTS requirements for the input data timeresolution, the simulation time-step resolution, and the length of the simulation. Detailed simulations quantify the specific errors introduced by not performing yearlong high-resolution QSTS simulations.

The rapidly growing penetration levels of distributed photovoltaic (PV) systems requires more comprehensive studies to understand their impact on distribution feeders. IEEE P.1547 highlights the need for Quasi-Static Time Series (QSTS) simulation in conducting distribution impact studies for distributed resource interconnection. Unlike conventional scenario-based simulation, the time series simulation can realistically assess time-dependent impacts such as the operation of various controllable elements (e.g. voltage regulating tap changers) or impacts of power fluctuations. However, QSTS simulations are still not widely used in the industry because of the computational burden associated with running yearlong simulations at a 1-s granularity, which is needed to capture device controller effects responding to PV variability. This paper presents a novel algorithm that reduces the number of times that the non-linear 3-phase unbalanced AC power flow must be solved by storing and reassigning power flow solutions as it progresses through the simulation. Each unique power flow solution is defined by a set of factors affecting the solution that can easily be queried. We demonstrate a computational time reduction of 98.9% for a yearlong simulation at 1-s resolution with minimal errors for metrics including: number of tap changes, capacitor actions, highest and lowest voltage on the feeder, line losses, and ANSI voltage violations. The key contribution of this work is the formulation of an algorithm capable of: (i) drastically reducing the computational time of QSTS simulations, (ii) accurately modeling distribution system voltage-control elements with hysteresis, and (iii) efficiently compressing result time series data for post-simulation analysis.

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A hierarchical control algorithm was developed to utilize photovoltaic system advanced inverter volt-VAr functions to provide distribution system voltage regulation and to mitigate 10-minute average voltages outside of ANSI Range A (0.95-1.05 pu). As with any hierarchical control strategy, the success of the control requires a sufficiently fast and reliable communication infrastructure. The communication requirements for voltage regulation were tested by varying the interval at which the controller monitors and dispatches commands and evaluating the effectiveness to mitigate distribution system over-voltages. The control strategy was demonstrated to perform well for communication intervals equal to the 10-minute ANSI metric definition or faster. The communication reliability impacted the controller performance at levels of 99% and below, depending on the communication interval, where an 8-minute communication interval could be unsuccessful with an 80% reliability. The communication delay, up to 20 seconds, was too small to have an impact on the effectiveness of the communication-based hierarchical voltage control.

Distribution system analysis with high penetrations of distributed energy resources (DER) requires quasi-static time-series (QSTS) analysis to capture the time-varying and time-dependent aspects of the system, but current QSTS algorithms are prohibitively burdensome and computationally intensive. This paper proposes a novel deviation-based algorithm to calculate the critical time periods when QSTS simulations should be solved at higher or lower time-resolution. This predetermined time-step (PT) solver is a new method of performing variable time-step simulations based solely on the input data. The PT solver demonstrates high accuracy while performing the simulation up to 20 times faster.

As the penetration of renewables increases in the distribution systems, and microgrids are conceived with high penetration of such generation that connects through inverters, fault location and protection of microgrids needs consideration. This report proposes averaged models that help simulate fault scenarios in renewable-rich microgrids, models for locating faults in such microgrids, and comments on the protection models that may be considered for microgrids. Simulation studies are reported to justify the models.

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The rapid increase in penetration of distributed energy resources on the electric power distribution system has created a need for more comprehensive interconnection modelling and impact analysis. Unlike conventional scenario - based studies , quasi - static time - series (QSTS) simulation s can realistically model time - dependent voltage controllers and the diversity of potential impacts that can occur at different times of year . However, to accurately model a distribution system with all its controllable devices, a yearlong simulation at 1 - second resolution is often required , which could take conventional computers a computational time of 10 to 120 hours when an actual unbalanced distribution feeder is modeled . This computational burden is a clear l imitation to the adoption of QSTS simulation s in interconnection studies and for determining optimal control solutions for utility operations . Our ongoing research to improve the speed of QSTS simulation has revealed many unique aspects of distribution system modelling and sequential power flow analysis that make fast QSTS a very difficult problem to solve. In this report , the most relevant challenges in reducing the computational time of QSTS simulations are presented: number of power flows to solve, circuit complexity, time dependence between time steps, multiple valid power flow solutions, controllable element interactions, and extensive accurate simulation analysis.

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