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Mather, Barry

Publications and source records attributed to Mather, Barry.

30 records · Page 2

Clean Grid Vision: A U.S. Perspective - Executive Summary

Clean Grid Vision: A U.S. Perspective aims to present a range of possible pathways for future grid development and call attention to some common trends. It focuses on the lessons learned through NREL’s studies of the U.S. power sector that have measured the impacts of high-penetration VRE and have tested strategies for enhancing grid flexibility and reliability. As such, this report is limited in its scope and does not attempt to review or summarize all grid integration literature. While it refers to relevant external literature to provide context when needed, this report is primarily a summary of the National Renewable Energy Laboratory’s (NREL’s) research in the past 5 years on five key topics: grid planning and operation, grid reliability at the distribution level, grid reliability at the transmission level, demand-side resources, and power markets—each corresponds to a chapter in this report. The main insights of the report are presented in this executive summary.

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Evaluating the Curtailment Risk of Non-Firm Utility-Scale Solar Photovoltaic Plants under a Novel Last-In First-Out Principle of Access Interconnection Agreement

With the increasing share of distributed energy resources on the electric grid, utility companies are facing significant decisions about infrastructure upgrades. An alternative to extensive and capital-intensive upgrades is to offer non-firm interconnection opportunities to distributed generators, via a coordinated operation of utility scale resources. This paper introduces a novel flexible interconnection option based on the last-in, first-out principles of access aimed at minimizing the unnecessary non-firm generation energy curtailment by balancing access rights and contribution to thermal overloads. Although we focus on solar photovoltaic (PV) plants in this work, the introduced flexible interconnection option applies to any distributed generation technology. The curtailment risk of individual non-firm PV units is evaluated across a range of PV penetration levels in a yearlong quasi-static time-series simulation on a real-world feeder. The results show the importance of the size of the curtailment zone in the curtailment risk distribution among flexible generation units as well as that of the “access right” defined by the order in which PV units connect to the grid. Case study results reveal that, with a proper selection of curtailment radius, utilities can reduce the total curtailment of flexible PV resources by up to more than 45%. Findings show that non-firm PV generators can effectively avoid all thermal limit-related upgrade costs.

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Rapid QSTS Simulations for High-Resolution Comprehensive Assessment of Distributed PV

The rapid increase in penetration of distributed energy resources on the electric power distribution system has created a need for more comprehensive interconnection modeling and impact analysis. Unlike conventional scenario-based studies, quasi-static time-series (QSTS) simulations 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 limitation to the adoption of QSTS simulations in interconnection studies and for determining optimal control solutions for utility operations. The solutions we developed include accurate and computationally efficient QSTS methods that could be implemented in existing open-source and commercial software used by utilities and the development of methods to create high-resolution proxy data sets. This project demonstrated multiple pathways for speeding up the QSTS computation using new and innovative methods for advanced time-series analysis, faster power flow solvers, parallel processing of power flow solutions and circuit reduction. The target performance level for this project was achieved with year-long high-resolution time series solutions run in less than 5 minutes within an acceptable error.

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Hosting Capacity Improvement Method Using MV–MV Solid-State-Transformer

As a large number of distributed generations are connected to the distribution system, research on the hosting capacity is actively being conducted. In particular, various methods, such as smart inverter functionality, co-located energy storage systems (ESS), and the use of on-load tap changers (OLTC), have been proposed to improve the hosting capacity. In this paper, a method to improve the hosting capacity by utilizing a solid-state transformer (SST) and its unique control capability is proposed. Lastly, the proposed method is verified in the distribution system of the Republic of Korea using the OpenDSS program.

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Integrated Transmission-and-Distribution System Modeling of Power Systems: State-of-the-Art and Future Research Directions

Integrated transmission-and-distribution (T&D) modeling is a new and developing method for simulating power systems. Interest in integrated T&D modeling is driven by the changes taking place in power systems worldwide that are resulting in more decentralized power systems with increasingly high levels of distributed energy resources. Additionally, the increasing role of the hitherto passive energy consumer in the management and operation of power systems requires more capable and detailed integrated T&D modeling to understand the interactions between T&D systems. Although integrated T&D modeling has not yet found widespread commercial application, its potential for changing the decades-old power system modeling approaches has led to several research efforts in the last few years that tried to (i) develop algorithms and software for steady-state and dynamic modeling of power systems and (ii) demonstrate the advantages of this modeling approach compared with traditional, separated T&D system modeling. In this paper, we provide a review of integrated T&D modeling research efforts and the methods employed for steady-state and dynamic modeling of power systems. We also discuss our current research in integrated T&D modeling and the potential directions for future research. This paper should be useful for power systems researchers and industry members because it will provide them with a critical summary of current research efforts and the potential topics where research efforts are needed to further advance and demonstrate the utility of integrated T&D modeling.

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Development of an Encoding Method on an Co-simulation Platform for Mitigating the Impact of Unreliable Communication

This report presents a hardware-in-the-loop (HIL) based modeling approach for simulating impacts of unreliable communication on the performance of centralized volt-var control and for developing an encoding method to mitigate the impacts. First, an asynchronous real-time HIL simulation platform is introduced to enable multi-rate co-simulation of a distribution system with many inverter-based distributed energy resources (DERs). The distribution system is modeled by milliseconds phasor-based models and the DERs are modeled by micro-seconds power electronic models. Communication connections between a centralized volt-var controller (modeled externally to the HIL testbed) and smart inverters are built by implementing Modbus links and the Long Term Evolution network. On this co-simulation platform, an enhanced, augmented Lagrangian multiplier based encoded data recovery (EALM-EDR) algorithm for mitigating the impact of unreliable communication is developed and validated. Simulation results demonstrate the efficacy of using the HIL-based co-simulation platform as a power grid digital twin for developing algorithms that coordinate a large number of heterogeneous control systems through wired and wireless communication links.

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Variability and Diversity Load Model Tool [SWR-20-03]

The motivation for the development of this tool and the underlying algorithms and methods was to enable the development of high-temporal resolution, realistic time-series data for quasi-static time-series (QSTS) analysis of distribution systems. Often, aggregated load profile data for a distribution circuit is available (e.g. feeder loading data collected via SCADA at the utility substation) and, while this data is typically accurate it masks the considerable variability of the 100’s or 1000’s of individual loads connected on the circuit. This tool was developed to model both the increased variability expected for these individual loads (e.g. the load of a single distribution transformer connected to 8-12 houses) and the expected diversity between loads on the circuit. It is important to note that the difference in variability and diversity, in the context of this tool, is that variability modeling only adds representative variability due to disaggregated load characteristics (e.g. the presence in the load profile of loads turning off and on like an air conditioner/oven) while the average energy profile remains the same as the user supplied power profile. Diversity modeling generates multiple individual load profiles which, in aggregate, sum to the user supplied power profile. Diversity is effectively variability in the energy usage over longer periods of time than seen in the variability model. Put another way, variability modeling supplies the expected variability due to the operation of various end-use loads and diversity modeling supplies the usage differences due to human behavior, schedules, etc. This load modeling tool was developed for use in generating data for distribution systems. Modeling is summarized by two major functions: 1) taking low resolution load profiles and adding intra-seconds variability onto the profiles, and 2) taking a user supplied load profile and distribution factors and adding both diversity and variability to the user supplied profile.

Zhu, Xiangqi↗

Dynamic hosting capacity analysis for distributed photovoltaic resources—Framework and case study

Distributed photovoltaic systems can cause adverse distribution system impacts, including voltage violations at customer locations and thermal overload of lines, transformers, and other equipment resulting from high current. The installed capacity at which violations first occur and above which would require system upgrades is called the hosting capacity. Current static methods for determining hosting capacity tend to either consider infrequent worst-case snapshots in time and/or capture coarse time and spatial resolution. Because the duration of violations cannot be captured with these traditional methods, the metric thresholds used in these studies conservatively use the strictest constraints given in operating standards, even though both worse voltage performance and higher overloads may be temporarily acceptable. However, assessing the full details requires accurately capturing time-dependence, voltage-regulating equipment operations, and performance of advanced controls-based mitigation techniques. In this paper, we propose a dynamic distributed photovoltaic hosting capacity methodology to address these issues by conducting power flow analysis for a full year. A key contribution is the formulation of time aware metrics to take these annual results and identify the hosting capacity. Through a case study, we show that this approach can more fully capture grid impacts of distributed photovoltaic than traditional methods and the dynamic hosting capacity was 60%–200% higher than the static hosting capacity in this case study.

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Data-Driven Distribution System Load Modeling for Quasi-Static Time-Series Simulation

This paper presents a data-driven distribution system load modeling methodology targeting quasi-static time-series (QSTS) simulation. The proposed methodology is appropriate for modeling down to the level of the customer transformer, and it has three main features: 1) both load pattern diversity and intra-second load variability are considered, 2) the load profiles can be populated for multiple nodes on a circuit in such a way that the diversity factor of the feeder can be defined and tuned, and 3) the load aggregation method can be used to populate the profiles for different nodes at various load aggregation levels. Furthermore, as the foundation of the modeling methodology, variability and diversity libraries have been established based on high-resolution load data collected on customer transformers from real utility feeders. The proposed modeling methodology has been used to build load data sets for both the IEEE 123-bus feeder model and a realistic utility feeder model. The QSTS simulation results on the two evaluation feeders have demonstrated that the load data sets established from the proposed modeling methodology can effectively capture the load impact on feeder operations. For the realistic utility feeder, the effectiveness of the proposed methodology has also been validated by comparing the voltage characteristics of the feeder with modeled loads and the voltage characteristics of realistic voltage data from the same feeder.

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