Dynamic Stability Assessment for Integrated Transmission-Distribution System Considering Distributed Energy Resources

The AGGREGATE project team successfully developed and validated various modules for outage management. Brief summaries of each module are provided to showcase their strength for outage management and restoration for a distribution system with a high penetration of connected distribution energy resources (DERs).In recent years, inverter-based DERs have been widely deployed in distribution system. A most of behind-the-meter (BTM) solar power generation is not visible to the utility. The data-driven DER and load estimation modules are using machine learning (ML) and artificial intelligence (AI) to manage this issue, which provides an opportunity for distribution system operators (DSOs) to operate systems and make decisions in real-time for a distribution system with a high penetration of DERs deployed. Also, the estimated DER and true load can be further leveraged in network aggregation and cold-load pick up estimation for reducing the computing complexity and providing for fast restoration. After load demand and DER power generations have been estimated, the information will support topology and state estimation(SE). The topology estimation module demonstrated the viability of mixed integer linear programming (MILP) formulation to estimate the most likely operational radial topology and outage sections using power flow measurements, historical/estimated load and DERs data and smart meter ping measurements. Formulation includes continuous (power flow, load and DERs data) and binary measurements (smart meter ping measurements) in a single formulation. Errors in continuous data and binary data are modeled as normal distribution and Bernoulli distribution, respectively. In the future distribution grid, the power injection from controllable DERs will be essential for efficient and resilient grid operation. However, determining the optimal DER injections and restoration actions is dependent on knowledge of the system states. State estimation (SE), already the cornerstone of transmission energy management systems, will become commonplace in distribution management systems as more measurements become available from deployment of automated metering infrastructure (AMI). Observability analysis is the first step in SE, as it determines the sufficiency of the available measurements for accurately estimating the current system states. A new type of pseudo-measurement called a Correlational Measurement (CM) is introduced in this module, to enhance the observability of the system to enable more accurate SE. CMs encapsulate knowledge of correlation between demand patterns for similar classes of loads as well as injection patterns for same-technology renewable DERs. During grid contingency scenarios, DERs have been traditionally disconnected, without any fault ride-through capabilities. However, with new regulations and better technology, it is feasible for these resources to contribute to the grid’s restoration after an adverse event and hence enhance resilience. The controllability module proposes a two-step restoration scheme for the power system restoration process by leveraging additional degrees of freedom in power electronics interfaced DERs for mitigating voltage problems. In a resilience mode without the utility system, the distribution grid relies on DERs to serve critical load. In such a severe event with multiple faults on the distribution feeders, actuation of various protective devices (PDs) divides the distribution system into electrical islands. The undetected actuated PDs due to fault current contributions from DERs can delay the restoration process, thereby reducing the system resilience. The Advanced Outage Management (AOM) and the Advanced Feeder Restoration (AFR) modules developed in this project provide improved system resilience with multiple DERs. AOM identifies the faulted sections and actuated PDs in a distribution system with DERs by incorporating smart meter data. The most credible outage scenario including fault locations, PD actuations, and fault indicator (FI) failures is identified by a set of binary integer linear programming incorporating hypotheses. The AFR module serves to restore a distribution system with available energy resources taking into consideration the availability of utility sources and DERs. By partitioning the system into islands, critical load will be served with the available generation resources within islands based on the solution of a MILP. When the utility systems become available, the optimal path will be determined by a spanning tree search algorithm that reconnects these islands back to substations and restores the remaining load. The transmission and distribution (T&D) co-simulation module was used to validate the effect of a control action performed on the distribution side assets as it propagates to the transmission side. This ensures that the control action performed results in a feasible operating point on both the transmission and the distribution system. In addition to validation, the team used the T&D co-simulation module to demonstrate how distribution system assets can be used to mitigate issues on the transmission system. Specifically, the team demonstrated that appropriate switching operations on the distribution side can alleviate the line overload condition on the transmission side without causing new operational constraint violations.

Grid codes around the world are requiring grid-support functions (GSFs) and standardized interoperability interfaces for distributed energy resources (DERs) to address the rapid increase of renewable energy. However, these new GSFs need to be assessed to ensure the desired power and communication capabilities exist in the field. The IEEE 1547.1 standard outlines the conformance test procedures for DER devices and is currently undergoing a major revision to align it with IEEE 1547–2018. Once it is published (anticipated in mid-2020), GSFs in commercial PV inverters in USA and Canada will be certified to the IEEE 1547.1 conformance test procedures. Several international research laboratories are collaborating to develop a versatile open-source DER testing platform that performs automated testing of DER devices. This community of laboratories is developing open-source IEEE Std. 1547.1 test scripts to lower barriers to DER vendor internal equipment evaluations, ease product compliance testing at certification laboratories, and provide research institutions a tool to study DER behaviors. In this work, test scripts were used for test verification of GSFs, including limit active power, constant reactive power, active power-reactive power (watt-var), and prioritization of GSF response for several DER devices. Sample test results for these DER GSFs and test protocol recommendations are presented in this paper.

DOE's mission under the Distributed Energy and Electricity Reliability (DEER) Program is to strengthen America's electric energy infrastructure and provide utilities and consumers with a greater array of energy-efficient technology choices for generating, transmitting, distributing, storing, and managing demand for electric power and thermal energy. DOE recognizes that distributed energy technologies can help accomplish this mission. Distributed energy (DE) technologies have received much attention for the potential energy savings and electric power reliability assurances that may be achieved by their widespread adoption. Fueling the attention has been the desire to reduce greenhouse gas emissions and concern about easing power transmission and distribution system capacity limitations and congestion. However, these benefits may come at a cost to the electric utility companies in terms of lost revenue and other potential impacts on the distribution system. It is important to assess the costs and benefits of DE to consumers and distribution system companies. DOE commissioned this study to assess the costs and benefits of DE technologies to consumers and to better understand the effect of DE on the grid. Current central power generation units vent more waste heat (energy) than the entire transportation sector consumes and this wasted thermal energy is projected to grow by 45% within the next 20 years. Consumer investment in technologies that increase power generation efficiency is a key element of the DOE Energy Efficiency program. The program aims to increase overall cycle efficiency from 30% to 70% within 20 years as well. DOE wants to determine the impact of DE in several small areas within cities across the U.S. Ann Arbor, Michigan, was chosen as the city for this case study. Ann Arbor has electric and gas rates that can substantially affect the market penetration of DE. This case study analysis was intended to: (1) Determine what DE market penetration can realistically be expected, based on consumer investment in combined heat and power systems (CHP) and the effect of utility applied demand response (DR). (2) Evaluate and quantify the impact on the distribution utility feeder from the perspective of customer ownership of the DE equipment. (3) Determine the distribution feeder limits and the impact DE may have on future growth. For the case study, the Gas Technology Institute analyzed a single 16-megawatt grid feeder circuit in Ann Arbor, Michigan to determine whether there are economic incentives to use small distributed power generation systems that would offset the need to increase grid circuit capacity. Increasing circuit capacity would enable the circuit to meet consumer's energy demands at all times, but it would not improve the circuit's utilization factor. The analysis spans 12 years, to a planning horizon of 2015. By 2015, the demand for power is expected to exceed the grid circuit capacity for a significant portion of the year. The analysis was to determine whether economically acceptable implementation of customer-owned DE systems would reduce the peak power demands enough to forestall the need to upgrade the capacity of the grid circuit. The analysis was based on economics and gave no financial credit for improved power reliability or mitigation of environmental impacts. Before this study was completed, the utility expanded the capacity of the circuit to 22 MW. Although this expansion will enable the circuit to meet foreseeable increases in peak demand, it also will significantly decrease the circuit's overall utilization factor. The study revealed that DE penetration on the selected feeder is not expected to forestall the need to upgrade the grid circuit capacity unless interconnection barriers are removed. Currently, a variety of technical, business practice, and regulatory barriers discourage DE interconnection in the US market.

Distributed energy resources (DERs) are transforming the operation and planning of both distribution and transmission grids. Stability impacts from the increasing generation contribution of DERs have been widely recognized in distribution systems and are emerging in transmission systems. There is a need for the development of transmission hosting capacity studies of DERs so utilities will be able to predict and prevent instabilities, reductions in reliability on the electrical grid, and create planning methodologies that enable the continued growth of DERs. This paper evaluates the impact of different modeling considerations for assessing hosting capacity of DERs in transmission systems through analysis on a 2,000-bus synthetic grid test system. The modeling considerations include transient and steady state contingencies, use of dynamic load and DER models with voltage support control, dynamic load composition, and seasonal and loading scenarios. The results demonstrate that transient stability evaluations are more limiting than steady state analysis, the use of voltage support control in DERs can increase hosting capacity in the system, and large variations in hosting capacity can be found when assessing between seasonal variations. From comparing system factors the amount of wind generation in the system was a critical factor for hosting capacity in this study.

The decarbonization of the energy sector has led to a significant high penetration of distributed energy resources (DERs), particularly photovoltaic (PV) systems, in low-voltage (LV) distribution networks. To maintain grid stability, recent standards (e.g., IEEE 1547-2018) mandate DERs to provide grid-support functionalities through smart inverters (SIs), which typically operate autonomously based on local measurements. However, as DER penetration increases, uncoordinated control modes of SIs can lead to adverse interactions, compromising system efficiency, voltage regulation, and overall stability. While previous studies have demonstrated the benefits of coordinated inverter control and optimal dispatch strategies, the system-wide impacts of heterogeneous SI groups operating under different control modes remain largely unexamined. This paper addresses this gap by assessing the dynamic interactions among multiple SI groups with varying control strategies, namely: Constant Power Factor (CPF), Volt-VAR, and Volt-Watt modes. Furthermore, the analysis covers both resistive and inductive feeder types. The validation is performed using a real-time setup. The CIRGE low-voltage (LV) distribution network is simulated in the Opal-RT platform as the test network, enabling realistic and high-fidelity evaluation of SI control interactions under practical grid conditions.

Distributed energy resources (DER) such as photovoltaic (PV) systems, when deployed in a large scale, are capable of influencing significantly the operation of power systems. Looking to the future, stakeholders are working on standards to make it possible to manage the potentially complex interactions between DER and the power system. In 2009, the Electric Power Research Institute (EPRI), Sandia National Laboratories (SNL) with the U.S. Department of Energy (DOE), and the Solar Electric Power Association (SEPA) initiated a large industry collaborative to identify and standardize definitions for a set of DER grid support functions. While the initial effort concentrated on grid-tied PV inverters and energy storage systems, the concepts have applicability to all DER. A partial product of this on-going effort is a reference definitions document (IEC TR 61850-90-7, Object models for power converters in distributed energy resources (DER) systems) that has become a basis for expansion of related International Electrotechnical Commission (IEC) standards, and is supported by US National Institute of Standards and Technology (NIST) Smart Grid Interoperability Panel (SGIP). Some industry-led organizations advancing communications protocols have also embraced this work. As standards continue to evolve, it is necessary to develop test protocols to independently verify that the inverters are properly executing the advanced functions. Interoperability is assured by establishing common definitions for the functions and a method to test compliance with operational requirements. This document describes test protocols developed by SNL to evaluate the electrical performance and operational capabilities of PV inverters and energy storage, as described in IEC TR 61850-90-7. While many of these functions are not currently required by existing grid codes or may not be widely available commercially, the industry is rapidly moving in that direction. Interoperability issues are already apparent as some of these inverter capabilities are being incorporated in large demonstration and commercial projects. The test protocols are intended to be used to verify acceptable performance of inverters within the standard framework described in IEC TR 61850-90-7. These test protocols, as they are refined and validated over time, can become precursors for future certification test procedures for DER advanced grid support functions.

Distributed Energy Resources (DERs) installed on low-voltage distribution systems, both utility-owned and nonutility owned may be employed to make improvements to system resiliency and power quality, in addition to simply serving load demand. By selectively dispatching active and reactive power from these existing DERs, improvements in voltage profiles and service availability during adverse events may be achieved. Further benefits can be gained by optimally choosing which DERs to dispatch power from, and the distribution of power from those DERs. For a given operating condition, using Linear Programming methods, optimal power dispatch values for individual DERs can be determined, while considering variables such as voltage gains, losses in the lines and the DERs, and DER reserve capacities. One such optimization technique is developed in this paper, and results from a real-time simulation study on a modified IEEE 13-bus distribution system with three DERs, are being presented. The operation of the optimized DER selection and dispatch algorithm is shown during normal operation of the transmission system when the DERs operate in grid-connected mode. Similar analyses can drive decision making during transmission system failure when the DERs operate in grid-forming or islanded mode.

With the proliferation of Distributed Energy Resources (DER), Grid Support Functions (GSFs) have been widely deployed. With the object to maintain the frequency and voltage stability during the grid-connected operation, GSFs, however, has raised great concerns on the effectiveness degradation of islanding prevention. Focusing on it, this paper evaluates the performance of the widely used islanding detection method, Slip-Mode Frequency Shift (SMS) operating together with GSFs. First, a small-signal model for this control combination is firstly derived, facilitating the investigation of interaction mechanism between GSFs and SMS. Accordingly, the optimal range of SMS coefficient is identified to guarantee both a successful islanding detection when an island forms and a stable operation during the grid-connected condition. It is observed that several key parameters, especially the slope and the open-loop response time of GSFs, as well as the SMS coefficient, jointly dominate the effectiveness of the islanding detection and should be deliberately designed. Finally, extensive simulations and controller hardware-in-the-loop (HIL) tests are performed to validate the above analysis.

The electric power grid is undergoing a tremendous transformation due to the increasing penetration of renewable energy resources beginning with wind and more recently with the distributed energy resources (DERs) such as solar and battery storage. DERs have dramatically changed the role of the distribution systems in the overall power grid, and they are expected to contribute a significant portion of power generation in the future. If current trends for DERs continue, system operation and control will need to change dramatically for improved grid reliability and resiliency. As renewable resources increase in penetration, new and challenging operational, planning, and design problems are expected to emerge. Some of the key challenges that arise in the planning and operation of the future grid are: 1) Quantifying the impact of high DER penetration in distribution systems on bulk grid behavior over multiple time scales. 2) Identifying whether a particular DER configuration/settings have a large impact on the overall grid behavior. These challenges can be addressed in an offline manner using detailed T&D grid models and they can also be addressed in an online manner using sensor measurements. In particular, the advancement and planned growth in sensor technology in power grid over various voltage levels provide us with a unique opportunity to tackle these challenges from a data analytic perspective without needing detailed T&D grid models. A few questions that naturally arise when addressing the challenges from DERs using sensor data are: 1) How can we use limited sensor measurements to monitor & control voltage stability and small signal stability of the bulk system? 2) How can we ensure that the developed data analytic methods are robust to data availability and quality issues? 3) How can we compute the developed analytics in a scalable manner using streaming measurements? In this project, we addressed the aforementioned challenges arising from DERs and answered the questions raised above on how to effectively use the sensor measurements to enhance the reliability and performance of the electric grid. Thus, the overarching goal of this project is to develop effective reduced/representative system models from data that make the computational complexity sufficiently manageable so as to be useful to simulate, analyze, and even control complex non-linear power systems dynamics with large penetrations of DERs. In order to achieve the objective, the project team established a four-fold technical approach 1) Formulated a combined transmission-distribution co-simulation framework for data generation and validation, 2) Derived reduced/representative models of power systems based on data-driven methods for efficient computation and appropriate representation of system behavior, 3) Developed data driven characterization of power system behavior based on transfer operator theory, machine learning and optimization for model estimation, 4) Incorporated a scalable data management and processing architecture using distributed Kafka streaming applications that coordinate input data streams to the developed data analytics. The key accomplishments of the project are: 1) Development of a scalable multi-timescale T&D co-simulation framework (both for steady state and for dynamic co-simulation) using commercial solvers (PSSE and GridLAB-D). The steady-state T&D co-simulation interface is shared with our industry partner (PJM). 2) A structured reduced order dynamic model of distribution systems that can represent partial motor stalling along with a systematic procedure to derive the model parameters. 3) A PMU based online method to monitor, localize and mitigate fault-induced delayed voltage recovery using DER reactive support and load control in distribution systems. 4) Development of linear operator based robust methodologies for dynamic state estimation, uncertainty quantification, system identification and trajectory prediction for power system dynamics. 5) An adaptive damping control for utilizing wind energy resources to provide oscillation damping and system stability. 6) Implementation of Kafka-based framework for efficient processing of streaming data using Linux-based local virtual environment.

Receding horizon load restoration for coupled transmission and distribution system considering load-source uncertainty

Distributed energy resources (DER) have become a popular solution to modern-day issues surrounding the efficiency and reliability of power generation, as well as climate change concerns. Energy centers are shifting towards incorporating smart inverters with embedded functionalities such as high voltage ride through (HVRT), low voltage ride through (LVRT), active and reactive power compensation. However, the integration of smart inverters leave DER systems highly vulnerable to cybersecurity threats. The distributed network protocol 3 (DNP3) is a common method of communication between grid-tied hardware. Despite its popularity, the level of security leaves all hardware connected to the grid at risk of severe cyber-attacks. Thus, it is important to study any potential cybersecurity threats towards grid-tied smart inverters to mitigate cybersecurity vulnerabilities and refine existing cyber-security protections. This report describes the proposed testbed design to study cybersecurity threats to smart inverters. The testbed utilizes a real-time simulation case in RSCAD that includes a grid-tied wind turbine (WT) topology featuring two back-to-back two-level voltage source converters (BTB,2L-VSCs) and a permanent magnet synchronous machine (PMSM). The simulated case runs within the NovaCor real time digital simulator (RTDS). This report focuses on the design and implementation of a single module of the GTNETx2 card as a distributed network protocol and the configuration of an IEEE 1518 DNP database file that includes input and output variables mapped to different connection points in the grid that transmit and receive discrete, analog, and binary signals on command. This allows realistic emulation of the communication between the smart inverter and the grid for cybersecurity studies.

Due to the increased penetration in Distributed Energy Resources (DERs), especially in Photovoltaic (PV) systems, voltage and frequency regulation has become a topic of interest. Utilities have been requesting DER voltage and frequency support for almost two decades. Their request was addressed by standards such as the IEEE Std 1547-2018. With the continuous improvements in inverters’ ability to control their output voltage, power, and frequency, a group of advanced techniques to support the grid is now required by the interconnection standard. These techniques are known as Grid Support Functions (GSF), and they allow the inverter to provide voltage and frequency support to the grid as well as the ability to ride-through abnormal events. Understanding how a GSF behaves is challenging, especially when multiple GSFs are combined to help the utility to control the system voltage and frequency. This paper evaluates the effects of GSF’s on the IEEE Std 1547.1-2020 Unintentional Islanding Test 5B by comparing simulation results from a developed PV inverter model and experimental results from a Power Hardware-in-the-Loop platform.

With the increasing deployment of Distributed Energy Resources (DERs) in the distribution system, DERs presents many challenges for smooth and stable operation of the grid. For the effective management of DERs extensive communication between different components of DER and distribution system is required. To standardize the communication methods and modeling of logical nodes required for Intelligent Electronic Devices (IEDs) in DERs, data modeling of DERs is issued in IEC 61850-7-420 standard. This paper has contributed communication modeling of Green Energy Resources (GERs) and other DERs, modeling of messages exchanged among different IEDs with regard to their optimum structure & size and a Substation Communication Network (SCN) topology. End to End (ETE) time delay performance of the designed communication configuration architecture is presented using OPtimized Network Engineering Tool (OPNET). The dynamic performance result in the SCN has demonstrated the successful communication configuration for integrating the DERs in distribution system.

Enhancing the operation of smart inverters with PMU and data concentrators

The objective of this CRADA between Sandia National Laboratories (SNL) and SunSpec Alliance (SunSpec) was to create a software test platform called the System Validation Platform (SVP) that performs end-to-end certification testing of photovoltaic (PV) inverters, energy storage systems, and other distributed energy resources (DERs). The SVP automates interactions of test equipment (PV and grid simulators), data acquisition systems, and interoperable DERs to certify the devices for advanced grid-support functions and interoperability. To assist electricity grid, operators maintain voltage and frequency, new interconnection requirements in the U.S. and Europe require DERs to have grid-support functions with adjustable settings. Automating the certification process for DER devices impacts the bottom line of NRTLs because they do not need to rely on test engineers running days (or weeks) of experiments to validate the performance of the equipment. These savings can then be passed down to the DER vendors so the certification process becomes less expensive and lowers the barrier to market for PV inverters, charge controllers, and other grid-interconnected equipment. This technology can also be used as a research platform for SNL, other national labs, and universities that would like to run hardware tests with power electronics equipment.