Advanced Distribution Management Systems
NREL's advanced distribution management system (ADMS) research helps utilities meet customer expectations of reliability, power quality, renewable energy use, data security, and resilience to natural disasters and other threats.
The "advanced" elements of an ADMS go beyond traditional distribution management systems by providing next-generation control capabilities. These capabilities include the management of high penetrations of distributed energy resources (DERs), closed-loop interactions with building management systems, and tighter integration with utility tools for meter data management systems, asset data, and billing.
Grid Integration of Distributed Energy Resources
NREL has decades of experience with grid integration of DERs and has world-class teams of experts dedicated to grid integration and DER technologies, including solar, buildings, vehicles, storage, and fuel cells. NREL has deep expertise across the value chain for DER integration—from device design to nationwide impact analysis and hardware testing to deployment assistance.
Power-, Controller-, and Remote-Hardware-in-the-Loop Evaluation
The megawatt-scale power-hardware-in-the-loop capability at the Energy Systems Integration Facility allows NREL researchers and partners to conduct integration development with hardware devices in the context of real-time, dynamic grid models. Multiple bidirectional AC grid emulators, at power levels up to 2 MW, enable interconnectivity testing of multiple devices, each with a separate, simulated point of common coupling. Each point of common coupling has independent phase control that enables the re-creation of a variety of grid scenarios, such as voltage sags/surges and the complete loss of a single phase or multiple phases. Both Opal-RT/RT-Lab and RTDS/RSCAD real-time simulation platforms are available to command the AC grid emulators based on system simulations. In addition, NREL developed approaches to co-simulate power-hardware-in-the-loop in real time with commercially available power systems simulation software. This flexible architecture also enables co-simulation and machine interfacing.
Advanced Distribution Management System Test Bed
The ADMS test bed is a national, vendor-neutral effort funded by the Department of Energy Office of Electricity’s Advanced Grid Research Program to accelerate industry development and the adoption of ADMS capabilities. The test bed enables utility partners, vendors, and researchers to evaluate existing and future ADMS, distributed energy resource management system (DERMS), and other utility management system applications in a realistic laboratory environment.
The ADMS test bed is an evaluation platform that consists of software simulations of large-scale distribution systems and field equipment integrated through hardware-in-the-loop techniques that realistically represent a power distribution system to a commercial or precommercial ADMS. The ADMS is interfaced to the test bed using industry standard communication protocols so it can be deployed as it would be in a utility environment. The test bed can integrate distribution system hardware in the Energy Systems Integration Facility for hardware-in-the-loop experiments and makes use of the facility’s advanced visualization capabilities, including 3D visualization. The test bed can also integrate simulations of end-use loads in buildings as well as home energy management system controllers with the distribution system simulation using the Hierarchical Engine for Large-scale Infrastructure Co-Simulation (HELICS), an open-source, cyber-physical-energy co-simulation framework for electric power systems.
Open-Source Platform and Applications for Advanced Distribution Management Systems
NREL is partnering with Pacific Northwest National Laboratory to build an open-source ADMS platform, GridAPPS-D, that will accelerate the deployment of ADMS technologies to address the operational challenges faced by distribution utilities. GridAPPS-D has been designed to provide a services-based platform that supports the development of applications. GridAPPS-D provides a reference architecture and implementation that can be used by others to implement similar application development tools or to adapt existing systems or create new ones for operational deployment of applications that comply with standards. Researchers, utilities, and vendors can use this open-source platform to develop, test, and adopt functionalities tailored to their needs without the burden of implementing full-scale ADMS systems.
This platform can be integrated with the ADMS test bed to evaluate the performance of novel ADMS applications. By reducing the cost and complexity of deployment, and by quantifying the operational benefits, barriers to widespread deployment will be eliminated. The GridAPPS-D platform provides a data rich control environment for researchers to develop futuristic advanced distribution applications, which include the following examples: increased efficiency, reliability, and resilience with real-time DER dispatch; short-term grid forecasting, which has the capacity to pave the way for developing market-based approach to manage distribution assets and flexible resources; and solar forecasting that provides intra-hour forecasted data for DSO to include the impact of solar PV for making operational planning decisions.
The rural cooperative Holy Cross Energy connected with NREL to outfit a new zero energy development with controllable DERs, including renewables. The development, named Basalt Vista, was modeled using the ADMS test bed, where researchers implemented and studied the performance of distributed control algorithms.
NREL and Holy Cross Energy—in collaboration with Survalent, the National Rural Electric Cooperative Association, and Heila Technologies—demonstrated a novel monitoring and control paradigm to manage a variety of assets at the grid edge. Holy Cross Energy incorporated the algorithms, and Basalt Vista is gaining national attention as a zero energy success story. In this case study, the real-time optimal power flow algorithm—developed by NREL under the Advanced Research Projects Agency–Energy Network Optimized Distributed Energy Systems program—was adopted and revised to develop a prototype DERMS that fits the needs of Holy Cross Energy’s system operations.
Next, the project team will evaluate the effectiveness of coordinating Survalent’s dynamic voltage regulation application on its ADMS platform with NREL’s DERMS to achieve peak load reduction and reduce demand charges.
Read more about the partnership with Holy Cross.
Colorado's Xcel Energy is modernizing its electric grid operations in anticipation of continued growth in solar photovoltaic (PV) systems and electric vehicles. The ADMS test bed allows Xcel to quantify the impact that ADMS network-model quality will have on a Volt-VAR optimization (VVO) application. In this project, utility partner Xcel Energy—which is in the process of deploying an ADMS provided by Schneider Electric—plans to use the ADMS VVO application to reduce energy use and potentially the monthly bills for its customers.
The VVO application, when configured for energy conservation, aims to reduce energy use by flattening the voltage profile and reducing voltages across the feeder as much as possible while avoiding voltage exceedances. This is also known as conservation voltage reduction.
With the penetration of renewable generation continuing to increase in distribution systems, we can no longer assume that the voltage is lower the farther a point is located from the feeder head; therefore, the VVO application was configured for this research to use a network model and real-time measurements to optimize the set points of multiple legacy voltage control devices, including a load tap changer and four capacitor banks.
If a utility does not have a high level of confidence in the accuracy of the network model used by the ADMS, it could use more conservative constraints, keeping the voltages in the feeder higher to avoid undervoltage exceedances. This approach would result in reduced energy savings. Alternatively, a utility might invest in data remediation (specifically, data cleansing) to gain more confidence in the model so it can operate with less conservative constraints and potentially increase energy savings. Data remediation is an expensive and time-consuming process, and the results from this work will help Xcel Energy understand how much data remediation is required to achieve the desired result from its ADMS investment.
As part of the Enabling Extreme Real-time Grid Integration of Solar Energy (ENERGISE) program, NREL developed and validated Enhanced Control, Optimization, and Integration of Distributed Energy Applications (ECO-IDEA), a data-enhanced hierarchical control architecture that is a hybrid of centralized and distributed control approaches. The architecture features an ADMS operation, with synergistic ADMS and grid-edge operations, the inclusion of PV fast-regulation capabilities, and comprehensive situational awareness.
The focus of this project is to demonstrate the effectiveness of a data-enhanced hierarchical control architecture to achieve various system-level control and operation objectives. NREL partnered with Xcel Energy, Schneider Electric, the Electric Power Research Institute, and Varentec to demonstrate the novel technology on an Xcel Energy feeder through simulations and field evaluation.
In the architecture, the ADMS, grid-edge management system, and real-time optimal power flow (an NREL-patented technology) control the legacy voltage devices (load tap changer, capacitor banks), grid-edge devices, and PV inverters, respectively. The coordination of the three system-level controls enables improved voltage performance under high penetrations of PV in distribution grids.
This project is funded by the Solar Energy Technologies Office.
NREL partnered with San Diego Gas & Electric Co. to identify and demonstrate novel methods for leveraging advanced metering infrastructure (AMI)—smart meters—for advanced grid planning and operations. AMI data use is currently limited to customer billing and outage detection. The new methods will reduce the cost of operations for the utility by transforming the AMI meters into a pervasive secondary network measurement platform for monitoring the grid edge.
The current utility architecture has limited field measurements in the form of a few supervisory control and data acquisition points for each feeder. The ADMS test bed will be used to evaluate the effectiveness of a data-driven voltage control algorithm using AMI data as input, especially in the presence of high penetrations of PV. The algorithm will be deployed on GridAPPS-D, an open-source grid operations research platform.
NREL will evaluate the performance of a fault location, isolation, and restoration (FLISR) application of an ADMS on a Central Georgia EMC electric distribution system with DERs using the ADMS test bed.
FLISR is one of the distribution automation applications that utilities are most interested in. It operates groups of switches on distribution feeders to improve the reliability of power delivery after localizing outages. FLISR is an essential function for enabling a self-healing electric grid, and it directly affects grid reliability and resilience.
The presence of DERs brings both new opportunities and challenges for FLISR applications. For instance, some DERs can work as backup generation sources and help energize local networks, so more switching options can be achieved with the coordination of FLISR operations; however, the existence of DERs also brings new challenges.
For this project, the team will set up the ADMS test bed to use the FLISR application of the Survalent ADMS and a hardware-in-the-loop simulation of a feeder from Central Georgia EMC, a cooperative electric utility. The performance of the FLISR application will be evaluated for different DER locations and trip settings of DERs.
A Federated Architecture for Secure and Transactive Distributed Energy Resource Management Solutions (FAST-DERMS) is being developed to enable the provision of reliable, resilient, and secure distribution and transmission grid services through scalable aggregation and near-real-time management of utility-scale and small-scale DERs.
A flexible resource scheduler at the distribution utility level, which could be implemented on an ADMS, performs reliability-constrained economic dispatch of DERs, either directly or through a transactive market or DER aggregator. FAST-DERMS also allows for the seamless integration of any centralized distribution utility management system and a transmission energy management system at the independent system operator level.The project will end with a laboratory demonstration at NREL's ESIF using its ADMS test bed.
FAST-DERMS is being developed through funding provided by the Building Technologies Office and Office of Electricity’s Advanced Grid Research program through the Grid Modernization Laboratory Consortium. The project is led by NREL and supported by multiple partners, including Lawrence Berkeley National Laboratory, Oak Ridge National Laboratory, San Diego Gas & Electric, Southern, ComEd, Centrica, and Oracle.
Electric distribution systems are seeing an increase in the deployment of intelligent devices. This increase provides opportunities for better sensing and control; however, there are challenges associated with using a centralized sensing and control architecture.
This project uses a standards-based architecture for distributed power system controls that increases operational flexibility by coordinating centralized and distributed control systems. The combination of laboratory experiments and a field demonstration will show the effective operation of the proposed approach for a FLISR ADMS application.
NREL, Siemens Corp., Corporate Technology, Columbia University, Holy Cross Energy, and Siemens Digital Grid are addressing the challenges of situational awareness and resilience in power systems with high renewable integration. The objective of the AURORA (AUtonomous and Resilient Operation of Energy Systems with RenewAbles) project is to develop, validate, and demonstrate a three-level energy management system (EMS) containing security situational awareness, distributed microgrid coordination, and autonomous microgrid restoration technologies that significantly outperform today's EMS in terms of situational awareness, resilience, and autonomy.
The first layer of defense, the security situational awareness, supports the operator in the microgrid management system to (1) assess the power system's resilience with appropriate metrics based on solar situational awareness; (2) suggest preemptive measures to increase the resilience prior to anticipated physical threats, such as natural disasters; and (3) detect, localize, and find the root cause of cyberattacks. Security situational awareness will use advanced data analytics and power flow optimization methods.
If a contingency is so severe that it results in a microgrid management system or communications system breakdown, the second layer takes over. The distributed microgrid coordination combines distributed control and optimization methods to maintain continuity of service with a peer-to-peer energy management system or—if the communications system fails completely—communications-free energy management system.
In a worst-case scenario, where the first two layers cannot avoid a power outage, the third layer drives fast restoration of the power system. The autonomous microgrid restoration merges different techniques—including grid-forming inverter control, black start with fleets of inverters, and self-configuring local microgrid controllers—to restore power supply to critical loads autonomously, i.e., without human interaction.
This project is funded by the Solar Energy Technologies Office.
The goal of this project is to create an integrated grid management framework that will be akin to having an autopilot system for the grid’s interconnected components—from central and distributed energy resources in bulk power systems and distribution systems to local control systems for energy networks, including BMSs. In this 3-year project, NREL collaborated with Lawrence Livermore National Laboratory, Pacific Northwest National Laboratory, Sandia National Laboratory, and Los Alamos National Laboratory.
The project team developed an open framework to coordinate EMS, DMS, and BMS operations. The General Electric ADMS at NREL was virtually linked with a GE EMS and a BMS at Pacific Northwest National Laboratory. The use case of controlling flexible buildings and DERs in distribution systems to support voltages in transmission systems was demonstrated through the integrated EMS-DMS-BMS platform. New operations applications—probabilistic risk-based operations and forecasting data integration for decision support—were also deployed and demonstrated in this project. This integrated grid management framework will transform how utility operators improve situational awareness and control capabilities to (1) reduce the economic costs of power outages, (2) decrease the cost of reserve margins while maintaining reliability, and (3) decrease the net integration costs of DERs.
This is a Grid Modernization Laboratory Consortium-funded project.
The goal of this project is to develop and demonstrate an ADMS that allows DERs to improve distribution system operations and simultaneously contribute to transmission-level services. The team envisions (1) elevating load buses to the level of generator buses with respect to the degree of control authority they present to system operators and (2) simultaneously optimizing distribution-level measures such as resistive losses and nodal voltage magnitudes. NREL brings significant expertise in network optimization and distributed control of power systems to this project.
This project is funded under the Office of Electricity.
Keeping up with the meteoric increase of DERs is a challenge for utilities needing to manage the energy flow of these behind-the-meter resources. NREL is focusing on developing technology that enables utilities to monitor, estimate, and operate millions of DERs through efficient communications with only a small number of devices—instead of needing to connect to each individual system.
Researchers at NREL have developed technologies for managing large-scale distributed PV systems through two modules. The first is predictive state estimation, an advanced machine learning algorithm that communicates with a small number of existing energy sensors to estimate and forecast the operation states of an entire system. Predictive state estimation facilitates the estimation and prediction of an entire system’s conditions from only a few data points. Related matrix-completion algorithms are used by other industries to predict user choices and preferences. For example, Netflix uses a similar algorithm to recommend movies for subscribers by filling in preferences related to their browsing histories.
The second module is online multi-objective optimization, an advanced algorithm that communicates with asynchronous devices in the system, such as capacitor bands and PV arrays, to dispatch devices at different timescales. The result is the capability to operate and control up to tens of millions of solar energy arrays through a fraction of devices in a proactive fashion.
Improving the Performance of Power-Hardware-in-the-Loop Cosimulation with Quasi-Steady-State-Time-Series Models, IEEE Transactions on Industrial Electronics (2020)
Open-Source Framework for Data Storage and Visualization of Real-Time Experiments, IEEE Kansas Power and Energy Conference (2020)
Matrix Completion for Low-Observability Voltage Estimation, IEEE Transactions on Smart Grid (2020)
Design of the HELICS High-Performance Transmission-Distribution-Communication-Market co-Simulation Framework, Workshop on Modeling and Simulation of Cyber-Physical Energy Systems (2017)
View all NREL publications about advanced distribution management systems.