Advanced Distribution Management Systems

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 was to demonstrate the effectiveness of a data-enhanced hierarchical control architecture to achieve various system-level control and operation objectives using NREL’s ADMS Test Bed. 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 was 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 was 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 was deployed on GridAPPS-D, an open-source grid operations research platform.

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.

NREL, Siemens Corp., Corporate Technology, Columbia University, Holy Cross Energy, and Siemens Digital Grid partnered to address 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
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.

Autonomous Restoration of Networked Microgrids Using Communication-Free Smart Sensing and Protection Units, IEEE Transactions on Sustainable Energy (2023)

Investigating Multi-Microgrid Black Start Methods Using Grid-Forming Inverters, IEEE Power and Energy Society Innovative Smart Grid Technologies Conference (2023)

Peer-To-Peer Communication Trade-Offs For Smart Grid Applications, International Conference on Computer Communications and Networks (2022)

Performance Evaluation of Peer-to-Peer Distributed Microgrids Coordination for Voltage Regulation, IEEE Power and Energy Society General Meeting (2022)

Autonomous Microgrid Restoration Using Grid-Forming Inverters and Smart Circuit Breakers, IEEE Power and Energy Society General Meeting (2022)

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 General Electric 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
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
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.

Combining Model-Based and Model-Free Methods for Stochastic Control of Distributed Energy Resources, Applied Energy (2021)

Hierarchical Management of Distributed Energy Resources Using Chance-Constrained OPF and Extremum Seeking Control, American Control Conference (2019)

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.

Climate change has resulted in increasingly impactful and more frequent extreme weather events. However, distribution utilities deploying the automated FLISR function in their ADMS software usually do not consider the available generation and/or load-modification capabilities of DERs present in the network, especially at customer premises or at the grid edge. Further, long-duration power outages can result in significant losses to society and to individuals, and these losses are not equally experienced across social groups. Therefore, this project developed an approach that can unlock the value of grid-edge DERs and increase the load restoration capability while considering the impacts on customers with varying social vulnerability. The algorithms developed in this project were integrated with the FLISR application on Survalent’s ADMS.

DER-Aware, Equitable Service Restoration to Enhance Grid Resilience and Mitigate Social Impacts Under Long-Duration Power Outages, SSRN (2024)

Distributed Energy Resource-Cognizant Upgrade Paths to the Traditional Restoration Strategy of Utilities for Improved Load Restoration, NREL Conference Paper (2023)