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At least 73 records · Page 4

AGGREGATE: dAta-driven modelinG preservinG contRollable dEr for outaGe mAnagemenT and rEsiliency (Report for Task 13: Functional Specification Report(Deliverable D9))

This report provides functional specification for the AGGREGATE project and associated modules/ tools being developed for outage management and restoration with the Distributed Energy Resources (DERs). This report also provide initial validation of the developed modules and performance metrics. The AGGREGATE team at this stage has been collaborating with General Electric (GE) and Seattle City Light (SCL) to move forward from offline validation to online validation using commercial advanced distribution management system (ADMS). Hence, the functional specifications documents, which outline the requirement of various modules, is provided to address the integration of the modules, including 1) real-time model update and aggregation tools module, 2) observability and controllability metric module, 3) fault location solution service restoration module, 4) transmission-distribution co-simulation module, and 5) advanced distribution management system module. integration of different AGGREGATE modules and functional specification provides the foundation for online multi-scenario testing using SCL system model.

42 ENGINEERING↗

AGGREGATE: dAta-driven modelinG preservinG contRollable dEr for outaGe mAnagemenT and rEsiliency (Report for Task 14: Model Verification/Validation Test Plan (Deliverable D10))

This report summarizes the technical progress and validation plan for each of AGGREGATE project modules, and integrated modules. The overall validation plan can be divided into two major parts. Firstly, it provides offline validation results of each module using the IEEE-123 node distribution system with certain modifications to support individual module results verification. The offline validation plan tentatively validated the usability and practicability of developed AGGREGATE tools. Secondly, the realworld test system - Seattle City Light (SCL) test feeder for verifying each module and the integrated modules using GE advanced distribution management system (ADMS) software.

42 ENGINEERING↗

Managing Uncertainty and Flexibility in Day-Ahead Electricity Markets

Net load imbalances from day ahead forecasts can lead to significant grid operations costs and are expected to increase as variable renewable energy adoption grows. We propose a new wholesale market product to manage the risk of net load imbalances called Flexibility Options. This product relies on probabilistic forecasts to estimate flexibility demand and would be co-optimized in the day-ahead market. We also propose stochastic methods that enable DER and flexible load aggregators to participate in flexibility markets while considering the uncertainty in weather and occupant behavior.

day-ahead market↗

Network-Cognizant Time-Coupled Aggregate Flexibility of Distribution Systems Under Uncertainties

Increasing integration of distributed energy resources (DERs) within distribution feeders provides unprecedented flexibility at the distribution-transmission interconnection. To exploit this flexibility and to use the capacity potential of aggregate DERs, feasible substation power injection trajectories need to be efficiently characterized. This paper provides an ellipsoidal inner approximation of the set of feasible power injection trajectories at the substation such that for any point in the set, there exists a feasible disaggregation strategy of DERs for any load uncertainty realization. The problem is formulated as one of finding the robust maximum volume ellipsoid inside the flexibility region under uncertainty. Though the problem is NP-hard even in the deterministic case, this paper derives novel approximations of the resulting adaptive robust optimization problem based on optimal second-stage policies. The proposed approach yields less conservative flexibility characterization than existing flexibility region approximation formulations. The efficacy of the proposed method is demonstrated on a realistic distribution feeder.

aggregates↗

Network-Cognizant Time-Coupled Aggregate Flexibility of Distribution Systems Under Uncertainties

Increasing integration of distributed energy resources (DERs) within distribution feeders provides unprecedented flexibility at the distribution-transmission interconnection. To exploit this flexibility and to use the capacity potential of aggregate DERs, feasible substation power injection trajectories need to be efficiently characterized. This paper provides an ellipsoidal inner approximation of the set of feasible power injection trajectories at the substation such that for any point in the set, there exists a feasible disaggregation strategy of DERs for any load uncertainty realization. The problem is formulated as one of finding the robust maximum volume ellipsoid inside the flexibility region under uncertainty. Though the problem is NP-hard even in the deterministic case, this paper derives novel approximations of the resulting adaptive robust optimization problem based on optimal second-stage policies. The proposed approach yields less conservative flexibility characterization than existing flexibility region approximation formulations. The efficacy of the proposed method is demonstrated on a realistic distribution feeder.

adaptive robust optimization↗

AGGREGATE: dAta-driven modelinG preservinG contRollable dEr for outaGe mAnagemenT and rEsiliency (Report for Task 11 & 12: Components and Capabilities of the Resiliency Driven Outage Management and Feeder Restoration System (Deliverable D8))

This report provides progress update for the development of a outage management, feeder restoration, and restoration action feasibility check modules as part of the AGGREGATE project. Details for integration with controllability module, data driven situational awareness of network and distributed energy resources as well cyber security plan for these modules integrated with GE ADMS are also presented in the report. These three modules for outage management, feeder restoration, and restoration action feasibility check modules are developed in MATLAB and validated with a modified IEEE 123-node feeder. Results demonstrate ability of these new modules to improve the restoration process post-disaster to enhance the system resilience.

42 ENGINEERING↗

Report for Task 15: Developed Tool Verification/Validation Report (Deliverable D11): AGGREGATE: dAta-driven modelinG preservinG contRollable dEr for outaGe mAnagemenT and rEsiliency

This report summarizes the verification report for the developed modules. The team conducted verification in two phases. In phase 1, the modules were validated using offline validation methods and in phase 2 the modules were subjected to real-time validation. This report outlines the approach and the results for the modules under offline and real-time settings. The rest of the report details the functional workflow of AGGREGATE modules, we then transition to offline validation followed by real-time validation of modules. We conclude the report by discussing some of the key points of this report.

14 SOLAR ENERGY↗

A Graph-Net with Node Embeddings to Detect False Data Injection Attacks in Photovoltaic Systems

Distributed energy resources (DER) contribute to the operational stability of the larger power grid both at utility-scale as well as commercial and residential scales in aggregated forms. These DER in-turn are susceptible to increasing cyber threats. An adversary can plug into the same local network that a field photovoltaic (PV) system uses to interconnect its data loggers and inverters and manipulate certain measurements collected from the network or trick existing irradiance and inverter readings through false data injection attacks (FDIA). Control routines that rely on these measurements can propagate the false data, impacting critical decisions that result in a suboptimal operation or even cause intentional harm leading to inverter-tripping or unscheduled loads that need to be shed. To detect FDIA in PV systems, the paper introduces an attention-based graph neural network with node embeddings and applied it to a simple prototypical DC-coupled microgrid with PV, energy storage, and load. The algorithm shows a detection accuracy of up to 98.95%. The proposed FDIA detection technique will provide micro-grid operators with an effective method to safeguard their systems, guaranteeing the secure and reliable operation.

Parvez, Imtiaz [Utah Valley University]↗

Residential Demand Side Aggregation of Privacy-Conscious Consumers

The increasing adoption of smart meters has led to growing concerns regarding privacy risks stemming from the high resolution measurements. This has given rise to privacy protection techniques that physically alter the consumer's energy load profile, masking private information by using localised devices, e.g. batteries or flexible loads. Meanwhile, there has also been increasing interest in aggregating the distributed energy resources (DERs) of residential consumers to provide services to the grid. In this paper, we propose an online distributed algorithm to aggregate the DERs of privacy-conscious consumers to provide services to the grid, whilst preserving their privacy. Results show that the optimisation solution from the distributed method converges to one close to the optimum computed using an ideal centralised solution method, balancing between grid service provision, consumer preferences and privacy protection. More importantly, the distributed method preserves consumer privacy, and does not require high-bandwidth two-way communications infrastructure.

ancillary services↗

Aggregate data‐driven dynamic modeling of active distribution networks with DERs for voltage stability studies

Abstract Electric distribution networks increasingly host distributed energy resources based on power electronic converter (PEC) toward active distribution networks (ADN). Despite advances in computational capabilities, electromagnetic transient models are limited in scalability because of their reliance on exact data about the distribution system and each of its components. Similarly, the use of the DER_A model, which is intended to examine the combined dynamic behavior of many DERs, is limited by the difficulty in parameterization. There is a need for improved dynamic models of DERs for use in large power system simulations for stability analysis. This paper proposes an aggregate model‐free, data‐driven approach for deriving a dynamic partitioned model (DPM) of ADNs. Detailed residential distribution feeders were first developed, including PEC‐based DERs and composite load models (CMLDs), from which the aggregated DPM was derived. The performance was evaluated through various case studies and validated against the detailed ADN model and state‐of‐the‐art DER_A model with CMLD. The data‐driven DPM achieved a of over 90%, accurately representing the aggregated dynamic behavior of ADNs. Furthermore, the DPM significantly accelerated the simulation process with a computational speedup of 68 times compared to the detailed ADN and a 3.5 times speedup compared to the DER_A CMLD model.

42 ENGINEERING↗

AGGREGATE: dAta-driven modelinG preservinG contRollable dEr for outaGe mAnagemenT and rEsiliency (Report for Task 9: Viability of Data-Driven Approach for Outage Management (Deliverable D6))

This technical report is provided to US Department of Energy for progress made on the AGGERGATE project led by the Washington State University. This report is specifically related to the deliverable: ’D6: Technical report discussing the viability of the developed data-driven models and co-simulation architecture for models for operation in a real-world operational setting and the results of Tasks 1 to 8, summarizing the project findings and accomplishments to date’.

42 ENGINEERING↗

AGGREGATE: dAta-driven modelinG preservinG contRollable dEr for outaGe mAnagemenT and rEsiliency (Report for Task 10: Controllability and Observability Analysis (Deliverable D7))

It is common to have less than full observability for distribution systems, as the number of available measurements are not sufficient. Considering increasing penetration of distributed energy resources (DERs), it is imperative to understand and control distribution systems better. Developed for the transmission system, the original numerical observability analysis methods were based on the canonical DC Power Flow (DC-PF) model. However, the DC-PF model is ill-suited for the distribution system in which line resistance to reactance (R/X) ratios can be near unity. In this report, we apply the non-iterative Observability Test (OT) and Observable Island Identification Procedure (OIIP) in to the gain matrix from the distribution system state estimator. Because sensors are few in distribution systems, pseudo-measurements based on historical load profiles and zero-injection virtual measurements are often employed to ensure observability. However, both the observability and the accuracy of the state estimates are uncertain when historical data is limited/unavailable.

42 ENGINEERING↗

Achieving Cyber-Resilience for Power Systems using a Learning, Model-Assisted Blockchain Framework

The secure integration and management of distributed energy resources (DER) and power aggregators in the electric grid requires secure communications and a physics-aware Command and Control (C2) strategy. A Blockchain (BC)-based overlay network was developed to provide a security layer for the existing power grid network that mitigates risks in current and legacy network and C2 protocols. By integrating a Model-Assisted Machine Learning (MAML) framework with a Secure Blockchain Overlay Network (SBON) a defense-in-depth strategy was achieved. In our approach, the MAML framework leveraged a smart contract framework to gather network data and learn the dynamics of DER to develop detection strategies for attacks targeting sensors and actuators used by DER. The MAML framework learned dynamical systems models for individual DERs to detect sensor attacks. For DER we utilized a Digital Twin (DT) to accelerate the learning process for a model resistant to stealthy attacks. The project created DT for PV inverters and BESS. The DTs were coupled with a model-assisted, data-driven learning of DER behavior. Specifically, we evaluated architectures for model-based learning with model-free fine-tuning. Additionally, differential privacy techniques were used to obfuscate data, while still allowing the computation of attack detection results based on obfuscated data. The SBON developed leverages a private permissioned blockchain network orchestrated with the Hyperledger Fabric framework. To connect the cyber world, which orchestrates the blockchain fabric, and the physical world where the power network resides, we developed a system implementation to enable the secure interaction of the physical world and the abstracted blockchain.

97 MATHEMATICS AND COMPUTING↗

Aggregation and Grid Security Workshop Report

The Aggregation and Grid Security Workshop - held on June 17-18, 2025, National Laboratory of the Rockies (NLR) in Golden, Colorado - brought together approximately 40 external stakeholders from the energy sector, including VPP owner/operators, aggregators, OEMs, utilities, testing & certification labs, trade associations, and cybersecurity vendors. Led by key facilitators, the workshop focused on addressing cybersecurity challenges and enhancing grid resilience for aggregated Distributed Energy Resources (DERs) and Virtual Power Plants (VPPs). The workshop was catalyzed by recognition that traditional, rearward-looking regulatory frameworks are insufficient to keep pace with technological change. There is a "missing understanding" of risk, an "absent security basis" for managing it, and an "untenable responsibility" due to unclear ownership and requirements. The workshop aimed to shift the mindset from reacting to past crises to proactively preparing for emerging threats, fostering forward resilience through risk simulation and collaborative action. This report summarizes the outcomes of the workshop, marking it a significant step toward a secure, reliable and affordable energy future.

14 SOLAR ENERGY↗

Virtual Battery Aggregator (Virtual Battery Aggregator for Distributed Energy Resource Management Systems)

Distributed energy resource management systems (DERMS) are being deployed in feeders with high distributed energy resource (DER) penetration to provide visibility of DERs and enable DER control strategies for grid operators. DERMS can support centralized grid controls by aggregating individual DER information into a single virtual DER model. This codebase creates algorithms for a DERMS platform that are able to aggregate a set of DERs that can be modeled as batteries, create a virtual battery model for centralized grid controls, and dispatch power setpoints to the individual DERs based on a desired virtual power setpoint received from the centralized grid control. It integrates with existing co-simulation frameworks and models for buildings, DERs, and distribution systems. While the DERMS is designed to work with batteries, it can be used with any DER that can be defined by a generalized battery model.

Blonsky, Michael↗

Analyzing impact of $\mathrm{DER}$ on $\mathrm{FIDVR}$ - comparison of $\mathrm{EMT}$ simulation of a combined transmission and distribution grid with aggregated positive sequence models

The increase in percentage of distributed energy resources (DERs) brings in a degree of uncertainty in bulk power system planning and operations. Further, the presence of 1 - φ induction motors introduces the possibility of motor stalling and fault induced delayed voltage recovery (FIDVR). With newer versions of IEEE Std 1547™ there can be the opportunity to obtain dynamic voltage support from DERs. In this report, the impact of DERs providing dynamic voltage on the dynamic behavior of 1 - φ induction motors is examined in detail along with an exploration of the need for simulation platforms that go beyond positive sequence. The studies discussed here are carried out both in detailed electromagnetic time domain and in positive sequence domain for comparison.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Virtual Power Plant Architecture and Resilient Design

Virtual Power Plants (VPPs) represent a fundamental shift in electric grid operations, aggregating distributed energy resources (DERs) such as solar panels and battery storage to deliver utility-scale grid services traditionally provided by centralized power plants. This report examines the unique architectural, operational, and digital assurance considerations that distinguish VPPs from conventional utility infrastructure as they scale from pilot projects to mainstream deployment across the United States. While VPPs offer significant opportunities for grid modernization and enhanced flexibility, their distributed, multi-stakeholder architecture introduces distinct security challenges that differ fundamentally from traditional generation facilities. The analysis identifies risks in VPP operations, including device-level security gaps, platform vulnerabilities, and communication protocol weaknesses that create expanded attack surfaces compared to centralized power plants. Through examination of real-world incidents and emerging threat patterns, the report demonstrates how some VPPs' reliance on consumer-owned devices, public internet infrastructure, and complex vendor ecosystems require new approaches to digital assurance and operational security. The findings provide practical guidance for utilities, regulators, and aggregators to implement robust security frameworks and operational best practices essential for maintaining grid reliability as VPP deployment accelerates under the Federal Energy Regulatory Commission (FERC) Order 2222 and related regulatory initiatives.

24 - POWER TRANSMISSION AND DISTRIBUTION↗