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DOE OSTI2024

The Transactive Energy Network Template Metamodel

While transactive energy, which is defined as an allocation of electricity based on dynamically discovered values or prices, has been extensively studied, its uptake and use has been slow. This report describes a tool, the transactive network template, which should hasten the creation and uptake of transactive energy networks. Some basic principles of transactive energy are familiar from existing wholesale electricity markets. Locational prices are calculated today for zones within bulk electric transmission systems. Locational prices differ while accounting for the locational costs of electricity generation and the losses and constraints incurred when electricity is transmitted from generators and distributed to consumers. A transactive energy network might include these transmission zones. However, current research strives to apply transactive energy also in electricity distribution circuits, buildings, and even for individual generating and consuming devices. At the same time, researchers explore how to apply transactive energy in real time during increasingly shorter time intervals. Automated computational agents become necessary as transactive energy becomes applied to smaller circuit zones and at faster dynamic timescales. A transactive energy network is an example of a multi-agent system. Each zone in the network is represented by its transactive agent, which makes decisions for and acts on behalf of a business entity that is responsible for and manages one of the circuit regions. A transactive energy network is also an example of a decentralized, distributed control system. Control decisions and responsibilities are distributed among the network’s transactive agents. The transactive agents are independent; that is, there typically is no centralized authority or oversight function. Instead, transactive agents exchange transactive signals and thereby negotiate the prices and quantities of electricity that they will exchange. Initially, the circuit regions and responsibilities of transactive agents appear to be very dissimilar. Each circuit region may comprise transmission, distribution, or building-level circuits. Each has a unique position and electrical connectivity within the transactive energy network. Each possesses unique assets that either generate or consume electricity, and these (e.g., renewable energy generator, diesel generator, aggregate utility load, building load, space conditioning, refrigerator, etc.) may further differ in their price flexibility and in their strategies for responding to dynamic electricity prices. Given such diversity, an implementer’s first inclination might be to start from scratch to define all these devices and to engineer their seemingly unique interactions. Given that each implementer’s perspective may be narrow within a transactive energy network, it is unlikely that uniquely engineered systems would interact well. This is where the transactive network template is applicable. The transactive network template is a metamodel that has been developed to guide implementers as they configure their own transactive agent within a network of such agents. The object-oriented design of the transactive network template provides basic code object types that may be used and extended by implementers to represent each of the assets in their circuit region. These objects further facilitate the transactive agent’s necessary computations, which are divided among responsibilities to schedule power usage, balance electric supply and demand, and coordinate the exchange of electricity with the other transactive agents. This report addresses the conceptual transactive network template design. Implementers are directed to more formal design documents and reference implementations. A Python™-based1 reference implementation of the transactive network template has been coded, and three implementations have been configured to represent a national laboratory and two university campuses. Version 2 of the transactive node template generalizes the market class and its methods to facilitate multiple, and more diverse market coordination mechanisms than were facilitated by and demonstrated using Version 1. Version 3 includes new Appendix B, which addresses the designs of methods that would make dynamic prices track approved electricity rates. In the future, the author wishes to make the transactive network template more generally applicable to networks that require more accurate power flow. Development of the transactive network template is jointly funded by the U.S. Department of Energy (DOE) Energy Efficiency and Renewable Energy and the DOE Office of Electricity. In late 2015, one of the first projects to be funded by the DOE Grid Laboratory Modernization Laboratory Consortium was the Clean Energy and Transactive Campus project, led by Pacific Northwest National Laboratory. DOE funds were matched by an investment by the Washington Department of Commerce through its Clean Energy Fund. The transactive network template was developed to guide the implementation of transactive energy networks within this project’s scope.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Swing Contract-Based Valuation for Distributed Energy Resources in Transactive Energy Systems: A Reinforcement Learning Approach

With the proliferation of distributed energy resources (DERs) and power grids with high fractions of renewable energy, market constructs are evolving to allow DERs to participate in multiple possible markets, at different levels of grid hierarchy. The effective participation of DERs in market environments is aided by swing contract-based pricing mechanisms, whereby DERs have a two-part compensation structure – one for their reservation/commitment and another for performancedriven ex-post payment for their actual mobilization during dispatch. In this paper, we propose a reinforcement learningbased (Q-learning) approach that allows a rational DER agent to select the market it wants to participate in within a composite market environment where individual markets are coordinated by possibly different actors. The proposed Q-learning framework aids DERs in their self-valuation by implicitly maximizing their own payoff through market participation, assuming a swing contract-based compensation structure. We complement our work through simulation-based investigations where factors affecting the DER decision making process, such as parametric uncertainties in market (and grid) environments, are studied.

Naqvi, Syed Ahsan Raza↗
DOE OSTI2023

Transactive Energy Communications Interface Standards Landscape

Transactive energy represents distributed, optimal-seeking coordination approaches for managing the operation of large numbers of energy-related devices and systems. The concept assumes intelligent agents interact with other agents on behalf of their owners to balance the supply and demand of energy and coordinate other operation services in an electric system. They do this by exchanging value signals for services in near-term and forward time periods using market mechanisms. The technique is particularly applied to coordination of flexibility in operating distributed energy resources. The integration of large numbers of devices requires that they be able to connect and interoperate easily and reliably. Given the many technologies and solution providers integrating products, communications interfaces based on clear, unambiguous specifications with supporting tests require standardization and adoption by the community of system integrators. This report reviews the state of communications interface standards that show promise for transactive energy approaches to the coordination of distributed energy resources. It reviews promising standards to highlight challenges and gaps. It offers structured comparisons between standards and the features offered by their ecosystems of participants.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Transactive Energy System Deployment Over Insecure Communication Links

Here, in this paper, the privacy and security issues associated with the transactive energy system (TES) deployment over insecure communication links are addressed. In particular, it is ensured that 1) individual agents’ bidding information is kept private throughout hierarchical market-based interactions; and 2) any extraneous data injection attack can be quickly and easily detected. An implementation framework is proposed to enable the cryptography-based enhancement of privacy and security for the deployment of any general hierarchical systems including TESs. Under the proposed framework, a unified cryptography-based approach is developed to achieve both privacy and security simultaneously. Specifically, privacy preservation is realized by an enhanced Paillier encryption scheme, where a block design is proposed to significantly improve computational efficiency. Attack detection is further achieved by an enhanced Paillier digital signature scheme, where a stamp-concatenation mechanism is proposed to enable detection of data replace and reorder attacks. Simulation results verify the effectiveness of the proposed cyber-resilient design for transactive energy systems. Note to Practitioners—This paper is motivated by addressing the issues of cyber resiliency for practically deploying transactive energy system (TES) but it is also applicable to the problem of enhancing the privacy and security for any general hierarchical control systems. TES is an emerging control approach that engages energy suppliers and customers through market operations and uses the price to optimally allocate energy resources. While it has been shown to be promising for power system applications, the underlying market-based interactions raise significant concerns of privacy (data leakage) and security (data tampering). However, existing TES works only focus on the coordination mechanism instead of privacy and security issues. This paper proposes a new cryptography-based TES design for practical deployment. Specifically, to protect privacy, individual supply and demand amounts to be exchanged are all encrypted in a particular way such that the original amounts cannot be inferred from the encrypted amounts, while the desired computation for setting the market clearing price can be carried out over the encrypted amounts, thus generating an encrypted result which, when decrypted, matches that of the same computation over the original amounts. To achieve security, for each exchanged data, its sender generates a particular digital signature which is exchanged together with the data. This enables the receiver to automatically detect the integrity by checking whether a mathematical relationship holds for the pair of data and signature. In our future research, we will investigate more challenging scenarios where some suppliers and customers themselves could be corrupted and purposely submit distorted amounts.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Overview on Transactive Energy—Advantages and Challenges for Weak Power Grids

This document lists some challenges that researchers face when implementing transactive energy in weak power grids. These challenges often include high voltage fluctuations, limited generation, high line loadability, and unbalanced grids. The operation of transactive energy, as well as optimization techniques, are also considered, highlighting the performance and functionalities depending on power grid characteristics and market topology. Some of the most used optimization techniques for market clearing, considering the characteristics and topology, are presented as part of the research work. In addition, this paper compares different market topologies and highlights their advantages and challenges. Furthermore, this paper contains a brief description of the interoperability frameworks applied to a smart grid. As a result, it was determined that interoperability is necessary for the proper functioning of the grid. Moreover, all methods were found to be effective for their purpose from the user’s point of view as each technique has different characteristics relevant to the user and the grid. It was concluded that it is convenient to combine the optimization techniques to consider different constraints in the market clearing.

14 SOLAR ENERGY↗
DOE OSTI2024

Transactive Energy Practices Survey

For nearly two decades, the idea of using market-based approaches in field deployments that coordinate the flexible operation of electricity customer assets has occupied the efforts of transactive energy practitioners. While the purported benefits of this distributed decision-making approach encourage transactive energy designs have been well explored, the practical aspects of implementing such a system to address real-world problems are just beginning to emerge. This report surveyed 24 field-deployed programs and interviewed experts instrumental in these deployments. The results of the survey and interviews reveal the diversity of designs and applications. They highlight the technical promise of the approaches as well as challenges with system integration, sustainable business strategy, and regulatory policy obstacles. Insights from the survey offer considerations to direct future effort and investment.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Taming the wild edge of smart grid – Lessons from transactive energy market deployments

For two decades, the idea of using market-based approaches in field deployments that coordinate the flexible operation of electricity customer assets has occupied the efforts of transactive energy practitioners. While the purported benefits of this distributed decision-making approach have been well explored, the practical aspects of implementing such a system to address real-world problems are just beginning to emerge. This report surveyed 24 field-deployed programs and interviewed experts instrumental in these deployments. The results of the survey and interviews reveal the diversity of designs and applications. They highlight the technical promise of the approaches as well as challenges with system integration, sustainable business strategy, and regulatory policy obstacles. Insights from the survey offer considerations to direct future effort and investment.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Data-Driven Approach to Transactive Energy Systems with Commercial Buildings

A microgrid with solar, storage, and responsive load resources has been implemented and tested on an urban academic campus. Through modeling and simulation, a consensus transactive energy mechanism has been implemented, with each resource participating as a virtual battery. Most owners of large buildings don't have the information and expertise to develop and validate suitable models of their buildings using available tools. To mitigate this adoption barrier, a data-driven building model has been implemented and validated. It uses 5-minute weather data, 3-second revenue meter data, energy audit information, and a load reduction test conducted by the building owner.

Buildings, data-driven modeling, deep learning, en↗
DOE OSTI2024

Dataset for: Price Controls for Scarcity Events in Real-Time and Transactive Energy Systems

Real time pricing (RTP) is often promoted as a mechanism to improve the economic efficiency of the electricity system. However, many regulators have been hesitant to adopt RTP due to concerns about exposing customers to extreme price swings. To balance these concerns, this paper proposes a methodology for establishing price controls, based on the supply of demand-side flexibility in the system. As an illustrative example, we measure price responsiveness using an agent-based simulation model that is representative of the ERCOT market. The model is composed of a distribution feeder that has 250 customers with active agents controlling their HVAC systems in response to the historical ERCOT RTP with an artificially added high-price event. These agents are subjected to increasing electricity prices during the event, which we then use to create a supply curve for demand-side resources in our modeled scarcity event. We set potential price caps at points on the supply curve where customers’ have exhausted their flexible capacity. Using historical prices, we examine the systemic costs of these price caps, and present regulatory options for recouping them. Utilities and regulators interested in limiting consumer risk from dynamic pricing can utilize these methods to develop rate structures and encourage conservation. The attached data upload allows for the duplication or modification of the analysis performed in this study.

Kerby, Jessica R↗
DOE OSTI2023

Transactive Campus Energy Systems: An R&D Testbed for Renewalables Integration, Efficiency, and Grid Services - CRADA 356 (Abstract)

Under this Cooperative Research and Development Agreement (CRADA), the project team consisting of Pacific Northwest National Laboratory (PNNL), acting on behalf of the U.S. Department of Energy, and the University of Washington (UW) and Washington State University (WSU), acting under the purview of the State of Washington’s Department of Commerce (the “industrial” partner), will connect the PNNL, UW, and WSU campuses to form a multi-campus test bed for transaction-based energy management – transactive – solutions (see sidebar). Building on the foundational transactive system established by the Pacific Northwest Smart Grid Demonstration (PNWSGD), it is proposing to construct the test bed as both a regional flexibility resource and as a platform for R&D on buildings/grid integration and information-based energy efficiency.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

An Introduction to the Federated Architecture for Secure and Transactive Distributed Energy Management Solutions (FAST-DERMS)

Deployment and capability of distributed energy resources (DER) in power systems is growing rapidly. These resources present an opportunity for low-cost provision of energy and grid services. The Federal Energy Regulatory Commission recently provided rulings to enable market participation of these distribution-connected resources, but the prevailing strategies for their management may not scale well to meet future needs. This paper introduces the Federated Architecture for Secure and Transactive Distributed Energy Management Solutions (FAST-DERMS) which was designed to address this need. In it we describe the architectural features of the approach, and a reference controls implementation employing a hierarchical coordination that includes stochastic optimization, model predictive control, and a simple real-time management scheme. Sample results from simulation show firm transmission-level service provision measured at the distribution substation.

grid architecture↗
DOE OSTI2024

An Introduction to the Federated Architecture for Secure and Transactive Distributed Energy Management Solutions (FAST-DERMS): Preprint

Deployment and capability of distributed energy resources (DER) in power systems is growing rapidly. These resources present an opportunity for low-cost provision of energy and grid services. The Federal Energy Regulatory Commission recently provided rulings to enable market participation of these distribution-connected resources, but the prevailing strategies for their management may not scale well to meet future needs. This paper introduces the Federated Architecture for Secure and Transactive Distributed Energy Management Solutions (FASTDERMS) which was designed to address this need. In it we describe the architectural features of the approach, and a reference controls implementation employing a hierarchical coordination that includes stochastic optimization, model predictive control, and a simple real-time management scheme. Sample results from simulation show firm transmission-level service provision measured at the distribution substation.

DERMS↗
DOE OSTI2023

Multi-stage charging and discharging of electric vehicle fleets

Fleets of electric vehicles will likely shift electricity demand, and the effect of upstream charging emissions will come from generation sources that are dispatched in response. This study proposes a multi-stage charging and discharging problem to translate low-cost energy transactions into vehicle dispatch decisions. A day-ahead charging optimization problem minimizes electricity purchases and marginal emissions damages, with energy transactions becoming targets in an optimization-based dispatch strategy for an on-demand shared autonomous electric vehicle (SAEV) fleet. The framework was tested for Austin, Texas, using an agent-based simulator. Fleets can schedule charging to lower daily power costs (averaging 15.5% or $\$0.79$/day/SAEV) while reducing health damages from generation-related pollution (2.8% or $\$0.43$/day/SAEV). Finally, fleet managers can increase profits ($\$8$ per SAEV per day) by adopting a multi-stage charging and discharging strategy that can serve more passengers per day than price-agnostic dispatch strategies.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Digital Real-Time Simulation and Power Quality Analysis of a Hydrogen-Generating Nuclear-Renewable Integrated Energy System

This paper investigates the challenges and solutions associated with integrating a hydrogen-generating nuclear-renewable integrated energy system (NR-IES) under a transactive energy framework. The proposed system directs excess nuclear power to hydrogen production during periods of low grid demand while utilizing renewables to maintain grid stability. Using digital real-time simulation (DRTS) in the Typhoon HIL 404 model, the dynamic interactions between nuclear power plants, electrolyzers, and power grids are analyzed to mitigate issues such as harmonic distortion, power quality degradation, and low power factor caused by large non-linear loads. A three-phase power conversion system is modeled using the Typhoon HIL 404 model and includes a generator, a variable load, an electrolyzer, and power filters. Active harmonic filters (AHFs) and hybrid active power filters (HAPFs) are implemented to address harmonic mitigation and reactive power compensation. The results reveal that the HAPF topology effectively balances cost efficiency and performance and significantly reduces active filter current requirements compared to AHF-only systems. During maximum electrolyzer operation at 4 MW, the grid frequency dropped below 59.3 Hz without filtering; however, the implementation of power filters successfully restored the frequency to 59.9 Hz, demonstrating its effectiveness in maintaining grid stability. Future work will focus on integrating a deep reinforcement learning (DRL) framework with real-time simulation and optimizing real-time power dispatch, thus enabling a scalable, efficient NR-IES for sustainable energy markets.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Equitable Transactive Market Design to Coordinate Networked Microgrids with Mixed Ownership

This paper presents an inter-microgrid peer-topeer (P2P) transactive market mechanism to support the coordination of multiple microgrids in a mixed-ownership environment, while enabling prosumers to actively participate in the market to get their own benefits. An equitable P2P transactive energy market is designed, in which the energy burden to customers within microgrids is fairly distributed by leveraging a peer-to-peer communication network among MG owners and the distribution system operator (DSO). To reach the market settlement, a consensus-based distributed optimization algorithm is introduced to enable each MG owner and the DSO to distributedly determine the cleared price which is compensated by a household-income-based discount factor to encourage the energy-burden equity among customers in networked microgrids service territory. Numerical results on the modified 123 node test feeder including 6 microgrids are used to demonstrate the operation of the introduced equitable transactive energy market.

Vu, Thanh Long↗
DOE OSTI2024

Federated Architecture for Secure and Transactive Distributed Energy Resource Management Solutions

There are fewer conventional, dispatchable generation resources and more variable renewable energy (VRE) and distributed energy resources (DERs). There is more uncertainty from bulk-level VRE and net demand from distribution systems with high DER levels. FAST-DERMS aims to develop and demonstrate a scalable solution for managing uncertainties in supply and demand at the grid edge. We propose that distribution system operators (DSOs) provide firm net load forecasts to the bulk system operator's energy management system (EMS).

distributed energy resources↗
DOE OSTI2024

Using Co-Simulation to Model Interconnect-Scale Power Systems from Loads to Generators

Co-simulation is a modeling technique that allows analysts to combine simulation tools and their corresponding models to exchange data during run-time, allowing the creation of larger and more complex models across heterogeneous domains. HELICS is a co-simulation platform developed over the past six years that has been shown to be effective for these multi-domain analysis. Recently, a HELICS-based analysis was completed where the ERCOT electrical interconnect in the United States was modeled in high detail from bulk power system generation to individual customer loads. This model was used to evaluate a flat-rate and transactive energy tariff with integrated wholesale and retail real-time and day-ahead energy markets. This modeling allows detailed analysis showing how the operations of the power system under these tariffs impact all actors in the power system, from individual customers to bulk power system operators.

co-simulation, HELICS, transactive energy system, ↗