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At least 37 records · Page 2

Predicting U.S. federal fleet electric vehicle charging patterns using internal combustion engine vehicle fueling transaction statistics

Utilizing fueling transactions from internal combustion engine vehicles (ICEVs), the authors estimated how frequently midday public charging would be required for U.S. federal fleet battery electric vehicles (BEVs). Fueling transaction summary statistics are more widely available than trip-level telematics data, making this methodology more accessible and transferable to other researchers and fleet managers considering BEV replacements. For example, readers can easily apply a linear model using only the count of back-to-back fueling events at gas stations over 57 straight-line miles apart to predict days exceeding range. This linear regression predicted binned days exceeding 250 miles at 80% accuracy on a hold-out test set from the same fleet as the training data and 66 % accuracy on a new fleet displaying different driving behaviors. The authors additionally provide linear equations for days exceeding 200 and 300 miles as alternative range estimates to account for differences in BEV range and temperature impacts. Beyond the single-feature linear models which readers can apply, the authors tuned and trained other machine learning models on a variety of fueling transaction statistics including consecutive transaction distances, transaction distance from garage, estimated miles traveled from fuel economy and fuel quantity, and transaction periodicity. Utilizing a subset of 1678 light-duty federal fleet vehicles which contained daily vehicle miles traveled (VMT) in addition to fueling statistics, the authors determined which fueling transaction statistics were most relevant in predicting driving days exceeding 250 miles (an approximation of BEV rated driving range). In support of the U.S. federal fleet transition to zero-emission vehicles (ZEVs), the authors used these statistics and machine learning models to predict the frequency of BEV midday charging. After training models on the subset with VMT, the authors predicted days exceeding rated range for 112,902 light-duty vehicles operating in similar circumstances in the federal fleet using a Support Vector Regressor (SVR). In conclusion, they then used the projections as part of the ZEV Planning and Charging (ZPAC) tool to identify optimal candidates for BEVs for the federal fleet. An anonymized version of ZPAC is included in the supplementary materials.

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The Distribution System Operator with Transactive (DSO+T) Study

The Distribution System Operator with Transactive (DSO+T) study investigates the engineering and economic performance of a transactive energy retail market coordinating a high penetration of customer-side flexible energy assets. The study seeks to answer whether such an implementation is cost effective for customers, recovers sufficient revenue for DSOs, and is equally applicable and beneficial to a range of flexible asset types, renewable generation scenarios, and market assumptions. Using a highly interdisciplinary co-simulation and valuation framework, this assessment encompasses the entire electrical delivery system from bulk system generation and transmission, through the distribution system, to the modeling of individual customer buildings and flexible assets (including heating, ventilation, and air conditioning [HVAC] units, water heaters, batteries, and electric vehicles). The study exercises a transactive energy retail market coordination scheme designed to integrate with an existing day-ahead and real-time competitive wholesale electricity market. Software decision-making agents are designed for the retail market operator as well as various price-responsive flexible assets. The engineering and economic performance of the transactive energy scheme is studied for two separate flexible asset deployments: flexible loads (HVAC units and residential water heaters) and behind-the-meter batteries. The results of each transactive case are compared to a business-as-usual case. These cases are subject to two different renewable generation scenarios, a moderate renewable generation scenario, representative of current levels of renewable generation deployment, and a future high renewables scenario, including the increased deployment of rooftop solar photovoltaic and electric vehicles. The transactive coordination scheme is shown to produce effective and stable control and decrease peak loads 9–15%. The resulting annual demand flexibility provides net economic savings of $3.3–5.0B per year for a region the size of Texas. Detailed analysis shows that net benefits were seen for a range of distribution system operator, customer, and flexible asset types. Both participating customer (with transactive flexible assets) and nonparticipating customers (with nonflexible assets) see reductions in annual utility bills and net annual energy expenses in the range of 10–16%.

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Distribution System Operator with Transactive (DSO+T) Study: Volume 1 (Main Report)

The Distribution System Operator with Transactive (DSO+T) study investigates the engineering and economic performance of a transactive energy retail market coordinating a high penetration of customer-side flexible energy assets. The study seeks to answer whether such an implementation is cost effective for customers, recovers sufficient revenue for DSOs, and is equally applicable and beneficial to a range of flexible asset types, renewable generation scenarios, and market assumptions. Using a highly interdisciplinary co-simulation and valuation framework, this assessment encompasses the entire electrical delivery system from bulk system generation and transmission, through the distribution system, to the modeling of individual customer buildings and flexible assets (including heating, ventilation, and air conditioning [HVAC] units, water heaters, batteries, and electric vehicles). The study exercises a transactive energy retail market coordination scheme designed to integrate with an existing day-ahead and real-time competitive wholesale electricity market. Software decision-making agents are designed for the retail market operator as well as various price-responsive flexible assets. The engineering and economic performance of the transactive energy scheme is studied for two separate flexible asset deployments: flexible loads (HVAC units and residential water heaters) and behind-the-meter batteries. The results of each transactive case are compared to a business-as-usual case. These cases are subject to two different renewable generation scenarios, a moderate renewable generation scenario, representative of current levels of renewable generation deployment, and a future high renewables scenario, including the increased deployment of rooftop solar photovoltaic and electric vehicles. The transactive coordination scheme is shown to produce effective and stable control and decrease peak loads 9–15%. The resulting annual demand flexibility provides net economic savings of $3.3–5.0B per year for a region the size of Texas. Detailed analysis shows that net benefits were seen for a range of distribution system operator, customer, and flexible asset types. Both participating customer (with transactive flexible assets) and nonparticipating customers (with nonflexible assets) see reductions in annual utility bills and net annual energy expenses in the range of 10–16%.

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Twin-page storage management for rapid transaction-undo recovery

This paper presents and evaluates a new twin-page disk-storage management scheme for rapid database transaction-undo recovery. In contrast to previous twin-page schemes, the present approach uses static page mapping and allows dirty pages in the main memory to be written, at any instant, onto disk without the requirement of undo logging. No explicit undo is required when a transaction is aborted. Transaction undo is implicitly performed by not subsequently fetching from disk the invalid pages updated by the aborted transaction. Performance in terms of disk I/O and CPU overhead for transaction-undo recovery is analyzed and compared with a previous approach TWIST. It is shown that the scheme achieves rapid transaction-undo recovery without degrading average system performance for various workloads, and that the scheme is well suited for applications with a large number of updates and frequent transaction aborts.

Wu, Kun-Lung↗

Reduced Order Model of Transactive Bidding Loads

Transactive energy (TE) has been identified to provide better grid efficiency and reliability by market-based transactive exchanges between energy producers and energy consumers. Simulations of TE systems are crucial to evaluate the benefits and impacts of different transactive mechanisms. However, such simulations can be time consuming due to the information exchange between various participants and complex co-simulation environments. In this paper, we develop a reduced order model to speed up the simulation of transactive systems in TE simulation platform (TESP) while achieving very low error between the reduced order and full model results. Specifically, the developed reduced order model consists of an aggregate responsive load agent which utilizes two Recurrent Neural Networks (RNNs) with Long Short-Term Memory units (LSTMs) to enable transactive elements to collectively participate in the TE system. The proposed aggregate responsive load (ARL) agent is able to produce similar transactive behaviors to the full simulation model while achieving significant simulation time reduction. Finally, we also show that the developed model enables generalization of simulation results across different dates and across different number of loads included in the simulations.

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Security Constrained Distributed Transaction Model for Multiple Prosumers

Massive access of renewable energy has prompted demand-side distributed resources to participate in regulation and improve flexibility of power systems. With large-scale access of massive, decentralized, and diverse distributed resources, demand-side market members have transformed from traditional “consumers” to “prosumers”. To explore the distributed transaction model of prosumers, in this paper, a multi-prosumer distributed transaction model is proposed, and the Conditional Value-at-Risk (CVaR) theory is applied to quantify potential risks caused by the stochastic characteristics inherited from renewable energy. First, a prosumer model under constraints of the distribution network including photovoltaic units, fuel cells, energy storage system, central air conditioning and flexible loads is established, and a multi-prosumer distributed transaction strategy is proposed to achieve power sharing among multiple prosumers. Second, a prosumer transaction model based on CVaR is constructed to measure risks inherited from the uncertainty of PV output within the prosumer and ensure safety of system operation in extreme PV output scenarios. Then, the alternating direction multiplier method (ADMM) is utilized to solve the constructed model efficiently. Finally, distributed transaction costs of prosumers are distributed fairly based on the generalized Nash equilibrium to maximize social benefits. Simulation results show the multi-prosumer distributed transaction mechanism established under the proposed generalized Nash equilibrium method can encourage power sharing among prosumers, increasing their own income and social benefits. Also, the CVaR can assist decision making of prosumers in weighting the risks and benefits, improving system resilience through energy management of prosumers.

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Transactive Campus Energy Systems: Final Report

Transactive energy refers to the combination of economic and control techniques to improve grid reliability and efficiency. The fundamental purpose of transactive energy management is to seamlessly coordinate the operation of large numbers of new intelligent assets—such as distributed solar, energy storage and responsive building loads—to provide the flexibility needed to operate the power grid reliably and at minimum cost, particularly one filled with intermittent renewable generation such as the Pacific Northwest. It addresses the key challenge of providing smooth, stable, and predictable “control” of these assets, despite the fact that most are neither owned nor directly controlled by the power grid. The Clean Energy and Transactive Campus (CETC) work described in this report was done as part of a Cooperative Research and Development Agreement (CRADA) between the U.S. Department of Energy’s Pacific Northwest National Laboratory (PNNL) and the Washington State Department of Commerce (Commerce) through the Clean Energy Fund (CEF). The project team consisted of PNNL, the University of Washington (UW) and Washington State University (WSU), to connect the PNNL, UW, and WSU campuses to form a multi-campus testbed for transaction-based energy management—transactive—solutions. Building on the foundational transactive system established by the Pacific Northwest Smart Grid Demonstration (PNWSGD), the purpose of the project was to construct the testbed as both a regional flexibility resource and as a platform for research and development (R&D) on buildings/grid integration and information-based energy efficiency. This report provides a summary of the various tasks performed under the CRADA.

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Transactive Campus Energy Systems (Final Report)

Transactive energy refers to the combination of economic and control techniques to improve grid reliability and efficiency. The fundamental purpose of transactive energy management is to seamlessly coordinate the operation of large numbers of new intelligent assets—such as distributed solar, energy storage and responsive building loads—to provide the flexibility needed to operate the power grid reliably and at minimum cost, particularly one filled with intermittent renewable generation such as the Pacific Northwest. It addresses the key challenge of providing smooth, stable, and predictable “control” of these assets, despite the fact that most are neither owned nor directly controlled by the power grid. The Clean Energy and Transactive Campus (CETC) work described in this report was done as part of a Cooperative Research and Development Agreement (CRADA) between the U.S. Department of Energy’s Pacific Northwest National Laboratory (PNNL) and the Washington State Department of Commerce (Commerce) through the Clean Energy Fund (CEF). The project team consisted of PNNL, the University of Washington (UW) and Washington State University (WSU), to connect the PNNL, UW, and WSU campuses to form a multi-campus testbed for transaction-based energy management—transactive—solutions. Building on the foundational transactive system established by the Pacific Northwest Smart Grid Demonstration (PNWSGD), the purpose of the project was to construct the testbed as both a regional flexibility resource and as a platform for research and development (R&D) on buildings/grid integration and information-based energy efficiency. This report provides a summary of the various tasks performed under the CRADA.

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Blockchain Smart Contracts for Transactive Energy Systems

This report demonstrates the impact of blockchain technology underlying a transactive energy system and articulates details and principle components of each of five stages in a transactive energy system. This report depicts the engineering requirements of a sample market system, blockchain features, and the relationship between those requirements and features (Section 2.2). Clear value propositions of blockchain features for transactive energy systems are: identity management, security of data, resiliency, decentralization and smart contract trustworthiness, performance, integrity in a trustless environment and access control. Due to the immutability afforded by blockchain architecture, increased data fidelity could potentially help detect targeted cyber-attacks and increase resiliency of grid integration. A distributed system can be more fault tolerant and enable transactive energy by supporting machine-to-machine transactions that can be integrated directly into complex grid operations without the need of trust in a third party. Energy auctions, and potentially registration processes, can be carried out according to transparent rules implemented as smart contracts (Section 4.0). In this current experiment, we ran a use-case/table-top exercise that imitated a real-time 5-min double auction market. The objective of this demonstration is to investigate the applicability of blockchain with transactive energy systems (Section 3.0).

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The Deontic Transaction Model in Multi-Agent Normative Systems

In the area of multi-agent systems, much research is devoted to the coordination of the agents. There exist several issues, two of which are summarized. The first is that, although agents are said to be autonomous, they always react in a predictable way to each message, and they cannot decide to violate the conventions that are hard-wired into the protocol. In fact, there might be circumstances in which the agent violates a convention in order to realize a private goal that it considers to be more important. Another issue is that, if the protocols that agents use to react to the environment are fixed, they have no way to respond to changes. However, an important characteristic of agents is that they eon react to a changing environment. Although transaction models ([BOH92], [GR93]) evolved from the database domain, they establish a general execution paradigm that ideally covers all the subsystems invoked in a sequence of transactions. So transaction models apply to multi-agent systems. Recently, some research has been devoted to overcoming the limitations of the traditional transaction models which are suitable for conventional systems and focus on system integrity, e,g., [SJ97]. Here we solve above issues by turning to a deontic concept: obligation. In multi-agent systems, agents interact with each other according to norms, We use deontic logic ([And58], [Aqv84], [B C96], [JS94], [MW93]) to model norms. Here the norms prescribe how the agents ought to behave, but-- and this is essential-- they do not exclude the possibility of "bad" behavior (i.e., the actual behavior may deviate from the ideal), and so they also prescribe what should be done in circumstances of norm violation. Thus, we propose a new approach --- a deontic transaction model for multi-agent normative systems. Our approach improves the protocol of "abort/commit" of traditional transaction models to a protocol of "abort/exception/commit". In multi-agent normative systems, we can see the violation of a norm as an exception and how the other agents react to the violation as exception handling. This paper concentrates on our formal model.

Huang, Yonghua↗

Tracking transactions using extended memory features

An approach is disclosed that tracks memory transactions by a node. The approach establishes a transaction processing state corresponding to common virtual addresses accessed by a processing threads. Transactions are executed by the threads. A selected transaction is allowed to complete. In response to detecting a conflict in the transaction processing state, completion of a non-selected transaction is inhibited.

Kahle, James Allan↗

Transactive Systems Simulation and Valuation Platform Trial Analysis

Transactive energy systems use principles of value to coordinate responsive supply and demand in energy systems. Work continues within the Transactive Systems Program, which is funded by the U.S. Department of Energy at Pacific Northwest National Laboratory, to understand the value of, understand the theory behind, and simulate the behaviors of transactive energy systems. This report summarizes recent advances made by this program. The main capability advances include a more comprehensive valuation model, including recommended documentation that should make valuation studies of all sorts more transparent, definition of economic metrics with which transactive mechanisms can be evaluated, and multiple improvements to the time-simulation environment that is being used to evaluate transactive scenarios.

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Transactive Systems Simulation and Valuation Platform Trial Analysis

Transactive energy systems use principles of value to coordinate responsive supply and demand in energy systems. Work continues within the Transactive Systems Program, which is funded by the U.S. Department of Energy at Pacific Northwest National Laboratory, to understand the value of, understand the theory behind, and simulate the behaviors of transactive energy systems. This report summarizes recent advances made by this program. The main capability advances include a more comprehensive valuation model, including recommended documentation that should make valuation studies of all sorts more transparent, definition of economic metrics with which transactive mechanisms can be evaluated, and multiple improvements to the time-simulation environment that is being used to evaluate transactive scenarios.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Extending the Blockchain: Ensuring Transactional Integrity in Relational Data via Blockchain Technology

The idea of combining a relational database with concepts associated with blockchain technology is being examined. The use case outlined herein concurrently utilizes relational and blockchain data structures to facilitate the sharing of complex data among untrusted users without the participation of a trusted third party. By capturing the transactions that result in data being stored in a relational database and placing those transactions in a blockchain structure, users can be assured that the information has not been created, altered, or destroyed without the knowledge of all users of the data. Capturing relational database transactions via a blockchain structure presents several challenges. Among them are increased storage capacity requirements, transaction ordering prior to placement on the blockchain within a multiuser database, use of existing or creation of new consensus mechanisms, and timely data verification. Addressing these challenges, although not unsurmountable, will introduce trade-offs (e.g., increased system sizing, slower transaction execution) that might or might not be acceptable based upon the envisioned use. If these trade-offs are acceptable, then this concept of extending the blockchain is a powerful method to provide both applications and their users immutable, trusted, well-defined, and consistent data.

Ray, Brian↗

DSO+T: Transactive Energy Coordination Framework (DSO+T Study: Volume 3)

This report describes a transactive energy coordination scheme designed to integrate into existing day-ahead and real-time wholesale energy markets. This scheme was evaluated in the Distribution System Operator with Transactive (DSO+T) study to assess the engineering and economic performance of the transactive energy coordination of a large-scale deployment of distributed energy resources (DER). Transactive agents were developed for a range of DERs (heating, ventilation, and air conditioning units, water heaters, batteries, and electric vehicles) that optimize flexibility over a 48-hour horizon and adjust their strategy in response to changes in real-time prices. A transactive energy coordination scheme, executed by a DSO retail market operator, aggregates these DER bids from participating customers and clears them against a DSO supply curve using a double auction market mechanism. The process of constructing the price-quantity DSO supply curve includes distribution-level transportation constraints (for example, substation congestion limits) and forecast locational marginal price of the DSO’s connected transmission node. The resulting day-ahead and real-time quantities are then bid into a competitive wholesale market operated by an independent system operator. This report also details additional capabilities for proper marketplace simulation such as wholesale price, weather, and load forecasting. The report concludes with a discussion of lessons learned and key design features required to ensure successful operation.

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Sustainable Transactions - The Fine Art of the Forever Deal - 19569

The U.S. Department of Energy Office of Legacy Management (LM) has various real property interests at the 92 sites within its current portfolio. Because of its unique mission, LM does not own most of the sites for which it has responsibility for long-term surveillance and maintenance (LTS and M). In addition to the sites it does own, LM works with various federal, state, local, and private entities to execute its obligations. Each site has its own narrative with respect to the real property assets: how they were acquired, how they are sustained, and how they were or will be dispositioned. Since the regulatory time frame for LTS and M activities at some sites can be in perpetuity, durable and effective instruments and documentation are necessary to support LM's mission as a federal land manager and steward. In addition, more than half of the sites currently in LM's inventory do not allow unrestricted use because of residual contamination from historical activities, and institutional controls are required to limit human and environmental exposures to residual contamination by controlling land use, restricting access to potential hazards, and making the public aware of potential dangers from the residual contamination. Thus, the overall real property interests and transactions associated with these sites not only have to address the environmental concerns associated with protection of human health and the environment but also how best to position LM's real property assets to support the mission for future generations. These types of transactions are often complex, requiring the negotiation of numerous documents to achieve and sustain protection of human health and the environment while allowing for future use. Such planning needs to be flexible enough to envision that the original transaction will likely change over time due to changing regulations, communities, stakeholders, and site conditions as operation and maintenance activities are performed. Planning for the integration of these requirements with the needs of the end users, stakeholders, and communities is paramount to a successful project, and various transactional considerations impact how best to achieve this goal. As such, these transactions have to be sustainable. Real property interests change over time, with new owners, operators, regulators, and stakeholders. Determining the sustainability of these real property interests, therefore, calculates the sustainability of each asset's physical attributes and also the sustainability of the various legal instruments and arrangements that are put in place at each site. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Diagramming Transactive Building Business Cases: Using Principles of e3 Value to Document Valuation Studies

Energy management in buildings is becoming more transactive. Pacific Northwest National Laboratory and the U.S. Department of Energy Building Technologies Office recently defined innovative use cases wherein market-like mechanisms are used to manage energy within buildings, between buildings, and between buildings and third-party entities, such as power utilities. A next step toward defining a set of transactive use cases in the buildings domain is to carefully diagram the corresponding business cases to capture details of transactions among all stakeholders and their economic value propositions. The principles of e3-value diagramming are applied in this report toward creating business value diagrams. These principles are extended to be consistent with Universal Modeling Language use-case diagrams. Example diagrams are presented for a subset of buildings-domain use cases that were introduced in an earlier Pacific Northwest National Laboratory report. The diagrams are intended to clearly represent an understanding of the transactions through which individual entities accumulate value in their respective use cases, and the diagrams should therefore support economic valuation studies. The report reviews some of the foundational principles of e3 value and includes authors’ insights concerning the formulation of these diagrams using Universal Modeling Language as a more systematic modeling approach.

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Applying the Transactive Systems Business Value Model to IRP

As part of the Transactive Systems Program at Pacific Northwest National Laboratory, a value modeling system was developed to support the evaluation of transactive systems. The technique is general enough to be applied outside transactive systems and to demonstrate this capability, a project was undertaken to use this value modeling technique as a means for modeling the valuation process undertaken by vertically integrated utilities when undergoing integrated resource planning (IRP). IRP is the process by which vertically integrated utilities (those that both serve customers directly as well as manage and run generation assets to do so) regularly go through to demonstrate to their regulators that they have a plan to meet the expected future load of their customers in a least cost and compliant manner. Traditionally this has been primarily an issue of how many and of which types of power plants to build but increasingly has included alternative measures such as demand response programs. Increasingly, environmental regulations play a significant role in both determine what types of power plants can be built under current regulations as well as what retrofits or upgrades need to be made to existing plants to allow them to continue to operate. Two use-case diagrams were constructed, one showing the showing the process by which IRP is carried out and another showing how a vertically integrated utility procures the resources it requires to meet load now and in the future. These diagrams help clarify the difference and provide a high-level outline of the two processes. A class diagram was constructed to clearly define the types of actors that would be considered in this model and the relationships between them. This diagram tacitly indicates which types of actors are and are not included in the model which provides significant guidance in defining the scope of the model. The relationship between the classes/actors provides further indication of what areas of the model have higher levels of detail and by implication bear more significance in modeling the system. Using the classes/actors defined in the class diagram, a business value diagram was constructed that defines the key value streams exchanged between the actors. This diagram provides a clear expression of the business case of the vertically integrated utility and who its counterparties are during the process of meeting load. These value streams have not only to do with meeting the load but doing so in a manner that meets environmental regulations. Increasingly, IRPs have three key metrics to evaluate a given plant to meet load: net present value of revenue required, emissions, and renewable energy credits. From this business value diagram, more detailed activity diagrams were formed that focus on a few of the key value stream exchanges, showing the process by which each party accrues value. These diagrams provide insight into the timing and sequence of the interactions in a way that the business value diagrams did not. The transactive value model was found to be highly compatible with IRP and provided a clear, simple model of the analysis done during IRP and key metrics driving IRP decisions. In particular it highlighted a few key items that may or may not have been as clear prior to the development of the model. Specifically, the role of the environmental regulations has become increasingly important and two of the three key metrics by which IRPs are typically evaluated are environmentally focused. Additionally, though generally not acknowledged, the role of the investor was included in this model as they are an essential source of capital in building new power plants and cannot be ignored when defining the business case of the vertically integrated utility.

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