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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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Communication System Modeling in Transactive Systems

Transactive energy systems almost always rely on communication systems for proper operation but most analysis of transactive systems do not model the communication system. Often these analysis are performed by those without a communication system modeling or simulation background and the difficulty of implementing such models in the analysis environment is prohibitive. Without this model, an understanding of the communication system requirements to successfully implement a transactive energy system can not be comprehended. This report details a capability of auto-generating communication system models from an electrical distribution system model, discusses the need for such models, discusses the method by which these models were developed in this project, and demonstrates the impact on the performance of a load management system when using such models. This capability has been incorporated into Pacific Northwest National Laboratory’s (PNNL) Transactive Energy Simulation Platform (TESP).

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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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DSO+T: Integrated System Simulation (DSO+T Study: Volume 2)

This report summarizes an integrated co-simulation model used by the Distribution System Operator with Transactive (DSO+T) study to represent an electrical generation, delivery, and end-load systems for the purposes of assessing the viability and value proposition of transactive energy coordination of flexible assets versus a business-as-usual case. The integrated co-simulation model includes the bulk generation and transmission system, including the day-ahead and real-time scheduling and dispatch of thermal generators. Forty distribution system operators were modelled in detail, including tens of thousands of residential and commercial buildings and their flexible end-loads. These included HVAC systems, residential water heaters, electric vehicles, and stationary, behind-the-meter, batteries. Both wholesale market and end-load results for the business-as-usual case are presented and compared to actual ERCOT system data to assess the accuracy and representativeness of the resulting model.

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