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Transactive Energy (TE) is an emerging discipline that utilizes economic and control techniques for operating and managing the power grid effectively. Distributed Energy Resources (DERs) represent a fundamental shift away from traditionally centrally managed energy generation and storage to one that is rather distributed. However, integrating and managing DERs into the power grid is highly challenging owing to the TE implementation issues such as privacy, equity, efficiency, reliability, and security. The TE market structures allow utilities to transact (i.e., buy and sell) power services (production, distribution, and storage) from/to DER providers integrated as part of the grid. Flexible power pricing in TE enables power services transactions to dynamically adjust power generation and storage in a way that continuously balances power supply and demand as well as minimize cost of grid operations. Therefore, it has become important to analyze various market models utilized in different TE applications for their impact on above implementation issues.In this demo, we show-case the Transactive Energy Simulation and Analysis Toolsuite (TE-SAT) with its three publicly available design studios for experimenting with TE markets. All three design studios are built using metamodeling tool called the Web-based Graphical Modeling Environment (WebGME). Using a Git-like storage and tracking backend server, WebGME enables multi-user editing on models and experiments using simply a web-browser. This directly facilitates collaboration among different TE stakeholders for developing and analyzing grid operations and market models. Additionally, these design studios provide an integrated and scalable cloud backend for running corresponding simulation experiments.
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Transactive energy and solarization: assessing the potential for demand curve management and cost savings
Utilities and local power providers throughout the world have recognized the advantages of the "smart grid" to encourage consumers to engage in greater energy efficiency. The digitalization of electricity and the consumer interface enables utilities to develop pricing arrangements that can smooth peak load. Time-varying price signals can enable devices associated with heating, air conditioning, and ventilation (HVAC) systems to communicate with market prices in order to more efficiently configure energy demand. Moreover, the shorter time intervals and greater collection of data can facilitate the integration of distributed renewable energy into the power grid. This study contributes to the understanding of time-varying pricing using a model that examines the extent to which transactive energy can reduce economic costs of an aggregated group of households with varying levels of distributed solar energy. It also considers the potential for transactive energy to smooth the demand curve.
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- Award ID(s):
- 1743772
- PAR ID:
- 10296937
- Date Published:
- Journal Name:
- DESTION ’21: Design Automation for CPS and IoT
- Page Range / eLocation ID:
- 19 to 25
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1145/3445034.3460510
