FRESNO Project
Available Opportunities:
None at the moment.
Project Description
The “Flexible Aggregator Simulation Platform (FRESNO)” is a research project aiming to create a platform to simulate, test and verify advanced smart grid operation mechanisms at the distribution level. It is a revolutionary platform that facilitates studying larger amounts of renewable integration into the grid to provide a secure environment for larger adoption of electric vehicles by avoiding excessive capital cost of grid upgrade. Developing such a platform can be particularly beneficial for SA with the highest behind-the-meter PV and storage penetration per capita in the world. This is also aligned with the SA government plan to create the largest virtual power plant (VPP) in the world, consisting of 50000 prosumers. The project is funded by the University of Adelaide RTP and Watts, Denmark.
The project has started early 2021. Three PhD student projects are defined as a part of the University of Adelaide Industry-PhD. The PhD students in this project received $10K p.a. top-up scholarship and $5K p.a. research allowance from the industry partner. The base scholarship is provided by the University of Adelaide. Also, the students will complete a mandatory six months industry placement with the partner, who also offers a two-way ticket to Denmark from Adelaide plus an extra $9K scholarship for the placement duration. Each student in this project is supervised by three academic and two industry supervisors.
Research Keywords
- Flexibility aggregation
- Flexibility simulation platform
- Aggregator business models
- Aggregator & future local markets
- Aggregator & community storage
- Behind-the-meter flexibility model
PhD Students
Academic Supervisory Team
Project News
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Mar 2024
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Mar 2024
Congratulations, Ray! His article Smart meters haven’t delivered the promised benefits to electricity users. Here’s a way to fix the problems is published in The Conversation.
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Feb 2024
Congratulations, Ray! His paper Unleashing the benefits of smart grids by overcoming the challenges associated with low-resolution data is published in the Cell Reports Physical Science journal.
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Oct 2023
Congratulations, Nam! His paper Cost-effective community battery sizing and operation within a local market framework accepted for publication in the IEEE Transactions on Energy Markets, Policy and Regulation.
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May 2023
Congratulations, Ray! His paper A synthetic dataset of Danish residential electricity prosumers accepted for publication in the Scientific Data journal by Nature group.
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Oct 2022
Congratulations, Ray! His paper IRMAC: Interpretable refined motifs in binary classification for smart grid applications accepted for publication in the Engineering Applications of Artificial Intelligence journal.
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July 2022
Congratulations, Yogi! His paper Optimal offering strategy for an aggregator across multiple products of European day-ahead market accepted for presentation in the IEEE ISGT Europe 2022.
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May 2022
Congratulations, Nam! His paper Optimal sizing and scheduling of community battery storage within a local market accepted for the ACM e-Energy 2022.
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May 2022
Congratulations, Yogi! His major review was approved on 6 May.
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Mar 2022
Congratulations, Nam! His major review was approved on 22 March.
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Mar 2022
Congratulations, Ray! His major review was approved on 22 March.
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Dec 2021
FRESNO team places fifth in Renewable Energy Scheduling Competition organised by IEEE-CIS among 49 teams/participants.
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May 2021
Welcome to the team, Yogesh. Yogesh will work on FRESNO A project to develop decision-making tools for aggregators operation in the market in this PhD.
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Mar 2021
Welcome to the team, Nam. Nam will work on FRESNO C project to develop game-theoritic models of prosumers in this PhD.
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Dec 2020
Welcome to the team, Rui (Ray). He will develop probabilistic models for consumers reaction to time-varying prices in this PhD.
Project Publications
[6] Rui Yuan, S. Ali Pourmousavi, Wen L. Soong, Andrew J. Black, Jon A.R. Liisberg, Julian Lemos-Vinasco, Unleashing the benefits of smart grids by overcoming the challenges associated with low-resolution data, Cell Reports Physical Science, 5(2), 101830, Feb. 21, 2024. Link: https://alipourmousavi.com/docs/JPaper2-2024.pdf
[5] Nam Trong Dinh, Sahand Karimi-Arpanahi, S. Ali Pourmousavi, Mingyu Guo, and Jon A. R. Liisberg, Cost-effective community battery sizing and operation within a local market framework, IEEE Transactions on Energy Markets, Policy and Regulation, Oct 2023. Link: https://alipourmousavi.com/docs/JPaper5-2023.pdf
[4] Rui Yuan, S. Ali Pourmousavi, Wen L. Soong, Andrew J. Black, Jon A. R. Liisberg, and Julian Lemos-Vinasco, A synthetic dataset of Danish residential electricity prosumers, Scientific Data, May 2023. Link: https://alipourmousavi.com/docs/JPaper4-2023.pdf
[3] Rui Yuan, S. Ali Pourmousavi, Wen L. Soong, Giang Nguyen, Jon A. R. Liisberg, IRMAC: Interpretable refined motifs in binary classification for smart grid applications, Engineering Applications of Artificial Intelligence, 117:105588, Part A, January 2023. Link: https://alipourmousavi.com/docs/JPaper4_2022.pdf
[2] Yogesh Pipada Sunil Kumar, S. Ali Pourmousavi, Markus Wagner, J. Liisberg, Optimal offering strategy for an aggregator across multiple products of European day-ahead market, IEEE ISGT Europe conference, July 2022. Link: https://alipourmousavi.com/docs/JPaper1-2022.pdf
[1] N. Dinh, S. Ali Pourmousavi, S. Karimi-Arpanahi, Y. Kumar, M. Guo, D. Abbott, J. Liisberg, Optimal sizing and scheduling of community battery storage within a local market, Accepted for presentation in the ACM e-Energy conference, May 2022. Link: https://alipourmousavi.com/docs/JPaper1-2022.pdf
Project Software and Codes
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Oct 2023Community battery sizing study considering receding horizon operation
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June 2023A synthetic dataset of Danish residential electricity prosumers