Projects per year
Abstract
Power system operation faces an increasing level of uncertainties from renewable generation and demand, which may cause large-scale congestion under an ineffective operation. This article applies energy storage (ES) to reduce system peak and the congestion by the robust optimization, considering the uncertainties from the ES state-of-charge (SoC), flexible load, and renewable energy. First, a deterministic operation model for the ES, as a benchmark, is designed to reduce the variance of the branch power flow based on the least-squares concept. Then, a robust model is built to optimize the ES operation with the uncertainties in the severest case from the load, renewable energy, and ES SoC that are converted into branch flow budgeted uncertainty sets by the cumulant and Gram–Charlier expansion methods. The ES SoC uncertainty is modeled as an interval uncertainty set in the robust model, solved by the duality theory. These models are demonstrated on a grid supply point to illustrate the effectiveness of a congestion management technique. Results illustrate that the proposed ES operation significantly improves system performance in reducing the system congestion. This robust optimization-based ES operation can further increase system flexibility to facilitate more renewable energy and flexible demand without triggering the large-scale network investment.
Original language | English |
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Article number | 8805255 |
Pages (from-to) | 2694-2702 |
Number of pages | 9 |
Journal | IEEE Systems Journal |
Volume | 14 |
Issue number | 2 |
Early online date | 19 Aug 2019 |
DOIs | |
Publication status | Published - 1 Jun 2020 |
Keywords
- Energy storage (ES)
- load uncertainty
- robust optimization
- system congestion
ASJC Scopus subject areas
- Control and Systems Engineering
- Information Systems
- Computer Science Applications
- Computer Networks and Communications
- Electrical and Electronic Engineering
Fingerprint
Dive into the research topics of 'Robust Optimization-Based Energy Storage Operation for System Congestion Management'. Together they form a unique fingerprint.Projects
- 2 Finished
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Peer-to-Peer Energy Trading and Sharing - 3M (Multi-times, Multi-scales, Multi-qualities)
Li, F. (PI), Jeon, J. (CoI) & Li, R. (CoI)
Engineering and Physical Sciences Research Council
1/09/16 → 29/02/20
Project: Research council
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Fellowship - Multi-Vector Energy Distribution System Modelling and Optimisation with Integrated Demand Side Response
Gu, C. (PI)
Engineering and Physical Sciences Research Council
1/09/14 → 31/08/17
Project: Research council
Profiles
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Chenghong Gu
- Department of Electronic & Electrical Engineering - Reader
- Centre for Sustainable Energy Systems (SES)
- Centre for Climate Adaptation & Environment Research (CAER)
- Centre for Regenerative Design & Engineering for a Net Positive World (RENEW)
- IAAPS: Propulsion and Mobility
Person: Research & Teaching, Core staff, Affiliate staff
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Furong Li
- Department of Electronic & Electrical Engineering - Professor
- Centre for Doctoral Training in Decarbonisation of the Built Environment (dCarb)
- Centre for Sustainable Energy Systems (SES)
- IAAPS: Propulsion and Mobility
Person: Research & Teaching, Core staff, Affiliate staff