ORCID Profile
0000-0003-4228-7196
Current Organisation
UNSW Sydney
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Publisher: MDPI AG
Date: 07-01-2022
DOI: 10.3390/EN15020429
Abstract: Australia is one of the leading countries in energy transition, and its largest power system is intended to securely operate with up to 75% of variable renewable generation by 2025. High-inertia synchronous condensers, battery energy storage systems, and grid-forming converters are some of the technologies supporting this transformation while facilitating the secure operation of the grid. Synchronous condensers have enabled 2500 MW of solar and wind generation in the state of South Australia, reaching minimum operational demands of ≈100 MW. Grid-scale battery energy storage systems have demonstrated not only market benefits by cutting costs to consumers but also essential grid services during contingencies. Fast frequency response, synthetic inertia, and high fault currents are some of the grid-supporting capabilities provided by new developments that strengthen the grid while facilitating the integration of new renewable energy hubs. This manuscript provides a comprehensive overview, based on the Australian experience, of how power systems are overcoming expected challenges while continuing to integrate secure, low cost, and clean energy.
Publisher: F1000 Research Ltd
Date: 25-08-2022
DOI: 10.12688/DIGITALTWIN.17632.1
Abstract: Artificial Intelligence (AI) promises solutions to the challenges raised by the digitalization of power grids and their assets. Decision-making, forecasting and even operational optimization of grids and assets are just some of the solutions that AI algorithms can provide to operators, utilities and vendors. Nevertheless, barriers such as access to quality datasets, interpretability, repeatability, and availability of computational resources currently limit the extent of practical AI implementations. At the same time, Digital Twins (DTs) are foreseen as platforms that can overcome these barriers, and also provide a new environment for the development of enhanced and more intelligent applications. In this manuscript, we review the published literature to determine the existing capabilities and implementation challenges of AI algorithms in power systems, and classify AI-based applications based on their time scale to reveal their temporal sensitivity. By combining AI and DT, we outline multiple prospective use cases for AI-enhanced power grid and power asset DTs. Our review also identifies that the combination of AI-based solutions and DTs leverages new applications with the potential to fundamentally change multiple aspects of the power industry.
Publisher: F1000 Research Ltd
Date: 13-03-2023
DOI: 10.12688/DIGITALTWIN.17632.2
Abstract: Artificial Intelligence (AI) promises solutions to the challenges raised by the digitalization of power grids and their assets. Decision-making, forecasting and even operational optimization of grids and assets are just some of the solutions that AI algorithms can provide to operators, utilities and vendors. Nevertheless, barriers such as access to quality datasets, interpretability, repeatability, and availability of computational resources currently limit the extent of practical AI implementations. At the same time, Digital Twins (DTs) are foreseen as platforms that can overcome these barriers, and also provide a new environment for the development of enhanced and more intelligent applications. In this manuscript, we review the published literature to determine the existing capabilities and implementation challenges of AI algorithms in power systems, and classify AI-based applications based on their time scale to reveal their temporal sensitivity. Furthermore, DT-based technologies are discussed, identifying the potentials to tackle current limitations of real-world AI applications as well as exploring the synergies between DTs and AI. By combining AI and DT, we outline multiple prospective use cases for AI-enhanced power grid and power asset DTs. Our review also identifies that the combination of AI-based solutions and DTs leverages new applications with the potential to fundamentally change multiple aspects of the power industry.
Publisher: MDPI AG
Date: 19-01-2022
DOI: 10.3390/ELECTRONICS11030301
Abstract: As a variant modular converter configuration, the alternate arm converter (AAC) is well-suited for high-voltage power transmission and large-scale integration of renewables. In contrast to conventional multilevel converters, the director switches in the arms of AAC lead to the introduction of an overlap period, during which circuiting current can flow through the two arms in the same phase. Thus, fixed or variable overlap period control can be implemented in AAC systems so as to dynamically balance stored arm energy. However, the control of overlap period is linked to instability issues that might impede the safe operation of AAC systems, which are yet to be reported. In this paper, the stability of an AAC system is demonstrated based on measured grid and converter impedance, in conjunction with impedance-based stability criterion in the dq frame. The interaction between harmonic sources at AC and DC sides of the AAC system is analyzed to determine resonant frequencies in the AC current when any potential resonance is identified in the dq frame. Novel results with respect to the impact of overlap period on the system stability are obtained by depicting and comparing the Eigenloci in the polar plot, which are validated by real-time simulations.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2022
No related grants have been discovered for Zhiwei Shen.