Amidst the challenges posed by the high penetration of distributed energy resources (DERs), particularly a number of distributed photovoltaic plants (DPVs), in modern electric power distribution systems (MEPDS), the integration of new technologies and frameworks become crucial for addressing operation, management, and planning challenges. Situational awareness (SA) and situational intelligence (SI) over multi-time scales is essential for enhanced and reliable PV power generation in MEPDS. In this paper, data-driven digital twins (DTs) are developed using AI paradigms to develop actual and/or virtual models of DPVs, These DTs are then applied for estimating and forecasting the power outputs of physical and virtual PV plants. Virtual weather stations are used to estimate solar irradiance and temperature at user-selected locations in a localized region, using inferences from physical weather stations. Three case studies are examined based on data availability: physical PV plant, hybrid PV plants, and virtual PV plants, generating realtime estimations and short-term forecasts of PV power production that can support distribution system studies and decision-making.
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Transient Stability and Active Protection of Power Systems with Grid-Forming PV Power Plants
Photovoltaic (PV) power plants with grid-forming technology must withstand severe disturbances and remain operational. To address this challenge, this paper sets forth a grid-forming strategy for PV solar power plants so that they can ride through power system faults. This capability is accomplished by leveraging two-axis proportional-integral regulators with anti-windup functionality. This paper also demonstrates that fluctuations of solar irradiance can cause significant dc-link voltage variations and loss of synchronism of grid-forming PV plants. Hence, we develop an active dc-link protection method which depends on estimation in solar irradiance. The contributions of this paper are demonstrated via positive-sequence simulations of modified versions of the WSCC 9- and IEEE 39-bus grids.
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- Award ID(s):
- 2013739
- PAR ID:
- 10329800
- Date Published:
- Journal Name:
- IEEE Transactions on Power Systems
- ISSN:
- 0885-8950
- Page Range / eLocation ID:
- 1 to 1
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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