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Regular Paper | Open Access

Bi-level Optimal Allocation of Virtual Power Plants Under Grid Strength via Integrated Short-circuit Ratio

Dashuang Li, Qiuye Sun( ), Jie Hu
College of Information Science and Engineering, Northeastern University, Shenyang 110819, China
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Abstract

The integration of a virtual power plant (VPP) into a weak grid may cause system unreliability and instability. Different allocations of renewable energy sources (RERs) and flexible power-adjustable devices (FPADs) in VPP have different impacts on system strength. Short circuit ratio (SCR) is an important index used to assess the grid strength. First, this paper proposes an integrated short circuit ratio (ISCR) index based on the network structure characteristics of the VPP grid-connected system (VPPGCS). The ISCR considers the interactions among FPADs in addition to the interactions of the RESs in VPP to assess system strength accurately. Then, a bi-level optimal allocation method for RESs and FPADs is proposed based on the proposed ISCR to enhance system strength and increase the output capacity of VPP. In the upper level, the location and capacity of RESs are optimized. It guarantees the maximum value of ISCR at connection points (CP). In the lower level, the location and capacity of FPADs are optimized. It ensures the ISCR value is above the critical short-circuit ratio (CSCR) to maintain the system strength. Location optimization is determined by the ISCR value at CP. Capacity optimization is solved using linear programming. Finally, case studies verify the effectiveness of the proposed optimization method in increasing VPP output capacity while maintaining VPPGCS strength.

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CSEE Journal of Power and Energy Systems
Pages 1940-1951

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Cite this article:
Li D, Sun Q, Hu J. Bi-level Optimal Allocation of Virtual Power Plants Under Grid Strength via Integrated Short-circuit Ratio. CSEE Journal of Power and Energy Systems, 2026, 12(4): 1940-1951. https://doi.org/10.17775/CSEEJPES.2022.08040

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Received: 14 November 2022
Revised: 14 January 2023
Accepted: 28 March 2023
Published: 28 December 2023
© 2022 CSEE.

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).