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Research Article | Open Access

An Amplitude–Phase Parametric Method for Evaluating the Evolution of Fluctuation in Integrated Load-Photovoltaic-Wind Waveforms

Abstract

In high-penetration renewable power systems, wind power, photovoltaic power, and most loads are non-dispatchable, and are collectively referred to as passive power. The growth of passive power increases the system demand for regulation capacity while displacing conventional regulation resources, thereby intensifying the supply–demand mismatch. Since load, photovoltaic, and wind power waveforms have distinct morphologies, their integrated waveform evolves during aggregation. Characterizing the integration properties of all passive power waveforms is therefore essential for configuring regulation resources on demand and achieving power balance. Conventional studies on source–load power characteristics mainly focus on the stochasticity of power values, while the temporal characteristics of power and the morphological evolution of integrated waveforms have received limited attention. This paper proposes an amplitude–phase analysis method for power waveforms, in which waveform morphology is characterized by amplitude and phase across multiple timescales. On this basis, the phase and amplitude relationships among multiple power waveforms are analyzed, along with the multiscale formation mechanism governing multivariate waveform integration evolution. The regular evolution trends of integrated load–wind–photovoltaic waveforms under different penetration levels are further revealed. The effectiveness of the proposed method is validated using real-world data.

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Power and Energy Future
Article number: 9650011

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Cite this article:
Zhao J, Mu G, Yan G, et al. An Amplitude–Phase Parametric Method for Evaluating the Evolution of Fluctuation in Integrated Load-Photovoltaic-Wind Waveforms. Power and Energy Future, 2026, 1(2): 9650011. https://doi.org/10.26599/PEF.2025.9650011

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Received: 19 May 2026
Revised: 16 June 2026
Accepted: 20 June 2026
Published: 04 August 2026
© The Author(s) 2026. Published by Tsinghua University Press.

This is an open access article under the Creative CommonsAttribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).