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May 6, 2026Energies0 citationsOpen Access

Flexible Load Reserve Capacity Evaluation Method Considering User Response Willingness for Sustainable Reserve Provision

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ZOZhongxi OuLQLihong QianSPSui Peng

Key Points

  • This research aims to develop a method for evaluating flexible load reserve capacity while considering user response willingness.
  • Proposes a results-oriented reserve capacity evaluation method for flexible loads.
  • Develops a fuzzy logic system to assess user response willingness of electric vehicles and air-conditioning users.
  • Establishes a probabilistic modeling approach based on the theory of planned behavior to model user decision-making behavior.
  • Constructs a comprehensive framework that integrates user willingness states with operational constraints.
  • Demonstrates improved objectivity in flexible load reserve capacity assessments.
  • Maintains high levels of user participation willingness.
  • Supports long-term sustainable application of flexible loads as grid reserve resources.

Abstract

In future active distribution networks with high penetrations of renewable energy, flexible loads are expected to play an increasingly important role as reserve resources to support the sustainable and reliable operation of power grids. Accurate evaluation of flexible load reserve capacity is therefore essential for reliable reserve scheduling. Existing research mainly focuses on the operational characteristics and physical constraints of flexible loads, while insufficiently accounting for user response willingness and the uncertainty of user decision-making behavior, which may lead to biased reserve capacity assessments and impair the sustainability of reserve supply in actual grid operation. To address this issue, this paper proposes a results-oriented reserve capacity evaluation method for flexible loads that explicitly incorporates user response willingness. Specifically, a fuzzy logic system is developed to quantitatively characterize the response willingness of electric vehicle (EV) and air-conditioning (AC) users under multiple influencing factors. Then, a probabilistic modeling approach for user decision-making behavior is established using the theory of planned behavior, enabling explicit representation of behavioral uncertainty. Furthermore, a comprehensive reserve capacity evaluation framework for flexible loads is constructed by integrating user willingness states, sustainable response duration, and operational power constraints. Finally, the case studies demonstrate that the proposed method can effectively improve the objectivity of flexible load reserve capacity assessments while maintaining high user participation willingness, thus supporting the long-term sustainable application of flexible loads as grid reserve resources.

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Cite This Study

Ou et al. (2026) studied this question.

synapsesocial.com/papers/69fa8e8904f884e66b530ee8https://doi.org/10.3390/en19092165
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