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Practical Application of Complementary Regulation Strategy of Run-of-River Small Hydropower and Distributed Photovoltaic Based on Multi-Scale Copula-MPC Algorithm
Practical Application of Complementary Regulation Strategy of Run-of-River Small Hydropower and Distributed Photovoltaic Based on Multi-Scale Copula-MPC Algorithm
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Practical Application of Complementary Regulation Strategy of Run-of-River Small Hydropower and Distributed Photovoltaic Based on Multi-Scale Copula-MPC Algorithm
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Practical Application of Complementary Regulation Strategy of Run-of-River Small Hydropower and Distributed Photovoltaic Based on Multi-Scale Copula-MPC Algorithm
Practical Application of Complementary Regulation Strategy of Run-of-River Small Hydropower and Distributed Photovoltaic Based on Multi-Scale Copula-MPC Algorithm

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Practical Application of Complementary Regulation Strategy of Run-of-River Small Hydropower and Distributed Photovoltaic Based on Multi-Scale Copula-MPC Algorithm
Practical Application of Complementary Regulation Strategy of Run-of-River Small Hydropower and Distributed Photovoltaic Based on Multi-Scale Copula-MPC Algorithm
Journal Article

Practical Application of Complementary Regulation Strategy of Run-of-River Small Hydropower and Distributed Photovoltaic Based on Multi-Scale Copula-MPC Algorithm

2025
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Overview
A novel multi-scale copula-based model predictive control (MPC) method is proposed to address the core regulation challenges of runoff hydropower and distributed photovoltaic systems within high-penetration renewable energy grids. Complex spatio-temporal complementarity under ecological constraints and the limitations of conventional methods were critically analyzed. The core innovation lies in integrating copula theory with MPC, enabling adaptive spatio-temporal optimization and weight adjustment to significantly enhance the efficiency of complementary regulation and overcome traditional performance bottlenecks. Key nonlinear dependencies of water–solar resources were investigated, and mainstream techniques (copula analysis, MPC, rolling optimization, adaptive weighting) were evaluated for their applicability. Future directions for improving modeling precision and intelligent adaptive control are outlined.