A Framework for Inertia Pricing in Renewable-Rich Power Systems Using Convex Hull Pricing

With the rapid development of power systems rich in renewable energy, inertia shortages pose significant challenges to frequency security. There is an urgent need for appropriate market pricing mechanisms to quantify the economic value of inertia and incentivize inertia resources to participate in system frequency regulation. Existing market pricing mechanisms struggle to address non-convex generation scheduling problems involving inertia constraints, often resulting in substantial uplift payments that undermine market efficiency and reduce market transparency. To address this issue, this paper proposes a novel convex hull pricing framework specifically designed for the integrated energy–inertia market. The core innovation lies in combining Dantzig–Wolfe decomposition with column generation algorithms to efficiently solve non-convex optimization problems by dynamically constructing the convex hull of feasible dispatch schemes. Based on transient frequency security metrics, the method derives the minimum inertia requirement constraint for the system and calculates the economic value of inertia in non-convex markets using convex hull pricing. Simulation studies on a modified IEEE 39-node system demonstrate two major breakthroughs: the method accurately assesses the economic value of synchronous inertia, with prices reflecting scarcity as wind penetration increases and significantly reduces total system uplift payments compared to integer relaxation pricing schemes. Consequently, this research provides a transparent, incentive-compatible, and cost-effective tool for designing and operating future inertia ancillary service markets.

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Publication Details

Journal
Processes
Published
2026-02-15
DOI
https://doi.org/10.3390/pr14040667
Primary Topic
Electric Power System Optimization
Type
article
Field-Weighted Citation Impact
0.00

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A Framework for Inertia Pricing in Renewable-Rich Power Systems Using Convex Hull Pricing

Yuyang Guan, Jing Ye, Wenjing Wu, Yifei Sun et al.
Processes
Electric Power System Optimization
article

A Framework for Inertia Pricing in Renewable-Rich Power Systems Using Convex Hull Pricing

Yuyang Guan, Jing Ye, Wenjing Wu, Yifei Sun, Bijiang Zhu
article en

Abstract

With the rapid development of power systems rich in renewable energy, inertia shortages pose significant challenges to frequency security. There is an urgent need for appropriate market pricing mechanisms to quantify the economic value of inertia and incentivize inertia resources to participate in system frequency regulation. Existing market pricing mechanisms struggle to address non-convex generation scheduling problems involving inertia constraints, often resulting in substantial uplift payments that undermine market efficiency and reduce market transparency. To address this issue, this paper proposes a novel convex hull pricing framework specifically designed for the integrated energy–inertia market. The core innovation lies in combining Dantzig–Wolfe decomposition with column generation algorithms to efficiently solve non-convex optimization problems by dynamically constructing the convex hull of feasible dispatch schemes. Based on transient frequency security metrics, the method derives the minimum inertia requirement constraint for the system and calculates the economic value of inertia in non-convex markets using convex hull pricing. Simulation studies on a modified IEEE 39-node system demonstrate two major breakthroughs: the method accurately assesses the economic value of synchronous inertia, with prices reflecting scarcity as wind penetration increases and significantly reduces total system uplift payments compared to integer relaxation pricing schemes. Consequently, this research provides a transparent, incentive-compatible, and cost-effective tool for designing and operating future inertia ancillary service markets.

ProcessesVol. 14(4)
China Three Gorges University (CN)
National Natural Science Foundation of China
Affordable and clean energy
Openalex Percentile: Top 55%
Electric Power System Optimization
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