Coordinated Energy–Reserve Market Clearing and Pricing Mechanism for Regional Power Systems with High Wind Penetration

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Authors: Peng Zou, Xiaotao Luo, Xueting Cheng, Yizhao Liu, Jianbin Fan, Jian Le, Zheng Fang
Cited by: 2
References: 30

Abstract

Addressing the challenges of insufficient reserve capacity allocation and wind power uncertainty-induced security and economic concerns under high wind power penetration, this paper develops an integrated energy–reserve market clearing model for regional electricity markets. Firstly, a comprehensive day-ahead market clearing mechanism is designed, encompassing market participant bidding, security-constrained unit commitment (SCUC), security-constrained economic dispatch (SCED), nodal marginal price calculation, and market settlement. Secondly, a SCUC model targeting the minimization of total system operating costs and a SCED model targeting the minimization of energy and reserve procurement costs are established, comprehensively incorporating constraints, such as power balance, unit output and ramping limits, reserve requirements, and network power flows, with nodal marginal prices calculated using the Lagrangian multiplier method. Finally, simulation verification is conducted using a modified IEEE 30-bus system as a case study. Results demonstrate that the proposed model effectively coordinates wind power integration with system reserve requirements, achieving economically optimal dispatch while ensuring grid security and stability. Thermal units obtain substantial market revenues by providing reserve ancillary services, while wind units achieve high revenues through zero marginal cost advantages, fully validating the model’s effectiveness and economic efficiency under high wind power penetration conditions. The research findings provide theoretical foundations and practical guidance for constructing electricity spot market mechanisms adapted to large-scale renewable energy integration.

Fields of Study & Subjects

Electric Power System Optimization Integrated Energy Systems Optimization Energy Load and Power Forecasting

Publication details

Journal / source
Applied Sciences
Publisher
MDPI AG
Volume
16
Issue
4
Pages
2123–2123
Publication date
22 February 2026
Language
EN