储能科学与技术 ›› 2025, Vol. 14 ›› Issue (4): 1701-1708.doi: 10.19799/j.cnki.2095-4239.2024.1023

• 储能技术经济性分析 • 上一篇    下一篇

适应风光波动性和储能动态调峰容量的风-光-火-储协同低碳经济调度

莫东(), 李秋文, 陆裕富   

  1. 广西电网电力调度控制中心,广西 南宁 530023
  • 收稿日期:2024-11-08 修回日期:2024-11-14 出版日期:2025-04-28 发布日期:2025-05-20
  • 通讯作者: 莫东 E-mail:547544933@qq.com
  • 作者简介:莫东(1987—),男,硕士,高级工程师,研究方向为电力系统优化调度,E-mail:547544933@qq.com
  • 基金资助:
    广西电网公司科技项目(046000KK52222033)

Wind solar thermal storage collaborative low-carbon economic dispatch that adapts to wind solar volatility and dynamic peak shaving capacity of energy storage

Dong MO(), Qiuwen LI, Yufu LU   

  1. Guangxi Power Grid Power Dispatching and Control Center, Nanning 530023, Guangxi, China
  • Received:2024-11-08 Revised:2024-11-14 Online:2025-04-28 Published:2025-05-20
  • Contact: Dong MO E-mail:547544933@qq.com

摘要:

风光新能源高比例并网,其强波动性使电网调峰面临挑战,而储能的双向充放电具有优异的调峰能力,因此研究新型储能动态可用调峰容量,使其适应风光波动性的优化调度成为新型电力系统亟须解决的核心问题。对此,本工作提出了适应风光波动性和储能动态调峰容量的风-光-火-储协同低碳经济调度。首先,提出了最优Copula联合概率的风光波动性的出力分布函数及有功出力场景,为储能适应该波动性提出基本要求;其次,给出了火电机组的调峰成本函数、弃风弃光成本函数、储能动态调峰成本函数及四者的运行成本,并建立了联合优化目标函数及约束条件;然后,提出了改进的粒子群优化算法对所提联合优化目标函数的求解方法;最后,以某实际算例对所提算法进行仿真验证,结果表明所提低碳经济调度方法能够在降低弃风弃光的同时提高电网调峰能力和经济效益。

关键词: 双碳, 风光新能源, 储能, 调峰, 经济调度

Abstract:

The integration of a high proportion of wind and solar energy into the power grid poses challenges for grid peak regulation owing to the inherent volatility of these renewable energy sources. However, energy storage systems, with their bidirectional charging and discharging capabilities, offer an excellent solution for peak regulation. Therefore, addressing the dynamic peak regulation capacity of energy storage to accommodate wind and solar fluctuations has become a critical issue in developing the new power system. To tackle this challenge, a collaborative low-carbon economic dispatch model combining wind, solar, thermal power, and energy storage has been proposed. This helps energy storage systems to adapt to the volatility of these energy sources. First, the output distribution function and active output scenarios were developed using the optimal Copula joint probability method. This modeling provides a strong foundation for enabling energy storage systems to adapt to the volatility of wind and solar energy. Second, the peak shaving cost function, the wind and solar power curtailment cost function, the dynamic peak shaving cost function of energy storage, and the operating costs of thermal power units were defined. These were integrated into a joint optimization objective function, accompanied by a set of constraint conditions. Third, a revised particle swarm optimization algorithm was employed to efficiently solve the joint optimization objective function. Finally, a practical example was used to simulate and validate the proposed algorithm. The results demonstrated that the low-carbon economic dispatch method significantly improves the power grid's peak shaving capacity and economic performance, while reducing wind and solar power curtailment.

Key words: dual carbon, wind and solar new energy, energy storage, peak shaving, economic dispatch

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