1.酒钢(集团)嘉峪关宏晟电热有限责任公司,甘肃 嘉峪关 735100
2.国电南瑞科技股份有限公司,南京 211106
高建生(1983),男,工程师,从事冶金企业电网生产运行方面的研究,952093772@qq.com;
汪马翔(1982),男,高级工程师,硕士,从事电力系统及其自动化方面的研究,2672550737@qq.com。
邢鹏生(1987),男,高级工程师,从事企业电网继电保护方面的研究,122365711@qq.com;
肖柱(1983),男,副高级工程师,从事电网安全稳定控制和新能源并网消纳方面的研究,36512029@qq.com。
收稿:2025-02-20,
修回:2025-03-28,
网络出版:2025-05-08,
纸质出版:2025-10-25
移动端阅览
高建生,汪马翔,邢鹏生等.计及钢铁企业参与的含风电电力系统协同调度策略[J].综合智慧能源,2025,47(10):52-59.
GAO Jiansheng,WANG Maxiang,XING Pengsheng,et al.Coordinated scheduling strategy for wind power integrated power systems considering participation of steel enterprises[J].BLASTING,2025,47(10):52-59.
高建生,汪马翔,邢鹏生等.计及钢铁企业参与的含风电电力系统协同调度策略[J].综合智慧能源,2025,47(10):52-59. DOI: 10.3969/j.issn.2097-0706.2025.10.006.
GAO Jiansheng,WANG Maxiang,XING Pengsheng,et al.Coordinated scheduling strategy for wind power integrated power systems considering participation of steel enterprises[J].BLASTING,2025,47(10):52-59. DOI: 10.3969/j.issn.2097-0706.2025.10.006.
针对当前含风电电力系统中大规模新能源难以消纳及钢铁企业缺乏参与调度积极性的问题,提出计及钢铁企业参与的含风电系统协同调度策略。分析钢铁企业参与风电消纳的模式,基于电弧炉的调度特性对其进行建模;采用数据驱动方法进行大规模场景生成,分析电弧炉与风电出力的不确定性叠加影响,确定电力系统应对不确定性波动所需的备用容量;基于生成的场景集,提出计及风电出力变化与源荷波动的钢铁企业自适应电价机制,激励其参与需求响应;建立兼顾多方利益的优化调度模型并采用人工蜂群算法求解;通过算例对所提策略进行仿真验证。结果表明,所提方法可以在保证钢铁企业调度积极性的同时提高系统的经济性与风电消纳。
To address the challenges of large-scale renewable energy consumption in the current wind power integrated power systems and the lack of enthusiasm among steel enterprises to participate in scheduling, a coordinated scheduling strategy of wind power systems considering the participation of steel enterprises was proposed. The participation modes of steel enterprises in wind power consumption were analyzed, and modeling was conducted based on the scheduling characteristics of electric arc furnace. The data-driven method was used to generate large-scale scenarios, analyze the combined effect of uncertainties of electric arc furnace and wind power output, and determine the reserve capacity required by the power system to cope with uncertainty fluctuations. Based on the generated scenario set, an adaptive electricity price mechanism for steel enterprises was proposed, which considered the variation of wind power output and source-load fluctuation to encourage their participation in demand response. An optimal scheduling model considering the interests of multiple stakeholders was established and solved by the artificial bee colony algorithm. Numerical examples were then provided to simulate and verify the proposed method. The results showed that the proposed method could improve the economic efficiency and wind power consumption of the system while ensuring the scheduling enthusiasm of steel enterprises.
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