碳中和需求下新型电力系统工业用户可调节潜力量化评估方法

姚宏民; 张敏; 樊瑞; 高乐; 张世锋; 王腾鑫

姚宏民,张敏,樊瑞,高乐,张世锋,王腾鑫.碳中和需求下新型电力系统工业用户可调节潜力量化评估方法[J].电测与仪表,2026,63(6):41-51.
yaohongmin,Zhang min,Fan rui,Gao le,Zhang shifeng,Wang Tengxin.Quantitative evaluation method for adjustable potential of industrial users in novel power system under carbon neutrality demand[J].Electrical Measurement & Instrumentation,2026,63(6):41-51.

碳中和需求下新型电力系统工业用户可调节潜力量化评估方法

Quantitative evaluation method for adjustable potential of industrial users in novel power system under carbon neutrality demand

DOI：10.19753/j.issn1001-1390.2026.06.005

中文关键词: 新型电力系统改进经验模态分解可调节潜力双向长短期记忆网络注意力机制

英文关键词:novel power system, improved empirical mode decomposition, adjustable potential, bidirectional long short-term memory network, attention mechanism

基金项目:国网山西省电力公司科技项目（520530240009）

作者中文名	作者英文名	单位
姚宏民	yaohongmin	国网山西省电力有限公司电力科学研究院
张敏	Zhang min	国网山西省电力有限公司电力科学研究院
樊瑞	Fan rui	国网山西省电力有限公司电力科学研究院
高乐	Gao le	国网山西省电力有限公司电力科学研究院
张世锋	Zhang shifeng	国网山西省电力有限公司电力科学研究院
王腾鑫	Wang Tengxin	国网山西省电力有限公司电力科学研究院

摘要点击次数: 130

中文摘要:

构建新型电力系统是保障国家能源安全是实现“碳达峰、碳中和”目标的重要举措。但是，随着源荷双侧不确定性的大幅增加，传统源随荷动的平衡模式难以支撑新型电力系统的运行要求，亟需充分挖掘负荷侧各类可调节资源的灵活性潜力，解决新型电力系统调节能力不足与供需平衡的难题。为此，文中提出了一种面向新型电力系统工业用户的可调节潜力量化评估方法，采用改进的自适应噪声完备集合经验模态分解对工业负荷进行分解，考虑温度、湿度、电价和订单需求等多维影响因素，构建了工业用户可调节潜力分析数据集，利用牛顿-拉夫逊算法优化各分量双向长短期记忆网络参数并融合注意力机制，实现了工业用户响应日的可调节潜力量化评估；最后，通过实际数据算例验证所提方法能够克服工业用户负荷离散性、波动性大等问题，提高了可调节潜力量化评估的准确性。

英文摘要:

Constructing a novel power system is an important measure to safeguard national energy security and achieve the goals of carbon peaking and carbon neutrality. However, with the substantial increase in uncertainties on both the power generation and load sides, the traditional balance mode where power generation follows load fluctuations can hardly meet the operational requirements of the novel power system. It is therefore imperative to fully tap into the flexibility potential of various adjustable resources on the load side, so as to address the dilemmas of insufficient regulation capacity and supply-demand imbalance in novel power system. To this end, this paper proposes a quantitative evaluation method for the adjustable potential of industrial users oriented to the novel power system. The improved complete ensemble empirical mode decomposition with adaptive noise is adopted to decompose industrial loads. And then, considering multi-dimensional influencing factors such as temperature, humidity, electricity price and order demand, a dataset for analyzing the adjustable potential of industrial users is constructed. The Newton-Raphson algorithm is used to optimize the parameters of the bidirectional long short-term memory network for each component, combined with the attention mechanism, thus realizing the quantitative evaluation of the adjustable potential of industrial users on the response day. A case study based on actual data verifies that the proposed method can overcome the problems of high discreteness and volatility of industrial user loads, and improve the accuracy of quantitative evaluation of adjustable potential.

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