考虑柔性负荷的新型电力系统源荷日前-日内低碳优化调度  

Day-Ahead and Intra-Day Low-Carbon Optimal Scheduling of New Power System Source-Load Considering Flexible Load

作　　者：李若琼[1] 司宇杰 杨承辰 李欣 LI Ruoqiong;SI Yujie;YANG Chengchen;LI Xin(School of Automation and Electrical Engineering,Lanzhou Jiaotong University,Lanzhou 730070,China;Yunnan Power Grid Co.,Ltd.,Kunming 650000,China;School of New Energy and Power Engineering,Lanzhou Jiaotong University,Lanzhou 730070,China)

机构地区：[1]兰州交通大学自动化与电气工程学院,兰州730070 [2]云南电网有限责任公司,昆明650000 [3]兰州交通大学新能源与动力工程学院,兰州730070

出　　处：《南方电网技术》2025年第3期116-129,共14页Southern Power System Technology

基　　金：国家自然科学基金资助项目(51767015);甘肃省自然科学基金资助重点项目(22JR5RA317)。

摘　　要：柔性负荷参与新型电力系统的优化调度对于提高新能源的消纳能力具有显著作用,但目前柔性负荷潜力尚未充分挖掘。针对这一问题,提出一种基于源荷预测的日前-日内优化调度方法。首先,采用麻雀搜索算法优化卷积长短时记忆神经网络(sparrow search algorithm is used to optimize the convolutional long-term and short-term memory neural network,SSA-CNN-LSTM)对新能源和负荷进行日前和日内功率预测;其次,根据柔性负荷的特性和需求响应灵活性,将负荷分为可平移、可转移和可削减负荷等不同类型,以考虑阶梯式碳交易成本的系统运行成本和污染气体排放最优为目标构建源荷互动的日前-日内两阶段低碳环境经济调度模型;最后,利用改进多目标灰狼算法(multi-objective grey wolf algorithm,MOGWO)对模型进行求解。算例分析表明,通过对柔性负荷分类参与调度较传统方式总成本降低8.6%、污染物排放减少4.1%、新能源消纳能力提高4.2%,在多时间尺度内显著降低新能源和负荷响应的不确定性并提高新型电力系统的低碳环境经济综合效益。The participation of flexible load in the optimal scheduling of new power system has a significant effect on improving the consumption capacity of new energy,but the potential of flexible load has not been fully explored.To solve this problem,this paper presents a day-ahead and intra-day optimal scheduling method based on source-load prediction.Firstly,the sparrow search algorithm is used to optimize the convolutional long-term and short-term memory neural network(SSA-CNN-LSTM)for day-ahead and intraday power prediction of new energy and load.Secondly,according to the characteristics of flexible load and the flexibility of demand response,the load is divided into different types,such as shiftable,transferable and reducible load.The day-ahead and intra-day twostage low-carbon environmental economic dispatch model of source-load interaction is constructed with the goal of optimizing the system operation cost and pollutant gas emission considering the staged carbon transaction cost.Finally,the improved multi-objective grey wolf algorithm(MOGWO)is used to solve the model.The example analysis shows that the total cost of the flexible load classification is reduced by 8.6%,the pollutant emission is reduced by 4.1%,and the new energy consumption capacity is increased by 4.2%compared with the traditional method.The uncertainty of new energy and load response is significantly reduced in multiple time scales and the low-carbon environmental and economic comprehensive benefits of the new power system are improved.

关 键 词：柔性负荷 新型电力系统 源-荷多时间尺度 低碳优化调度 

分 类 号：TM73[电气工程—电力系统及自动化]