[1]Lago,Jesus,De,et al.Forecasting day-ahead electricity prices in Europe: The importance of considering market integration[J].Applied Energy, 2018.[2]Joachim L S ,Emil J V ,Jensen A B , et al.Principal spatiotemporal mismatch and electricity price patterns in a highly decarbonized networked European power system.[J].iS cience,2022,25(6):104380-104380.[3] 罗纯坚, 李姚旺, 许汉平, 等. 需求响应不确定性对日前优化调度的影响分析[J]. 电力系统自动化, 2017, 41(5):8.[4] 舒印彪, 张正陵, 汤涌, 等. 新型电力系统构建的若干基本问题[J]. 中国电机工程学报, 2024, 44(21):8327-8340.[5] 韩升科, 胡飞虎, 陈之腾, 张琳, 白兴忠. 基于GCN-LSTM 的日前市场边际电价预测[J]. 中国电机工程学报,2022,42(9):3276-3285.[6] 侯庆春, 杜尔顺, 田旭, 等. 数据驱动的电力系统运行方式分析[J]. 中国电机工程学报, 2021, 41(1):12.[7]Jesus L ,Grzegorz M ,Bart S D , et al.Forecasting day-ahead electricity prices: A review of state-of-the-art algorithms, best practices and an open-access benchmark[J]. Applied Energy,2021,293.[8] 加鹤萍, 郭宇辰, 马乾鑫, 等. 基于机器学习方法的现货电价预测研究综述[J]. 电力建设, 2025, 46(2):160-179.[9] 薛万磊, 牟颖, 赵昕, 等. 基于LSTM 深度学习方法的电力需求预测研究—— 考虑现货市场电价新兴影响因素的分析[J]. 价格理论与实践,2025,(04):93-98.[10] 邵云姝, 张琳, 周乃康, 等. 基于长短期记忆网络的电力市场价格预测研究[J]. 动力工程学报,2025,45(05):733-737.[11] 刘峻, 王鹏, 胡坤, 等. 基于CNN-Self attention 双重注意力机制的实时与日前电价差值区间预测方法[J/OL]. 华北电力大学学报( 自然科学版),1-11[2025-10-27].[12] 李子凯, 杨波, 周忠堂, 等. 考虑高比例风电波动的多注意力TCN 电价预测方法[J]. 电测与仪表,2025,62(03):138-146.[13]Hadjout D , Torres J F , Troncoso A ,et al.Electricity consumption forecasting based on ensemble deep learning with application to the Algerian market[J].Energy, 2022, 243.[14] 中国华能集团清洁能源技术研究院有限公司， 华能招采数字科技有限公司. 一种基于TCN-Transformer 模型的电价预测方法、系统、装置及存储介质.CN120374166A[P].2025-07-25.[15]Lecun Y , Boser B , Denker J ,et al.Backpropagation Applied to Handwritten Zip Code Recognition[J].Neural Computation, 1989, 1(4):541-551.[16]O’Shea K ,Nash R .An Introduction to Convolutional Neural Networks.[J].CoRR,2015,abs/1511.08458.[17]Hochreiter S , Schmidhuber J .Long Short-Term Memory[J].Neural Computation, 1997, 9(8):1735-1780.[18]Vaswani A, Shazeer N, Parmar N, et al. Attention is all you need[J]. Advances in neural information processing systems, 2017, 30.[19]Li J ,Wen X ,Jia L , et al.A Transformer-based model fusing temporal dependence and variable correlation for short and medium-term electricity price forecasting[J]. Energy,2025,338138799-138799.[20]Hou G ,Li Q ,Huang C .Spatiotemporal forecasting using multi-graph neural network assisted dual domain transformer for wind power[J].Energy Conversion and Managem ent,2025,325119393-119393.[21] 中国科学院广州能源研究所. 甘肃：电源装机突破1 亿千瓦，新能源已成为第一大电源[EB/OL]. (2025-01-13) [2025-12-14].[22] 国家能源局. 电力现货市场基本规则（试行）[R/OL]. 北京: 国家能源局, 2023. (2023-09-07) [2025-12-14].[23] 国家发展改革委, 国家能源局. 电力现货连续运行地区市场建设指引[EB/OL]. (2025-09-02)[2025-12-14].[24]Saleh A M ,Vokony István, Khan M A ,et al.Power system stability in the Era of energy Transition: Importance, Opportunities, Challenges, and future directions[J]. Energy Conversion and Management: X, 2024, 24(000).