1 |
肖白, 张小娜, 姜卓, 等. 考虑本位元胞接受能力和相邻元胞负荷影响的空间负荷预测. 电力系统自动化, 2021, 45 (12): 57- 64.
URL
|
|
XIAO B, ZHANG X N, JIANG Z, et al. Spatial load forecasting considering acceptability of standard cell and influence of load of adjacent cells. Automation of Electric Power Systems, 2021, 45 (12): 57- 64.
URL
|
2 |
肖白, 黎平. 城网空间电力负荷预测中的负荷规律性分析. 电网技术, 2009, 33 (20): 113- 119.
URL
|
|
XIAO B, LI P. Load regularity analysis on spatial load forecasting of urban power system. Power System Technology, 2009, 33 (20): 113- 119.
URL
|
3 |
曹梦, 刘宝成, 何金, 等. 基于前趋势相似度的细粒度用户用电负荷预测. 计算机应用与软件, 2018, 35 (7): 158-164, 172.
doi: 10.3969/j.issn.1000-386x.2018.07.028
|
|
CAO M, LIU B C, HE J, et al. Fine grained user power load forecasting based on prior trend similarity. Computer Applications and Software, 2018, 35 (7): 158-164, 172.
doi: 10.3969/j.issn.1000-386x.2018.07.028
|
4 |
马星河, 娄晨阳, 赵军营, 等. 基于人工蜂群算法的空间负荷预测. 电力系统及其自动化学报, 2018, 30 (8): 102- 107.
doi: 10.3969/j.issn.1003-8930.2018.08.017
|
|
MA X H, LOU C Y, ZHAO J Y, et al. Spatial load forecasting based on artificial bee colony algorithm. Journal of power Systems and Automation, 2018, 30 (8): 102- 107.
doi: 10.3969/j.issn.1003-8930.2018.08.017
|
5 |
邓燕国, 王冰, 曹智杰, 等. 基于熵权法与GRA-ELM的配电网空间负荷预测. 电力工程技术, 2021, 40 (4): 136- 141.
URL
|
|
DENG Y G, WANG B, CAO Z J, et al. Spatial load forecasting of distribution network based on entropy weight method and GRA-ELM. Electric Power Engineering Technology, 2021, 40 (4): 136- 141.
URL
|
6 |
肖白, 张婕, 姜卓, 等. 基于秩次集对分析理论的空间负荷预测方法. 电力自动化设备, 2020, 40 (4): 153- 158.
URL
|
|
XIAO B, ZHANG J, JIANG Z, et al. Spatial load forecasting method based on rank set pair analysis. Electric Power Automation Equipment, 2020, 40 (4): 153- 158.
URL
|
7 |
郑伟民, 叶承晋, 张曼颖, 等. 基于Softmax概率分类器的数据驱动空间负荷预测. 电力系统自动化, 2019, 43 (9): 117- 124.
URL
|
|
ZHENG W M, YE C J, ZHANG M Y, et al. Data-driven spatial load forecasting method based on Softmax probabilistic classifier. Automation of Electric Power Systems, 2019, 43 (9): 117- 124.
URL
|
8 |
郭艳飞, 程林, 李洪涛, 等. 基于支持向量机和互联网信息修正的空间负荷预测方法. 中国电力, 2019, 52 (4): 80- 88.
doi: 10.3969/j.issn.1007-3361.2019.04.023
|
|
GUO Y F, CHENG L, LI H T, et al. Spatial load forecasting method based on support vector machine and Internet information correction. Electric Power, 2019, 52 (4): 80- 88.
doi: 10.3969/j.issn.1007-3361.2019.04.023
|
9 |
肖白, 杨修宇, 穆钢, 等. 基于多变量分析的城市电网空间负荷预测方法. 东北电力大学学报, 2013, 33 (S1): 39- 44.
URL
|
|
XIAO B, YANG X Y, MU G, et al. Spatial electric load forecasting of urban power system based on multivariate analysis. Journal of Northeast Dianli University, 2013, 33 (S1): 39- 44.
URL
|
10 |
庞松岭, 刘岱, 曹杰. 基于MapInfo和VB的空间负荷预测系统设计与实现. 计算机应用与软件, 2008, 25 (6): 163-164, 210.
doi: 10.3969/j.issn.1000-386X.2008.06.064
|
|
PANG S L, LIU D, CAO J. Design and implementation of spatial load forecasting system based on MapInfo and VB. Computer Applications and Software, 2008, 25 (6): 163-164, 210.
doi: 10.3969/j.issn.1000-386X.2008.06.064
|
11 |
SHINDO T, YOKOYAMA S. Lightning occurrence data observed with lightning location systems in Japan: 1992-1995. IEEE Transactions on Power Delivery, 1998, 13 (4): 1468- 1474.
doi: 10.1109/61.714797
|
12 |
张纪伟, 刘晓明, 贡卓, 等. 基于城市用地性质及开发时间的改进空间负荷预测方法研究. 供用电, 2019, 36 (7): 65- 70.
URL
|
|
ZHANG J W, LIU X M, GONG Z, et al. Research on improved spatial load forecasting method based on land use and development time. Distribution & Utilization, 2019, 36 (7): 65- 70.
URL
|
13 |
李勤超, 周立中, 赵艳龙, 等. 基于分布式光伏典型日曲线的统调负荷预测方法. 浙江电力, 2019, 38 (6): 113- 117.
URL
|
|
LI Q C, ZHOU L Z, ZHAO Y L, et al. A unified dispatch load forecasting method based on the typical daily load curve of distributed PV power. Zhejiang Electric Power, 2019, 38 (6): 113- 117.
URL
|
14 |
杨军胜, 彭石, 王承民, 等. 基于城市用地性质的配网空间负荷预测研究. 电测与仪表, 2018, 55 (11): 30- 34.
URL
|
|
YANG J S, PENG S, WANG C M, et al. Research of spatial load forecasting in distribution network based on grid partition of urban land-use property. Electrical Measurement & Instrumentation, 2018, 55 (11): 30- 34.
URL
|
15 |
周湶, 孙威, 任海军, 等. 基于最小二乘支持向量机和负荷密度指标法的配电网空间负荷预测. 电网技术, 2011, 35 (1): 66- 71.
URL
|
|
ZHOU Q, SUN W, REN H J, et al. Spatial load forecasting of distribution network based on least squares support vector machine and load density index system. Power System Technology, 2011, 35 (1): 66- 71.
URL
|
16 |
唐玮, 钟士元, 舒娇, 等. 基于GRA-LSSVM的配电网空间负荷预测方法研究. 电力系统保护与控制, 2018, 46 (24): 76- 82.
URL
|
|
TANG W, ZHONG S Y, SHU J, et al. Research on spatial load forecasting of distribution network based on GRA-LSSVM method. Power System Protection and Control, 2018, 46 (24): 76- 82.
URL
|
17 |
肖白, 周潮, 穆钢. 空间电力负荷预测方法综述与展望. 中国电机工程学报, 2013, 33 (25): 78-92, 14.
URL
|
|
XIAO B, ZHOU C, MU G. Review and prospect of the spatial load forecasting methods. Proceedings of the CSEE, 2013, 33 (25): 78-92, 14.
URL
|
18 |
NUTKIEWICZ A, YANG Z, JAIN R K. Data-driven Urban Energy-Simulation(DUE-S): a framework for integrating engineering simulation and machine learning methods in a multi-scale urban energy modeling workflow. Applied Energy, 2018, 225, 1176- 1189.
doi: 10.1016/j.apenergy.2018.05.023
|
19 |
YE C J, DING Y, SONG Y H, et al. A data driven multi-state model for distribution system flexible planning utilizing hierarchical parallel computing. Applied Energy, 2018, 232, 9- 25.
doi: 10.1016/j.apenergy.2018.09.202
|
20 |
LE RAY G, PINSON P. Online adaptive clustering algorithm for load profiling. Sustainable Energy, Grids and Networks, 2019, 17, 100181.
doi: 10.1016/j.segan.2018.100181
|
21 |
TEERARATKUL T, O'NEILL D, LALL S. Shape-based approach to household electric load curve clustering and forecasting. IEEE Transactions on Smart Grid, 2018, 9 (5): 5196- 5206.
doi: 10.1109/TSG.2017.2683461
|
22 |
ZHANG Z, TAVENARD R, BAILLY A, et al. Dynamic time warping under limited warping path length. Information Sciences, 2017, 393, 91- 107.
doi: 10.1016/j.ins.2017.02.018
|
23 |
LIN S F, LI F X, TIAN E W, et al. Clustering load profiles for demand response applications. IEEE Transactions on Smart Grid, 2019, 10 (2): 1599- 1607.
doi: 10.1109/TSG.2017.2773573
|
24 |
王哲, 万宝, 凌天晗, 等. 基于谱聚类和LSTM神经网络的电动公交车充电负荷预测方法. 电力建设, 2021, 42 (6): 58- 66.
URL
|
|
WANG Z, WAN B, LING T H, et al. Electric bus charging load forecasting method based on spectral clustering and LSTM neural network. Electric Power Construction, 2021, 42 (6): 58- 66.
URL
|
25 |
BI Z Q, LENG Y B, LIU Z, et al. An improved spectral clustering algorithm using fast dynamic time warping for power load curve analysis. Berlin, Germany: Springer, 2020: 143- 159.
|
26 |
LIU M P, QIN H, CAO R, et al. Short-term load forecasting based on improved TCN and DenseNet. IEEE Access, 2022, 10, 115945- 115957.
doi: 10.1109/ACCESS.2022.3218374
|
27 |
郑豪丰, 杨国华, 康文军, 等. 基于多负荷特征和TCN-GRU神经网络的负荷预测. 中国电力, 2022, 55 (11): 142- 148.
URL
|
|
ZHENG H F, YANG G H, KANG W J, et al. Load forecasting based on multiple load features and TCN-GRU neural network. Electric Power, 2022, 55 (11): 142- 148.
URL
|