个人简介
教育经历
2012-2016 本科，四川大学电气信息学院，电气工程及其自动化专业
2016-2021 博士，四川大学电气工程学院，电力系统及其自动化专业
(‘3+2+3’ 本硕博连读计划) 导 师：刘俊勇教授
研究方向: 电力系统稳定分析和控制，人工智能在电力系统调控领域的应用研究
论文题目: 人工智能驱动的断面极限传输容量快速计算及调控方法研究
2018-2019 访问学者，美国威斯康星大学密尔沃基分校，工程和应用科学学院 导 师：Prof. Lingfeng Wang 研究方向：人工智能在电力系统调控领域的应用研究
专利：
[1] 刘友波, 邱高, 等. 一种基于深度学习的极限传输容量的计算方法. 四川省: CN112001066A, 2020-07-30.
[2] 邱高, 等. 一种感知风险的深度学习驱动的极限传输容量调整方法. 已授权，四川省: 2020107395873, 2021-11-09.
科研项目
2015.01-2020.06 国家自然科学基金重点项目， 基于大数据的电力系统运行行为识别提取与表征（51437003），386万，优秀结题
2017.11-2018.11 国家重点研发计划项目， 适应全球能源互联网的规模化储能应用关键技术研究（2018YFB0905500）， 25万，结题
2019.01-2021.06 国网总部科技项目， 应用于电网运行方式分析的深度强化学习技术研究（SGNXD00DWJS1900012），50万，结题
2020.03-2020.12 国网西北分部科技项目， 考虑西北电网安全运行的源荷侧联动调峰机制分析，130万，结题
2021.01-2022.12 国网公司科技项目、国网两个“一体化”重大专项， 高比例新能源区域电网消纳受阻因素智能辨识及辅助决策技术研究（5229DK21000D），82万，在研
近期论文
查看导师新发文章
（温馨提示：请注意重名现象，建议点开原文通过作者单位确认）
[1] Gao Qiu, et al., “Analytic Deep Learning-based Surrogate Model for Operational Planning with Dynamic TTC Constraints,” in IEEE Transactions on Power Systems, doi: 10.1109/TPWRS.2020.3041866.
[2] Gao Qiu, et al., "Hybrid Deep Learning for Dynamic Total Transfer Capability Control," in IEEE Transactions on Power Systems, vol. 36, no. 3, pp. 2733-2736, May 2021.
[3] Gao Qiu, et al., "Surrogate-assisted Optimal Re-Dispatch Control for Risk-aware Regulation of Dynamic Total Transfer Capability," in IET Generation, Transmission & Distribution, doi: 10.1049/gtd2.12147.
[4] Gao Qiu, et al., "Ensemble Learning for Power Systems TTC Prediction with Wind Farms," in IEEE Access, vol. 7, pp. 16572-16583, 2019.
[5] 邱高, 刘友波, 许立雄, 等. 基于深度确定性策略梯度的电网断面极限传输能力动态趋优控制[J/OL]. 中国电机工程学报.
[6] 邱高, 刘俊勇, 刘友波, 等. 风电外送通道极限传输能力的自适应向量机估计[J]. 电工技术学报, 2018, 33(014): 3342-3352.
[7] 刘季昂，邱高*，等. 基于高斯过程的电力系统复杂方式多维指标快速置信评价[J/OL]. 电力系统自动化.
[8] 胥威汀, 刘俊勇, 唐权, 邱高*, 等. 含风电系统断面TTC运行规则的极限学习机提取方法[J]. 电力系统保护与控制, 2018, 46(23): 135-142.
[9] 杨波, 崔红芬, 邱高*, 等. 基于储能系统控制的同步交直流系统稳定性改善方法[J]. 可再生能源, 2020, 38(09): 1252-1257.
[10] Gao Qiu, et al., "Deep Learning Based TTC Predictor for Power Systems with Wind Energy Integration," 2020 IEEE PES Innovative Smart Grid Technologies Europe (ISGT-Europe), The Hague, Netherlands, 2020, pp. 439-443.
[11] Liangzhong Yao, Fubao Wu, Gao Qiu*, et al., "De-risking transient stability of AC/DC power systems based on ESS integration," in The Journal of Engineering, 2019, vol. 2019, no. 16, pp. 1221-1226. (EI)
[12] Jing Ren, Chen Xue, Shuanbao Niu, Xiaowei Ma, Xiaodong Zhang, Gao Qiu*, et al., "A learning-assisted dynamic security enabled operational planning with transferable load," 2021 6th Asia Conference on Power and Electrical Engineering (ACPEE), 2021, pp. 1639-1643.
[13] Youbo Liu, Junbo Zhao, Lixiong Xu, Tingjian Liu, Gao Qiu, et al., "Online TTC Estimation Using Nonparametric Analytics Considering Wind Power Integration," in IEEE Transactions on Power Systems, vol. 34, no. 1, pp. 494-505, Jan. 2019.
[14] Xi Zhang, Youbo Liu, Jiajun Duan, Gao Qiu, et al, "DDPG-based Multi-agent Framework for SVC Tuning in Urban Power Grid with Renewable Energy Resources," in IEEE Transactions on Power Systems, in Press.
[15] Tingjian Liu, Youbo Liu; Junyong Liu; Lingfeng Wang; Lixiong Xu; Gao Qiu, et al., "A Bayesian Learning Based Scheme for Online Dynamic Security Assessment and Preventive Control," in IEEE Transactions on Power Systems, vol. 35, no. 5, pp. 4088-4099, Sept. 2020.
[16] Jiang Liu, Youbo Liu, Gao Qiu, et al., "Deep-Q-Network-Based Intelligent Reschedule for Power System Operational Planning," 2020 12th IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC), Nanjing, China, 2020, pp. 1-6.
[17] Honghao Wu, Junyong Liu, Youbo Liu, Gao Qiu, et al., "Power system transmission line fault diagnosis based on combined data analytics," 2017 IEEE Power & Energy Society General Meeting, Chicago, IL, 2017, pp. 1-5.
[18] 苏童, 刘友波, 沈晓东, 刘挺坚, 邱高, 等. 深度学习驱动的电力系统暂态稳定预防控制进化算法[J].中国电机工程学报,2020,40(12):3813-3824.
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