期刊论文 [1] Runjia Sun, Yutian Liu. Hybrid reinforcement learning for power transmission network self-healing considering wind power[J], IEEE Transactions on Neural Networks and Learning Systems, 2023, 34(9): 6405 - 6415. [2] Runjia Sun, Yutian Liu, Liang Wang. An online generator start-up algorithm for transmission system self-healing based on MCTS and sparse autoencoder[J], IEEE Transactions on Power Systems, 2019, 34(3): 2061-2070. [3] Runjia Sun, Yutian Liu, Hainan Zhu, et. al. A network reconfiguration approach for power system restoration based on preference-based multiobjective optimization[J], Applied Soft Computing, 2019, 83: 105656. [4] 孙润稼, 刘玉田. 基于深度学习和蒙特卡洛树搜索的机组恢复在线决策[J], 电力系统自动化, 2018, 42(14): 40-47 [5] Rizwan ul Hassan, Runjia Sun, Yutian Liu. Online static security assessment for cascading failure using stacked de-noising auto-encoder[J], International Journal of Electrical Power & Energy Systems , 2022, 137: 107852. [6] Rui Fan, Runjia Sun, Yutian Liu, et. al. Adaptive power load restoration considering flexible control of air conditioners for resilience enhancement[J]. International Journal of Electrical Power & Energy Systems, 2023, 148: 108959 . [7] Rui Fan, Runjia Sun, Yutian Liu, el. al. An online decision-making method based on multi-agent interaction for coordinated load restoration[J]. Frontiers in Energy Research, 2022, 10: 992996. [8] 范睿, 孙润稼, 刘玉田. 考虑空调负荷需求响应的负荷恢复量削减方法[J]. 电工技术学报, 2022, 37(11): 2869-2877. [9] 刘天浩, 朱元振, 孙润稼, 刘玉田. 极端自然灾害下电力信息物理系统韧性增强策略[J],电力系统自动化, 2021, 45(03): 40-48. [10]孙润稼, 朱海南, 刘玉田. 基于偏好多目标优化和遗传算法的输电网架重构[J], 山东大学学报(工学版), 2019, 49(05): 17-23. [11]刘玉田, 孙润稼, 王洪涛, 顾雪平. 人工智能在电力系统恢复中的应用综述[J], 山东大学学报(工学版), 2019, 49(05): 1-8. 发明专利 [1] Yutian Liu, Runjia Sun. Method and system for online decision making of generator start-up[P], 2018-9-29, 美国、欧盟 [2] 孙润稼, 刘玉田, 范睿. 一种极端天气下电网自适应负荷恢复方法及系统[P]. 中国: ZL 2021 11 580104.0, 2022-10-04. [3] 刘玉田, 孙润稼, 范睿. 自然灾害下电网应急抢修与恢复调度协同决策方法及系统[P]. 中国: ZL 2022 1 0000490.X, 2022-04-08. [4] 刘玉田, 孙润稼. 一种机组恢复在线动态决策方法及系统 [P]. 中国: ZL 2018 1 0271593.3, 20191018. 科研奖励 [1] 应对极端天气的大型城市电网安全防御与智能恢复关键技术及应用,山东电力科学技术进步奖,5/12,2023年度 |