基于人工智能的变电站倒闸智能防误技术研究与应用OA
Research and Application of Intelligent Anti-Misoperation Technolgy for Substation Switching Operation Based on Artificial Intelligence
针对当前变电站倒闸操作票缺乏有效的防误校核手段、智能化程度较低等问题,结合深度强化学习算法,提出了一种基于知识图谱的变电站倒闸智能防误技术.首先,利用电网设备拓扑、调度防误规程等数据分别构建设备物理实体图谱和防误语义图谱,并自动融合形成调度知识图谱;然后,基于防误算法构建智能防误图谱,自动生成符合防误规程的最优倒闸操作序列,实现智能防误校核;最后,通过算例对知识图谱智能防误的实用性、深度强化学习的性能、智能防误效率等进行分析.结果表明,提出的智能防误方法在提升倒闸智能防误效率和准确性方面具有一定的优势.
In response to the current lack of effective error prevention verification methods and low level of intelligence in operation tickets,a knowledge graph based intelligent error prevention technology for substation switching is proposed by combining deep reinforcement learning algorithms.Firstly,the data such as power grid equipment topology and scheduling error prevention regulations is utilized to constructe a physical entity graph and an error prevention semantic graph of the equipment,and a scheduling knowledge graph is automatically fused to form.Then,based on intelligent error prevention algorithms,a graph of error prevention regulations is constructed to automatically generate the optimal switching operation sequence that complies with the error prevention regulations,and the intelligent error prevention verification is achieved.Finally,the practicality of knowledge graph intelligent error prevention,the performance of deep reinforcement learning,and the efficiency of intelligent error prevention are analyzed through examples.The results show that the proposed method has certain advantages in improving the efficiency and accuracy of intelligent error prevention for switching.
胡新雨;郁海彭;何智;赵缪敏;邢松尧;张进伟
国网江苏省电力有限公司 南通供电分公司,江苏 南通 260001北京电链科技有限公司,北京 100020
动力与电气工程
倒闸操作智能防误深度强化学习知识图谱
switching operationintelligent error preventiondeep reinforcement learningknowledge graph
《电器与能效管理技术》 2024 (006)
70-79 / 10
评论