摘要
随着电力系统规模不断扩大和结构日益复杂，传统调度方式难以满足现代电力系统的高效、稳定运行需求，智能化调度成为解决这一问题的关键。本研究旨在构建适应现代电力系统的智能化调度策略，以提高电力系统的运行效率和稳定性。为此，提出了一种基于大数据分析与人工智能算法相结合的智能调度框架，该框架能够实时获取并处理海量电力数据，通过深度学习模型预测负荷变化趋势，利用强化学习优化调度决策过程。研究结果表明，所提出的智能调度策略可有效降低电网损耗约15%，提高发电设备利用率20%以上，显著改善了电力系统的经济性和可靠性。此外，创新性地引入了多源异构数据融合技术，实现了对不同类型电力数据的综合处理，为精准调度提供了可靠依据。同时，开发了可视化监控平台，使调度人员能够直观掌握系统运行状态，增强了调度决策的科学性和及时性，为实现电力系统的智能化转型提供了理论支持和技术保障。
关键词：智能化调度；大数据分析；人工智能算法；多源异构数据融合；可视化监控平台
Abstract
As the scale and complexity of power systems continue to expand, traditional dispatch methods are increasingly unable to meet the demands for efficient and stable operation in modern power systems, making intelligent dispatch a critical solution to this challenge. This study aims to develop an intelligent dispatch strategy tailored for modern power systems to enhance operational efficiency and stability. To achieve this, an intelligent dispatch fr amework combining big data analytics with artificial intelligence algorithms is proposed. This fr amework can acquire and process massive amounts of power data in real-time, predict load variation trends using deep learning models, and optimize the dispatch decision-making process through reinforcement learning. The research findings indicate that the proposed intelligent dispatch strategy effectively reduces grid losses by approximately 15% and increases the utilization rate of power generation equipment by over 20%, significantly improving the economic efficiency and reliability of power systems. Additionally, the innovative integration of multi-source heterogeneous data fusion technology enables comprehensive processing of different types of power data, providing a reliable basis for precise dispatch. Furthermore, a visualization monitoring platform has been developed, allowing dispatch personnel to intuitively grasp system operating conditions, thereby enhancing the scientific rigor and timeliness of dispatch decisions and offering theoretical support and technical assurance for the intelligent transformation of power systems.
Keywords：Intelligent Scheduling; Big Data Analysis; Artificial Intelligence Algorithms; Multi-source Heterogeneous Data Fusion; Visual Monitoring Platform
目 录
摘要 I
Abstract II
一、绪论 1
(一) 电力系统智能化调度的背景与意义 1
(二) 国内外研究现状综述 1
(三) 研究方法与技术路线 2
二、智能化调度的关键技术 2
(一) 数据采集与监控系统 2
(二) 高级分析算法应用 3
(三) 实时决策支持系统 3
(四) 智能优化调度模型 4
三、智能化调度策略设计 4
(一) 负荷预测与需求响应 4
(二) 发电侧智能调度策略 5
(三) 输配电网络优化配置 5
(四) 应急调度预案制定 6
四、智能化调度实施效果评估 7
(一) 系统运行效率评价 7
(二) 经济效益分析 7
(三) 环境影响评估 8
(四) 用户满意度调查 9
结 论 10
参考文献 11
随着电力系统规模不断扩大和结构日益复杂，传统调度方式难以满足现代电力系统的高效、稳定运行需求，智能化调度成为解决这一问题的关键。本研究旨在构建适应现代电力系统的智能化调度策略，以提高电力系统的运行效率和稳定性。为此，提出了一种基于大数据分析与人工智能算法相结合的智能调度框架，该框架能够实时获取并处理海量电力数据，通过深度学习模型预测负荷变化趋势，利用强化学习优化调度决策过程。研究结果表明，所提出的智能调度策略可有效降低电网损耗约15%，提高发电设备利用率20%以上，显著改善了电力系统的经济性和可靠性。此外，创新性地引入了多源异构数据融合技术，实现了对不同类型电力数据的综合处理，为精准调度提供了可靠依据。同时，开发了可视化监控平台，使调度人员能够直观掌握系统运行状态，增强了调度决策的科学性和及时性，为实现电力系统的智能化转型提供了理论支持和技术保障。
关键词：智能化调度；大数据分析；人工智能算法；多源异构数据融合；可视化监控平台
Abstract
As the scale and complexity of power systems continue to expand, traditional dispatch methods are increasingly unable to meet the demands for efficient and stable operation in modern power systems, making intelligent dispatch a critical solution to this challenge. This study aims to develop an intelligent dispatch strategy tailored for modern power systems to enhance operational efficiency and stability. To achieve this, an intelligent dispatch fr amework combining big data analytics with artificial intelligence algorithms is proposed. This fr amework can acquire and process massive amounts of power data in real-time, predict load variation trends using deep learning models, and optimize the dispatch decision-making process through reinforcement learning. The research findings indicate that the proposed intelligent dispatch strategy effectively reduces grid losses by approximately 15% and increases the utilization rate of power generation equipment by over 20%, significantly improving the economic efficiency and reliability of power systems. Additionally, the innovative integration of multi-source heterogeneous data fusion technology enables comprehensive processing of different types of power data, providing a reliable basis for precise dispatch. Furthermore, a visualization monitoring platform has been developed, allowing dispatch personnel to intuitively grasp system operating conditions, thereby enhancing the scientific rigor and timeliness of dispatch decisions and offering theoretical support and technical assurance for the intelligent transformation of power systems.
Keywords：Intelligent Scheduling; Big Data Analysis; Artificial Intelligence Algorithms; Multi-source Heterogeneous Data Fusion; Visual Monitoring Platform
目 录
摘要 I
Abstract II
一、绪论 1
(一) 电力系统智能化调度的背景与意义 1
(二) 国内外研究现状综述 1
(三) 研究方法与技术路线 2
二、智能化调度的关键技术 2
(一) 数据采集与监控系统 2
(二) 高级分析算法应用 3
(三) 实时决策支持系统 3
(四) 智能优化调度模型 4
三、智能化调度策略设计 4
(一) 负荷预测与需求响应 4
(二) 发电侧智能调度策略 5
(三) 输配电网络优化配置 5
(四) 应急调度预案制定 6
四、智能化调度实施效果评估 7
(一) 系统运行效率评价 7
(二) 经济效益分析 7
(三) 环境影响评估 8
(四) 用户满意度调查 9
结 论 10
参考文献 11
