摘要翻译：
本文提出了一种时间分解策略来降低电力系统多区间运行问题的计算复杂度。我们重点研究了经济调度问题。将所考虑的调度层分解为多个较小的子层。每个子层的第一时间间隔被建模为两个连续子层之间的耦合间隔。各子层之间的相互依赖关系用发电机组的斜坡率进行数学建模。提出了一种基于辅助问题原理的分布式协调策略，对各子层的经济调度方案进行协调，以求得整个运行层的最优解。我们还提出了一种初始化技术，从一个足够好的点开始迭代协调算法。该技术显著提高了收敛速度。将该算法应用于IEEE118节点系统的一周前经济调度问题，取得了良好的效果。
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英文标题：
《A Time Decomposition and Coordination Strategy for Power System
  Multi-Interval Operation》
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作者：
Farnaz Safdarian, Okan Ciftci, Amin Kargarian
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最新提交年份：
2018
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分类信息：

一级分类：Electrical Engineering and Systems Science        电气工程与系统科学
二级分类：Signal Processing        信号处理
分类描述：Theory, algorithms, performance analysis and applications of signal and data analysis, including physical modeling, processing, detection and parameter estimation, learning, mining, retrieval, and information extraction. The term "signal" includes speech, audio, sonar, radar, geophysical, physiological, (bio-) medical, image, video, and multimodal natural and man-made signals, including communication signals and data. Topics of interest include: statistical signal processing, spectral estimation and system identification; filter design, adaptive filtering / stochastic learning; (compressive) sampling, sensing, and transform-domain methods including fast algorithms; signal processing for machine learning and machine learning for signal processing applications; in-network and graph signal processing; convex and nonconvex optimization methods for signal processing applications; radar, sonar, and sensor array beamforming and direction finding; communications signal processing; low power, multi-core and system-on-chip signal processing; sensing, communication, analysis and optimization for cyber-physical systems such as power grids and the Internet of Things.
信号和数据分析的理论、算法、性能分析和应用，包括物理建模、处理、检测和参数估计、学习、挖掘、检索和信息提取。“信号”一词包括语音、音频、声纳、雷达、地球物理、生理、（生物）医学、图像、视频和多模态自然和人为信号，包括通信信号和数据。感兴趣的主题包括：统计信号处理、谱估计和系统辨识；滤波器设计；自适应滤波/随机学习；（压缩）采样、传感和变换域方法，包括快速算法；用于机器学习的信号处理和用于信号处理应用的机器学习；网络与图形信号处理；信号处理中的凸和非凸优化方法；雷达、声纳和传感器阵列波束形成和测向；通信信号处理；低功耗、多核、片上系统信号处理；信息物理系统的传感、通信、分析和优化，如电网和物联网。
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英文摘要：
  This paper presents a time decomposition strategy to reduce the computational complexity of power system multi-interval operation problems. We focus on the economic dispatch problem. The considered scheduling horizon is decomposed into multiple smaller sub-horizons. The first time interval of each sub-horizon is modeled as the coupling interval between two consecutive sub-horizons. The interdependencies between the sub-horizons are mathematically modeled using ramp rates of generating units. A distributed coordination strategy, which is based on auxiliary problem principle, is developed to coordinate the economic dispatch solutions of the sub-horizons to find an optimal solution for the whole operation horizon. We also propose an initializing technique to start the iterative coordination algorithm from a good-enough point. This technique enhances the convergence rate significantly. The proposed algorithm is deployed to solve a week-ahead economic dispatch problem on the IEEE 118-bus system, and promising results are obtained.
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PDF链接：
https://arxiv.org/pdf/1805.10185