摘要翻译：
随着屋顶太阳能光伏的普及和零能耗家庭概念的兴起，需要在智能控制器的性能、成本效益和微电网系统的整体复杂性之间取得平衡，以管理小尺寸和大尺寸微电网的双向潮流。本文提出了可再生能源供电微电网系统中有效管理潮流和实现调峰的解决方案。本文详细介绍了一种利用先进的计量和智能控制单元实现调峰和高效潮流管理的光伏源馈电微电网系统的设计和仿真。该系统通过自动减除负荷，使微电网在高峰时段的耗电量保持在限制范围内。在微电网的并网模式下，系统在较低的负载需求时将多余的电力馈送给公用事业电网，在高需求时段，当光伏发电不足以满足负载需求时，从电网中提取电力赤字。该系统具有良好的潮流管理性能，并能与除光伏以外的分布式电源一起运行。
---
英文标题：
《Efficient Power Flow Management and Peak Shaving in a Microgrid-PV
  System》
---
作者：
Sakshi Mishra, Praveen Palanisamy
---
最新提交年份：
2018
---
分类信息：

一级分类：Computer Science        计算机科学
二级分类：Systems and Control        系统与控制
分类描述：cs.SY is an alias for eess.SY. This section includes theoretical and experimental research covering all facets of automatic control systems. The section is focused on methods of control system analysis and design using tools of modeling, simulation and optimization. Specific areas of research include nonlinear, distributed, adaptive, stochastic and robust control in addition to hybrid and discrete event systems. Application areas include automotive and aerospace control systems, network control, biological systems, multiagent and cooperative control, robotics, reinforcement learning, sensor networks, control of cyber-physical and energy-related systems, and control of computing systems.
cs.sy是eess.sy的别名。本部分包括理论和实验研究，涵盖了自动控制系统的各个方面。本节主要介绍利用建模、仿真和优化工具进行控制系统分析和设计的方法。具体研究领域包括非线性、分布式、自适应、随机和鲁棒控制，以及混合和离散事件系统。应用领域包括汽车和航空航天控制系统、网络控制、生物系统、多智能体和协作控制、机器人学、强化学习、传感器网络、信息物理和能源相关系统的控制以及计算系统的控制。
--
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。
--

---
英文摘要：
  With the increasing penetration of the roof-top solar PV and the rising interest in net-zero energy homes concept, there is a need of balancing the performance of intelligent controllers, their cost-effectiveness and over-all sophistication of the microgrid systems in order to manage the bi-directional power flow in the small as well as large size microgrids. This paper proposes solutions to efficiently manage power flow and to achieve peak shaving in a renewable-source fed microgrid system. The paper details the design and simulation of a photovoltaic source fed microgrid system that achieves peak shaving and efficient power flow management using advanced metering and a smart control unit. The proposed system enables microgrid to maintain the power consumption within limits during peak hours by shedding luxurious loads automatically. Under the grid-connected mode of the microgrid, the system feeds the excess power available to the utility grid during lower load requirements and withdraws the power deficit from the grid during high demand hours when photovoltaic power generation is not sufficient to fulfill the load requirement. The proposed system exhibits desirable power flow management performance and is capable of functioning with distributed generation sources other than PV.
---
PDF链接：
https://arxiv.org/pdf/1807.0718