基于抽水能源利用的效益优化方法 存储单元与动态定价

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摘要翻译：
本研究提出了一个优化问题，以获得最大经济效益的可变和间歇发电量的前一日和平衡电力市场的风电场。该方法基于抽水蓄能机组和风电场的联合使用，利用市场价格的变化增加了电厂的利润，同时通过提供电厂所连接系统的一部分高峰负荷需求来支持电力系统。为了检验所提方法的有效性，利用实际风量和价格数据进行了详细的模拟研究，并将结果与未使用存储单元和/或未应用所提基于价格的能量管理方法的各种情况下的结果进行了比较。结果表明，抽水蓄能机组是一种能够有效地用于高功率水平的蓄能系统，所提出的优化问题在实现这些系统的成本效益方面是相当成功的。
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英文标题：
《A Profit Optimization Approach Based on the Use of Pumped-Hydro Energy
  Storage Unit and Dynamic Pricing》
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作者：
Ak{\i}n Ta\c{s}cikarao\u{g}lu, Ozan Erdin\c{c}
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最新提交年份：
2018
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分类信息：

一级分类：Economics        经济学
二级分类：Econometrics        计量经济学
分类描述：Econometric Theory, Micro-Econometrics, Macro-Econometrics, Empirical Content of Economic Relations discovered via New Methods, Methodological Aspects of the Application of Statistical Inference to Economic Data.
计量经济学理论，微观计量经济学，宏观计量经济学，通过新方法发现的经济关系的实证内容，统计推论应用于经济数据的方法论方面。
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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：
  In this study, an optimization problem is proposed in order to obtain the maximum economic benefit from wind farms with variable and intermittent energy generation in the day ahead and balancing electricity markets. This method, which is based on the use of pumped-hydro energy storage unit and wind farm together, increases the profit from the power plant by taking advantage of the price changes in the markets and at the same time supports the power system by supplying a portion of the peak load demand in the system to which the plant is connected. With the objective of examining the effectiveness of the proposed method, detailed simulation studies are carried out by making use of actual wind and price data, and the results are compared to those obtained for the various cases in which the storage unit is not available and/or the proposed price-based energy management method is not applied. As a consequence, it is demonstrated that the pumped-hydro energy storage units are the storage systems capable of being used effectively for high-power levels and that the proposed optimization problem is quite successful in the cost-effective implementation of these systems.
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PDF链接：
https://arxiv.org/pdf/1806.05211

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关键词：存储单元 结果 proposed systems power