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The value of improved wind power forecasting: Grid flexibility quantification, ramp capability analysis, and impacts of electricity market operation timescales

机译:改进的风电预测的价值:电网灵活性量化,匝道能力分析以及电力市场运营时间表的影响

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The value of improving wind power fOrecasting accuracy at different electricity market operation time scales was analyzed by simulating the IEEE 118-bus test system as modified to emulate the generation mixes of the Midcontinent, California, and New England independent system operator balancing authority areas. The wind power forecasting improvement methodology and error analysis for the data set were elaborated. Production cost simulation was conducted on the three emulated systems with a total of 480 scenarios considering the impacts of different generation technologies, wind penetration levels, and wind power forecasting improvement timescales. The static operational flexibility of the three systems was compared through the diversity of generation mix, the percentage of must-run base-load generators, as well as the available ramp rate and the minimum generation levels. The dynamic operational flexibility was evaluated by the real-time upward and downward ramp capacity. Simulation results show that the generation resource mix plays a crucial role in evaluating the value of improved wind power forecasting at different timescales. In addition, the changes in annual operational electricity generation costs were mostly influenced by the dominant resource in the system. Finally, the impacts of pumped-storage resources, generation ramp rates, and system minimum generation level requirements on the value of improved wind power forecasting were also analyzed. Published by Elsevier Ltd.
机译:通过仿真IEEE 118总线测试系统,对改进的风电预测精度在不同电力市场运行时间尺度上的价值进行了分析,该系统经过修改以模拟加利福尼亚州中部大陆和新英格兰独立系统运营商平衡授权区域的发电混合。阐述了风能预报改进方法和数据集的误差分析。在三种模拟系统上进行了生产成本模拟,总共有480种方案,其中考虑了不同发电技术,风力渗透水平以及风力发电预测改进时间表的影响。通过发电机组的多样性,必须运行的基本负荷发电机的百分比以及可用的斜坡率和最小发电机组级别,比较了这三个系统的静态运行灵活性。动态的操作灵活性通过实时的向上和向下斜坡容量进行评估。仿真结果表明,发电资源组合在评估不同时间尺度的风电预测值方面起着至关重要的作用。此外,年度运营发电成本的变化主要受系统中主要资源的影响。最后,还分析了抽水蓄能,发电斜率和系统最低发电水平要求对改进的风电功率预测值的影响。由Elsevier Ltd.发布

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