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A Sensitivity Analysis of Short-Term Hydropower Planning Using Stochastic Programming

机译:使用随机编程的短期水电规划敏感性分析

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Huge amount of uncertainties are being introduced to the power market because of the ongoing growth in the renewable energy sources like wind and solar power. The intermittent nature of these power sources increases the volatility of the day-ahead market prices. Therefore, improving planning tools and constructing an optimal bidding strategy to the day-ahead market is an essential task for the price-taker hydropower producer. This paper applies an optimal bidding model under the uncertainties of the day-ahead market prices and the water inflow level. Specifically, the model is built using a two-stage stochastic mixed integer linear programming approach. The uncertainties are handled by generating scenarios based on historical data. The model is tested by studying three reservoir test system. Profound sensitivity analysis is provided, in terms of volatility in day-ahead market prices and water inflow level as well as in terms of water opportunity cost and initial volume of the reservoir. Based on the comparison of the stochastic and corresponding deterministic problems, the result aims to show the impact of modeling the uncertainties explicitly.
机译:由于风和太阳能等可再生能源正在进行的持续增长,正在向电力市场引入大量的不确定性。这些电源的间歇性质增加了日前市场价格的波动。因此,改善规划工具和为日前市场构建最佳招标策略是价格 - 接受水电生产商的重要任务。本文采用了最佳市场价格和水流入水平的不确定性下的最佳竞标模型。具体地,使用两级随机混合整数线性编程方法构建模型。通过基于历史数据生成方案来处理不确定性。该模型通过研究三个储层测试系统来测试。在日落市场价格和水流入水平的波动方面提供深刻的敏感性分析,以及水库的水机会成本和初始体积。基于随机和相应的确定性问题的比较,结果旨在显式建模不确定性的影响。

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