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The Costs of Electricity Systems with a High Share of Fluctuating Renewables: A Stochastic Investment and Dispatch Optimization Model for Europe

机译:具有高度波动可再生能源的电力系统的成本:欧洲的随机投资和派遣优化模型

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摘要

Renewable energies are meant to produce a large share of the future electricity demand. However, the availability of wind and solar power depends on local weather conditions and therefore weather characteristics must be considered when optimizing the future electricity mix. In this article we analyze the impact of the stochastic availability of wind and solar energy on the cost-minimal power plant mix and the related total system costs. To determine optimal conventional, renewable and storage capacities for different shares of renewables, we apply a stochastic investment and dispatch optimization model to the European electricity market. The model considers stochastic feed-in structures and full load hours of wind and solar technologies and different correlations between regions and technologies. Key findings include the overestimation of fluctuating renewables and underestimation of total system costs compared to deterministic investment and dispatch models. Furthermore, solar technologies are - relative to wind turbines - underestimated when neglecting negative correlations between wind speeds and solar radiation.
机译:可再生能源将产生未来电力需求的很大一部分。但是,风能和太阳能的可用性取决于当地的天气状况,因此在优化未来的电力结构时必须考虑天气特征。在本文中,我们分析了风能和太阳能的随机可用性对成本最小的电厂组合以及相关的总系统成本的影响。为了确定不同份额的可再生能源的最佳常规,可再生能源和存储容量,我们将随机投资和调度优化模型应用于欧洲电力市场。该模型考虑了风力和太阳能技术的随机馈入结构和满负荷工时,以及区域和技术之间的不同关联。与确定性投资和调度模型相比,主要发现包括对可再生能源波动的高估和对系统总成本的低估。此外,相对于风力涡轮机,当忽略风速和太阳辐射之间的负相关性时,太阳能技术被低估了。

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