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Endogenous Assessment of the Capacity Value of Solar PV in Generation Investment Planning Studies

机译:发电投资规划研究中对太阳能光伏发电容量价值的内生评估

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There exist several different reliability- and approximation-based methods to determine the contribution of solar resources toward resource adequacy. However, most of these approaches require knowing in advance the installed capacities of both conventional and solar generators. This is a complication since generator capacities are actually decision variables in capacity planning studies. In this paper, we study the effect of time resolution and solar PV penetration using a planning model that accounts for the full distribution of generator outages and solar resource variability. We also describe a modification of a standard deterministic planning model that enforces a resource adequacy target through a reserve margin constraint. Our numerical experiments show that at least 50 days worth of data are necessary to approximate the results of the full-resolution model with a maximum error of 2.5% on costs and capacity. We also show that the amount of displaced capacity of conventional generation decreases rapidly as the penetration of solar PV increases. We find that using an exogenously defined and constant capacity value based on time-series data can yield relatively accurate results for small penetration levels. For higher penetration levels, the modified deterministic planning model better captures avoided costs and the decreasing value of solar PV.
机译:存在几种不同的基于可靠性和近似的方法来确定太阳能对资源充足性的贡献。但是,大多数这些方法都需要事先了解常规发电机和太阳能发电机的安装容量。这很复杂,因为发电机容量实际上是容量规划研究中的决策变量。在本文中,我们使用规划模型研究时间分辨率和太阳能光伏渗透的影响,该规划模型考虑了发电机故障和太阳能资源变化的全部分布。我们还描述了对标准确定性计划模型的修改,该模型通过储备保证金约束来强制实施资源充足性目标。我们的数值实验表明,至少大约需要50天的数据来近似全分辨率模型的结果,而成本和容量的最大误差为2.5%。我们还表明,随着太阳能PV渗透率的提高,常规发电的置换能力迅速下降。我们发现,使用基于时间序列数据的外生定义的恒定容量值可以针对较小的渗透水平产生相对准确的结果。对于更高的渗透水平,修改后的确定性计划模型可以更好地捕获避免的成本和太阳能光伏价值的下降。

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