A robust statistical analysis of the role of hydropower on the system electricity price and price volatility
A robust statistical analysis of the role of hydropower on the system electricity price and price volatility
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DOI：
10.1088/2515-7620/ac7b74
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发表时间：
2022-03
影响因子：
2.9
通讯作者：
Olukunle O. Owolabi;K. Lawson;Sanhita Sengupta;Ying Huang;Lan Wang;Chaopeng Shen;Mila Getmansky Sherman;D. Sunter
中科院分区：
文献类型：
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作者：
Olukunle O. Owolabi;K. Lawson;Sanhita Sengupta;Ying Huang;Lan Wang;Chaopeng Shen;Mila Getmansky Sherman;D. Sunter
水力发电(水电)的独特之处在于，它既可以作为传统的电力来源，也可以作为备用蓄水池(抽水蓄能和大型水库蓄水池)，以便在电网需求高的时候提供能源(S.Rehman，L M Al-Hadhrami和M M Alam)，(2015年可再生和可持续能源评论，第44，第586-98页)。本研究考察了2014-2020年间，水电对新英格兰独立系统运营商(ISONE，ISO New England Web Services API v1.1)所服务地区系统电价和价格波动的影响。Https://webservices.iso-ne.com/docs/v1.1/，2021年。接入：2021-01-10)。我们对平均效应和分位数效应以及水电在太阳能和风能资源存在时的边际贡献效应进行了稳健的整体分析。首先，价格数据针对确定性的时间趋势进行了调整，修正了可能掩盖数据中实际代表性趋势的季节性、周末和日间影响。利用多元线性回归和分位数回归，我们观察到水电有助于降低系统电价和价格波动性。虽然平均而言，水电对价格下跌和波动性的影响较小，但在极端分位数(>；70%)上影响更大。在这些较高的百分位数，我们发现，在风能等波动资源存在的情况下，水电对价格波动提供了稳定作用。最后，我们讨论了水电与系统电价和波动性之间的关系。
Hydroelectric power (hydropower) is unique in that it can function as both a conventional source of electricity and as backup storage (pumped hydroelectric storage and large reservoir storage) for providing energy in times of high demand on the grid (S. Rehman, L M Al-Hadhrami, and M M Alam), (2015 Renewable and Sustainable Energy Reviews, 44, 586–98). This study examines the impact of hydropower on system electricity price and price volatility in the region served by the New England Independent System Operator (ISONE) from 2014-2020 (ISONE, ISO New England Web Services API v1.1.” https://webservices.iso-ne.com/docs/v1.1/, 2021. Accessed: 2021-01-10). We perform a robust holistic analysis of the mean and quantile effects, as well as the marginal contributing effects of hydropower in the presence of solar and wind resources. First, the price data is adjusted for deterministic temporal trends, correcting for seasonal, weekend, and diurnal effects that may obscure actual representative trends in the data. Using multiple linear regression and quantile regression, we observe that hydropower contributes to a reduction in the system electricity price and price volatility. While hydropower has a weak impact on decreasing price and volatility at the mean, it has greater impact at extreme quantiles (>70th percentile). At these higher percentiles, we find that hydropower provides a stabilizing effect on price volatility in the presence of volatile resources such as wind. We conclude with a discussion of the observed relationship between hydropower and system electricity price and volatility.