春川气象站光伏板温度和光伏功率分析

J. Jee, Il-Sung Zo, Kyu-Tae Lee, Won-Hak Lee, Sung-Jin Choi
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摘要

本研究对光伏电站运行监测所需的光伏发电功率和光伏面板温度进行了计算和分析。2018年5月1日至8月19日,在春川气象台太阳能发电厂安装了光伏板温度传感器,进行了密集观测。利用实测PV面板温度对计算PV面板温度进行分析时,计算PV面板温度在较高温度下高估了PV面板温度,而在较低温度下高估了PV面板温度;但决定系数(r2)大于等于0.88。使用地面观测资料时,偏差为-0.33°C, RMSE为3.43°C。然而,当使用局部数据同化和预测(LDAPS)模型时,偏差为0.22°C, RMSE为4.27°C。利用地面气象观测资料(韩国气象厅,KMA)、LDAPS模式预测资料(LDAPS)和通信海洋与气象卫星(COMS)资料利用光伏组件温度对春川光伏电站的光伏发电进行了比较。光伏发电的决定系数(r2)以KMA最高(0.91),其次是COMS(0.88)和LDAPS(0.84)。KMA线性回归斜率(1.05)、最小偏差(2.24 kWh)和RMSE (3.38 kWh)与实测值相近。但与LDAPS相比,COMS的线性回归斜率(1.23)最大,偏差(4.77 kWh)和RMSE (6.23 kWh)略高。
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Analysis of Photovoltaic Panel Temperature and Photovoltaic Electric Power at Chuncheon Meteorological Station using Intensive Observation Period Data
In this study, photovoltaic (PV) electricity power and PV panel temperature for operation and monitoring of PV power plant were calculated and analyzed. A PV panel temperature sensor was installed at the Chuncheon Meteorological Observatory solar power plant for intensive observation from May 1 to August 19, 2018. When the calculated PV panel temperature was analyzed using the measured PV panel temperature, the calculated PV panel temperature was overestimated at a higher temperature compared to the measured PV panel temperature, which was overestimated at a lower temperature; however, the determination coefficient (R 2 ) was 0.88 or more. The bias was -0.33°C and RMSE was 3.43°C when the ground observation data were used. However, when the Local Data Assimilation and Prediction (LDAPS) model were used, the bias was 0.22°C and RMSE was 4.27°C. The PV electricity power generation by ground meteorological observation data (Korea Meteorological Administration, KMA), LDAPS model prediction data (LDAPS), and Communication Ocean and Meteorological Satellite (COMS) data using the PV module temperature were compared with those of the Chuncheon PV power plant. The determination coefficient (R 2 ) of PV power generation was the highest for KMA (0.91) followed by COMS (0.88) and LDAPS (0.84). The slope of the linear regression, (1.05) for KMA, and the smallest bias (2.24 kWh) and RMSE (3.38 kWh) were similar to the measured values. However, compared to the LDAPS, the slope (1.23) of the linear regression was the largest in COMS, and the bias (4.77 kWh) and RMSE (6.23 kWh) were slightly higher.
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