Error analysis and auto correction of hybrid solar tracking system using photo sensors and orientation algorithm Junbin Zhang, Zhuojun Yin, Peng Jin * Peking University, Shenzhen Graduate School, Shenzhen, 518055, China article info Article history: Received 15 October 2018 Received in revised form 20 April 2019 Accepted 3 June 2019 Available online 6 June 2019 Keywords: Dual-axis hybrid solar tracking Solar orientation Installation deviation Error correction Daylight harvesting abstract In order to further improve the efficiency of daylight harvesting system, a high accuracy solar tracking system is required. The tracking error is the combined result of various sources, such as the azimuth rotational axis tilt, geo-positioning deviation, installation deviation, true north meridian deviation, calculation error and mismatch of photo sensors, etc. In this paper, we designed a dual-axis hybrid tracking system which uses GPS/BeiDou for geological location, photodiodes for closed loop tracking, and orientation algorithm for open loop tracking. The difference of our calculated the solar hour angle, altitude angle and azimuth angle to that of SOLPOS results are less than 1  . An initializing calibration is proposed to correct the errors caused by the mismatch of photodiodes. The installation deviation, geo- positioning error and true north meridian deviation for orientation algorithm are also analyzed and corrected. This field test shows that the overall tracking accuracy of the system is improved after the second dynamic compensation. The tracking system can be used in a low cost and small form factor solar tracker with easy setup by providing geological location, orientation sensing and auto corrections for weight and wind load if the photo sensors are positioned at the deflection location. © 2019 Elsevier Ltd. All rights reserved. 1. Introduction Solar energy is the ultimate renewable and clean way to solve the increasing energy demand while reducing the CO 2 emission [1]. Solar energy has been harnessed in various forms such as PV, solar thermal, concentration photovoltaics (CPV) and concentrated solar power (CSP), etc [2]. Solar energy is not constant due to weather and sun movement. However, tracking and concentrating the solar flux can increase efficiency and power output for systems such as CPV, CSP and daylight harvesting system [3e7]. Experiments by Abdallah et al. [8] show that the productivity of a solar still using a solar tracking system is increased by 22% compared with a fixed solar still. Cruz-Perag on et al. [9] also conducted a similar experi- ment on the solar power system, where the power generation of photovoltaic tracking system could increased by 20%. A higher concentration ratio requires a more accurate angular tracking [10, 11]. The reliability and cost of tracking system are the key factors in CPV and CSP markets. In low tracking accuracy application such as a PV panel without concentration, an open loop single axis tracking is sufficient, where the PV panel rotated auto- matically [12, 13]. In order to reach concentration of over 100 suns, the required tracking accuracy is in the range of ±0.5  to ±2  , where dual axis tracking are needed [14]. A cost-effective and precise solar tracking assembly require that tracker be able to withstand the weight of all components and wind loads, and compensate any system or random errors within certain tolerable bounds [15]. Theoretically, high-precision algorithms can accurately calculate the solar position with negligible error [16]. However, various er- rors arise in field application, and reduce the solar tracking accu- racy [17]. The typical errors include the geo-positioning error, installation error, time error, calculation error, mechanical error, atmospheric refraction, weather, gravity bending, self-weight structure deformation, wind load, etc. [15e18]. The geo- positioning error is mainly reflected in the accuracy of obtaining the geological longitude and latitude of location of the tracker. It will directly affect the calculation of the solar position using the solar trajectory tracking algorithm. Installation errors are the most important sources of error in solar tracker, such as azimuth rota- tional axis tilt, dual-axis nonorthogonality, reference position off- sets, azimuth reference bias, elevation reference bias and true north meridian [16, 17]. Atmospheric refraction and rainy weather tend to * Corresponding author. Room E321A, Peking University Shenzhen Graduate School, University Town, Xili, Nanshan District, Shenzhen, 518055, PR China. E-mail addresses: zhangjunbin@pkusz.edu.cn (J. Zhang), 1701213738@sz.pku. edu.cn (Z. Yin), jinpeng@pkusz.edu.cn (P. Jin). Contents lists available at ScienceDirect Energy journal homepage: www.elsevier.com/locate/energy https://doi.org/10.1016/j.energy.2019.06.032 0360-5442/© 2019 Elsevier Ltd. All rights reserved. Energy 182 (2019) 585e593