Li X.,Zhejiang University |
Li X.,Zhejiang SUPCON Solar Technology Co. |
Zhao X.,China Power Engineering Consulting Group Corporation |
Li J.,Zhejiang SUPCON Solar Technology Co. |
And 3 more authors.
Dianli Xitong Zidonghua/Automation of Electric Power Systems | Year: 2015
Tower solar thermal power (STP) is one of the most promising techniques of renewable energy in the world, but its development has slowed down because of its high cost. A life-cycle calculation model is built to predict the levelized cost of electricity (LCOE) of tower STP plants in China, and the integrating factors, including construction cost, the electricity generation and the operation & maintenance costs, are considered one by one. This study focuses on the downward-trend of heliostats cost caused by various motivations, through a method of decomposition of the manufacturing costs into material, manufacturing and transport cost. The study shows that the LCOE is declined by the development of the motivations of production capacity, installed capacity and technical matter, and the installed capacity makes the most significant effect. ©2015 State Grid Electric Power Research Institute Press
Li D.,Zhejiang University |
Mi X.,Zhejiang Supcon Solar Technology Co. |
Huang W.,Zhejiang University |
Zhang P.,Zhejiang University |
Tian J.,Zhejiang Supcon Solar Technology Co.
Taiyangneng Xuebao/Acta Energiae Solaris Sinica | Year: 2015
A method of cloud image recognition and motion detection is proposed to dynamically forecast the impact on solar tower power generation caused by cloud movement. It firstly utilizes Wiener filtering in wavelet domain to process sky images collected by industrial camera, and then identifies clouds in these images by edge detection algorithm based on Lab space. After that, it calculates the velocity and direction of moving clouds using CSIFT feature points, and finally analyzes and forecasts the impact on system thermal power generation through the positional relationship of the clouds, the sun and the heliostat field. The experimental results showed that this method meets the requirement of timeliness and accuracy, thus is useful in engineering applications. © 2015, Science Press. All right reserved.
Zhu X.,Nanjing Normal University |
Mi X.,Zhejiang Supcon Solar Technology Co. |
Lin K.,Zhejiang Supcon Solar Technology Co. |
Huang W.,Zhejiang University
26th Chinese Control and Decision Conference, CCDC 2014 | Year: 2014
Solar tower power plant is the widest market prospect type in large-scale solar power plants during the next decades. Heliostats are the most important components in this system. To solve the problems in the sun-tracking, concentrating control and low dynamic precision of the heliostat clusters system, the nonlinear kinematical model of a heliostat is developed based on analysis of the two-axis rotation sun-tracking mechanism and property. The motion trajectory information of a single heliostat is sampled by using a sun's image reference system combined with machine vision-based method. Nonlinear optimization is proposed to get the best sun's image fitting to achieve the heliostat model parameters automatic intelligent calibration, which overcome the sun-tracking and concentrating precision drift caused by mechanical wears of the heliostat, the environmental and seasonal variations and achieve the high focusing rate and high efficiency of the energy collecting of the large-scale heliostat clusters. The effectiveness of proposed modeling, calibration, and control theory of heliostats are verified through theoretical simulation and experimental researches. © 2014 IEEE.
Shuiliang Z.,Nanjing Normal University |
Weijie D.,Nanjing Normal University |
Xuemei Z.,Nanjing Normal University |
Jun T.,Zhejiang Supcon Solar Technology Co.
Proceedings of the 28th Chinese Control and Decision Conference, CCDC 2016 | Year: 2016
To estimate the clouds covering in solar power tower, a new method based on particle filter tracking algorithm is proposed in this paper. When large clouds move above the heliostat field, it can be predicted by judging whether the clouds cover the sun. Firstly, a wide-angle camera is used to shoot the sky. Then, the particle filter is employed to track the sun and set up the color histograms of the sun. At last, by measuring the similarity of histograms, it can be estimated whether clouds covering occurs. Illustrated by experimental results, the method can judge clouds covering accurately. © 2016 IEEE.