权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

STUDY ON HIGH EFFICIENCY OPERATION OF SOLAR GENERATION PLANT USING FUZZY CONTROL WITH ADAPTIVE SCHEME.

采用模糊控制自适应方案的太阳能发电站高效运行研究。

基本信息

批准号：
08650342
负责人：
UEZATO Katsumi
金额：
$ 1.47万
依托单位：
UNIVERSITY OF THE RYUKYUS
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (C)
财政年份：
1996
资助国家：
日本
起止时间：
1996 至 1998
项目状态：
已结题

来源：
https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-08650342/
关键词：
SOLAR GENERATION MAXIMUM POWER POINT TRACKING CONTROL FUZZY NEURAL NETWORK DC DC CHOPPER INSOLATION PARAMETER TUNING 高効率化ファジ-制御ニューラルネット

项目摘要

In this research, fuzzy inference with adaptive scheme is applied to maximum power point tracking control to develop high efficiency solar generating plant, irrespective of operating condition changes and parameter variations of solar generating plant.In 1996, solar energy distribution of Ryukyu Islands were investigated. The optimum setting angle and direction of solar panel to extract maximum power from photovoltaic array for one year were determined.In 1997, laboratory shop-test plant for solar generation, in which control strategy for maximum power point tracking control is implemented with a personal computer, was constructed. The performance of the proposed control strategy was investigated on tracking performance for transient and steady state conditions. The good tracking performance was obtained for both natural and artificial insolation.In 1998, a new maximum power point tracking control strategy with using fuzzy neural network was developed. The parameters of fuzzy control is tuned off-line by intuition and experience of experts. The tuning of fuzzy controller is tedious and difficult task for beginners. The fuzzy neural network can represent the fuzzy controller and tune fuzzy parameters to which a cost function is minimized. The fuzzy parameters of the fuzzy neural network are trained on-line, therefore, good tracking performance is obtained in condition changes, such as solar insolation change, temperature change, and partial shading of photovoltaic array.The all of above mentioned researches was presented in domestic and international conference. Main research result has been accepted for international journal, and the paper will be published near future.

本研究将模糊推理与自适应方案应用于最大功率点跟踪控制中，以开发高效率的太阳能发电厂，而不考虑太阳能发电厂运行工况的变化和参数的变化。1996年，对琉球群岛的太阳能分布进行了调查。确定了太阳能电池板的最佳安装角度和方向，使光伏阵列在一年内获得最大功率。1997年，建立了利用个人计算机实现最大功率点跟踪控制策略的太阳能发电实验室车间试验装置。研究了该控制策略在瞬态和稳态条件下的跟踪性能。对自然日照和人工日照均具有良好的跟踪性能。1998年，提出了一种新的基于模糊神经网络的最大功率点跟踪控制策略。模糊控制的参数是根据专家的直觉和经验离线调整的。模糊控制器的整定对于初学者来说是一项繁琐而困难的工作。模糊神经网络可以表示模糊控制器，并对代价函数最小的模糊参数进行调整。通过在线训练模糊神经网络的模糊参数，对太阳日照变化、温度变化、光伏阵列部分遮阳等条件变化均有良好的跟踪性能。上述研究成果已在国内外学术会议上发表。主要研究成果已被国际期刊录用，论文将于近期发表。