Towards a Data-Driven Symbiosis of Agriculture and Photovoltaics

被引：2

作者：

Wang, Mingxin ^{[1
]}

Zhang, Yiqiang ^{[1
]}

Sun, Carter ^{[2
]}

Li, Wei ^{[3
]}

Zomaya, Albert Y. ^{[3
]}

Sun, Yaojie ^{[1
]}

机构：

[1] Fudan Univ, Dept Illuminating Engn & Light Sources, Shanghai, Peoples R China

[2] Univ Sydney, Sch Elect & Informat Engn, Sydney, NSW, Australia

[3] Univ Sydney, Ctr Distributed & High Performance Comp, Sch Comp Sci, Sydney, NSW, Australia

来源：

2019 INTERNATIONAL CONFERENCE ON INTERNET OF THINGS (ITHINGS) AND IEEE GREEN COMPUTING AND COMMUNICATIONS (GREENCOM) AND IEEE CYBER, PHYSICAL AND SOCIAL COMPUTING (CPSCOM) AND IEEE SMART DATA (SMARTDATA) | 2019年

基金：

中国国家自然科学基金;

关键词：

photovoltaics; agriculture; optimization; uniformity; PARTIAL SHADE;

D O I：

10.1109/iThings/GreenCom/CPSCom/SmartData.2019.00161

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

The naive combination of agriculture and photovoltaics could have several adverse effects with varying severity, such as affecting the daylighting of both, which is not conducive to crop growth as well as energy generation efficiency. In addition, the integration of these two separate but interrelated systems introduces a large number of new elements, so that it imposes great technical challenges to optimize system performance by means of traditional approaches. Thanks to recent developments in Internet of Things and Big Data analytics, they can provide the tools to better understand the features of each subsystem and to reveal the intrinsic link between agriculture and photovoltaics. Based on factors, such as, plant characteristics, this paper overviews a mechanism used to optimize the use of photovoltaics in agriculture to create more balanced strategies that allows for the use of land for both crop and energy production.

引用

页码：903 / 908

页数：6

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