학술논문

A low cost weather monitoring, PV and prediction system in East Africa
Document Type
Conference
Source
2023 IEEE International Conferences on Internet of Things (iThings) and IEEE Green Computing & Communications (GreenCom) and IEEE Cyber, Physical & Social Computing (CPSCom) and IEEE Smart Data (SmartData) and IEEE Congress on Cybermatics (Cybermatics) ITHINGS-GREENCOM-CPSCOM-SMARTDATA-CYBERMATICS Internet of Things (iThings) and IEEE Green Computing & Communications (GreenCom) and IEEE Cyber, Physical & Social Computing (CPSCom) and IEEE Smart Data (SmartData) and IEEE Congress on Cybermatics (Cybermatics), 2023 IEEE International Conferences. :740-745 Dec, 2023
Subject
Communication, Networking and Broadcast Technologies
Computing and Processing
Signal Processing and Analysis
Temperature sensors
Temperature measurement
Cloud computing
Temperature distribution
Wind speed
Heuristic algorithms
Cameras
weather monitoring
PV prediction
PV monitoring
solar mini-grid
microgrid
Language
ISSN
2836-3701
Abstract
This paper is about the design of a lowcost system to monitor the weather and resulting PV generation for small-midsized microgrids in Africa. The setups are one 12kWp near-grid and 192-panel 76kWp off-grid systems. The weather parameters collected are wind speed, wind direction, temperature, panel temperature, humidity, and rainfall as well as in-plane, horizontal irradiation. Cloud coverage, a major influence of solar generation, is captured by two 100° to 200° view-field cameras per site. Moreover, we compare this precise data with internet data for variation, particularly with large-grid-area satellite data. A wide and ultra-wide capture of cloud images in multiple resolutions for analysis and development of prediction algorithms. Lowresolution images allow for easier transmission over the internet in remote East Africa. A more accurate analysis of the different cloud types and characteristics is enabled with the dynamic range of two set-ups in addition to a comparison of the consistency and accuracy of the various algorithms to be developed. The ultra-low-cost is achieved across weather stations and sky imaging using a Raspberry Pi-based setup. Beneficial redundancies from multiple sensors per site are expected due to the experimental setup nature.