By Marla Keene, technology writer,AX Control
根据美国能源信息管理，前三大生产国家的公用尺度太阳能光伏产能increased by 10.8 GW在过去三年中。虽然预计这一指数增长将继续，但它遇到需要解决的挑战，包括如何检查太阳能领域并维持最佳输出。
Luckily, there are a number of technologies on the horizon that will aid in that challenge. And like the cost of PV equipment, the costs associated with these technologies are dropping with time. This includes increased use of drones, RGB imagery, artificial intelligence, as well as the incorporation of 5G networks as they become available across the country.
The use of drones for solar field inspection has been rapidly increasing over the last few years. Traditional assessments using field engineers and hand-held cameras is time-consuming and possibly hazardous work, and can lead to missed opportunities due to human error. Semi-autonomous drones can provide the same data while offering significant advantages over this older inspection method, including:
- An increase in efficiency.无人机can document anomalies over large areas with a single flight; for example,senseFly’s eBee X可以在一个42米的飞行中映射161英亩。可以在一个航班上在一个航班上识别出地理准确数字模型的故意破坏，模块故障和细胞和二极管的问题，然后工程师可以使用来定位和纠正问题。
- 改进了数据。Data collection is streamlined and connected to GPS or mapping software for accuracy. Because drones map entire sections at one time using GPS coordinates, gaps in data collection are limited or eliminated.
- Less hazardous.更快的检查较少的人数小时意味着不太接近元素，对动物和其他潜在的危险。
- Better reporting.大多数无人机应用程序将作为打击列表，空中检查或现场修复报告提供无人机数据，可以将智能手机应用程序或直接转向现场计算机。
When drone technology is combined with artificial intelligence, data can be manipulated in interesting ways. For example, AI can use the combination of RGB and thermal data from an inspection to match up scans and then computationally remove obstructions (such as overgrowths of vegetation) and review the surface underneath — like say, a panel edge. Thistype of optical sectioningmay have further ramifications to inspection by offering a more complete view through vegetation to the ground below and between panel rows.
AI can also be used to forecast problems before they occur by using contextual information from your data. Take the example of erosion from before. AI algorithms can be trained to recognize the relative ground elevation and slope orientations around your solar field; when areas deviate from these norms, they can be flagged as premature erosion points, leading to action far sooner than would have otherwise been possible.
- Daily meteorological surveys.
Additionally, autonomous navigation requires a system that can sense its surroundings and respond in a quick and highly intelligent nature. 5G networks will be part of this capability by driving ultra-low latency between the drone and its positioning directives, allowing drones to make the jump from semi-autonomous to independent.
Start by asking the right questions. Where have you traditionally needed better inspection? How can technology potentially cut down on operating costs? What part of new technology adoption should be brought in-house, and what can be outsourced? What preliminary steps need to be taken now, and what needs to be implemented next year, or the year after? The answers to these questions will help guide the timing of your actions.
技术作家玛丽克恩队的作品AX Control, an industrial automation parts supplier located in North Carolina. She writes about AR/VR, drones, green tech, artificial intelligence and how technology is changing our world. Her articles have been featured in电力杂志，明天的机器人在其他行业网站上。在为AX控制工作之前，Marla花了12年的运行自己的小企业。