School of Economics and Management, Hebei University of Science and Technology, Shijiazhuang, Hebei, China.
Faculty of Automation Engineering, Huaiyin Institute of Technology, Huai'an, 223003, China.
Environ Sci Pollut Res Int. 2022 Jun;29(29):43690-43709. doi: 10.1007/s11356-022-19902-8. Epub 2022 Apr 18.
Energy is the source of economic growth, and energy consumption indicates the country's state of development. Energy engineering is a relatively new technical discipline. It is increasingly considered as a significant step in meeting carbon reduction targets, which can produce a variety of appealing outcomes that are useful to humanity's evolution. Many countries have adopted national policies to decrease pollution by reducing fossil fuel use and increasing renewable energy usage by alleviating climate change (wind and solar, etc.). The ever-growing need for renewable sources has led to economic and technological problems, such as wind energy, essential for effective grid control, and the design of a wind project. Precise estimates offer network operators and power system designers vital information for the generation of an appropriate wind turbine and controlling demand and supply power. This work provides an in-depth study of the proliferation of artificial intelligence (AI) in the prediction of wind energy generation. The devices employed to calculate wind speed are examined and discussed, with a focus on studies recently published. This review's findings show that AI is being employed in power wind energy measurement and forecasts. When compared to individual systems, the hybrid AI system gives more accurate findings. The discussion also found that correct handling and calibration of the anemometer can increase predicting accuracy. This conclusion suggests that increasing the accuracy of wind forecasting can be accomplished by lowering equipment errors that measure the meteorological parameter and mitigate carbon emission.
能源是经济增长的源泉，能源消耗反映了国家的发展状况。能源工程是一个相对较新的技术学科。它越来越被认为是实现碳减排目标的重要一步，可以产生各种对人类进化有益的有吸引力的结果。许多国家已经采取了国家政策，通过减少化石燃料的使用和增加可再生能源的使用来减轻气候变化（风能和太阳能等）的影响，从而减少污染。对可再生能源的需求不断增长，导致了经济和技术问题，例如风能，这对于有效的电网控制和风力项目的设计至关重要。精确的估计为网络运营商和电力系统设计师提供了生成适当风力涡轮机以及控制需求和供应电力的重要信息。这项工作深入研究了人工智能（AI）在风能发电预测中的应用。对用于计算风速的设备进行了检查和讨论，重点是最近发表的研究。本综述的研究结果表明，人工智能正在被用于风力发电的测量和预测。与单个系统相比，混合人工智能系统提供了更准确的结果。讨论还发现，正确处理和校准风速计可以提高预测精度。这一结论表明，通过降低测量气象参数的设备误差并减少碳排放，可以提高风力预测的准确性。
