人工智能技术在光伏发电输出功率预测领域的研究进展与展望OA
RESEARCH PROGRESS AND PROSPECTS OF AI IN THE FIELD OF PREDICTION OF PV POWER GENERATION OUTPUT POWER
在光伏发电装机规模逐年增大的背景下,光伏发电的间歇性和随机性对电网的安全运行造成了较大威胁.人工智能技术作为当前科技革命和产业变革的核心动力,在光伏发电输出功率预测方面的应用也愈加受到重视.全面分析了人工智能技术在光伏发电输出功率预测领域的应用现状、研究成果及面临的挑战,并对其在光伏发电输出功率预测领域的发展趋势进行了预测.分析结果显示:1)基于深度学习的光伏发电输出功率预测技术已取得显著的研究成果,能够显著降低预测结果的误差率;基于优化算法改进的光伏发电输出功率预测技术、基于物理和统计方法的光伏发电输出功率预测技术及其他预测技术也在不断进步,通过技术集成提高了预测精度和鲁棒性.2)人工智能技术在光伏发电输出功率预测领域应用中面临的挑战主要体现在大规模数据处理存在局限性、预测模型的泛化能力和适应性有待提高、预测结果的时效性较差、预测模型的透明度和可信度有待提升,以及预测技术和算法需不断创新这5个方面.3)人工智能技术在光伏发电输出功率预测领域应用时的发展趋势主要体现在集成模型、可解释性人工智能技术、实时数据和预测模型动态更新,以及智能光伏发电系统这4个方面.研究结果可为光伏发电输出功率预测技术的进步提供坚实的理论基础和实践指导.
Against the backdrop of the increasing installed capacity of PV power generation year by year,the intermittency and randomness of PV power generation pose a significant threat to the safe operation of the power grid.As the core driving force of the current technological revolution and industrial transformation,AI technology is increasingly being valued for its application in prediction of output power of PV power generation.This paper comprehensively analyzes the current application status,research results,and challenges faced by AI technology in the field of prediction of output power of PV power generation,and predicts its development trend in the field of prediction of output power of PV power generation.The analysis results show that:1)The prediction technology of output power of PV power generation based on deep learning has achieved significant research results,which can significantly reduce the error rate of prediction results,prediction technology of output power of PV power generation based on optimization algorithms,prediction technology of output power of PV power generation based on physical and statistical methods,and other prediction technologies are constantly advancing,improving the accuracy and robustness of predictions through technological integration.2)The challenges faced by the application of AI technology in the field of prediction of output power of PV power generation mainly lie in the limitations of large-scale data processing,the need to improve the generalization ability and adaptability of prediction models,the poor timeliness of prediction results,the need to improve the transparency and credibility of prediction models,and the need for continuous innovation in prediction technology and algorithms.3)The development trend of AI technology in the field of prediction of output power of PV power generation is mainly reflected in four aspects:integrated models,explainable AI technology,real-time data and predicton model dynamic updates,and intelligent PV power generation systems.The research results can provide a solid theoretical basis and practical guidance for the advancement of prediction technology of output power of PV power generation.
杨军;李峰;武万里
宁夏气象服务中心,银川 750002国网宁夏电力有限公司,银川 750001宁夏气象服务中心,银川 750002
信息技术与安全科学
人工智能技术光伏发电输出功率预测深度学习可解释性人工智能技术技术创新
AI technologyprediction of output power of PV power generationdeep learningXAItechnological innovation
《太阳能》 2026 (2)
5-14,10
宁夏自然科学基金项目(2022AAC03676)
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