ABSTRACT

Energy demand in the world is overgrowing due to rising population and technological developments. It is vital to move toward a reliable, economical, and sustainable renewable energy source for energy needs arising in the future. Among other renewable energy sources, solar energy is a promising source of energy for handling long-term problems in the energy crisis. Solar power generation is expanding globally due to high energy demands and decreasing fossil fuel reserves, which are currently the primary sources of power generation. Photovoltaic (PV) cells are employed in the field of solar power generation for the conversion of solar radiation into electricity. Multiple PV cells combine in series or parallel to form a PV module (PVM). They are operated under continually changing environmental conditions causing various faults. Typically, faults are classified into visual, electrical, and miscellaneous faults. These faults should be identified and corrected immediately so that the performance, lifetime, and reliability of PV modules remain unaffected. This paper focuses on the detailed study of the types and causes of various faults that occur in a PVM. Several methods discussed in literature for fault diagnosis of PVM are reviewed. Faults occurring in PVM are particularly highlighted and diagnosis methods to detect and classify faults accurately are elaborated. Recommendations for future research direction are provided based on the reviewed papers.

摘要

由于人口增加和技术发展，世界上的能源需求正在增长。为了满足未来出现的能源需求，朝着可靠，经济和可持续的可再生能源发展至关重要。在其他可再生能源中，太阳能是解决能源危机中长期问题的有前途的能源。由于高能量需求和化石燃料储备的减少，太阳能发电正在全球范围内扩展，这是目前的主要发电来源。光伏（PV）电池用于太阳能发电领域，用于将太阳辐射转换为电能。多个PV电池串联或并联组合以形成PV模块（PVM）。它们在不断变化的环境条件下运行，导致各种故障。通常，故障分为视觉故障，电气故障和其他故障。应立即识别并纠正这些故障，以使PV模块的性能，寿命和可靠性不受影响。本文着重详细研究PVM中发生的各种故障的类型和原因。综述了文献中讨论的几种PVM故障诊断方法。特别强调了在PVM中发生的故障，并阐述了准确检测和分类故障的诊断方法。根据已审查的论文，提供了有关未来研究方向的建议。本文着重详细研究PVM中发生的各种故障的类型和原因。综述了文献中讨论的几种PVM故障诊断方法。特别强调了在PVM中发生的故障，并阐述了准确检测和分类故障的诊断方法。根据已审查的论文，提供了有关未来研究方向的建议。本文着重详细研究PVM中发生的各种故障的类型和原因。综述了文献中讨论的几种PVM故障诊断方法。特别强调了在PVM中发生的故障，并阐述了准确检测和分类故障的诊断方法。根据已审查的论文，提供了有关未来研究方向的建议。