当前位置: X-MOL 学术IEEE J. Emerg. Sel. Top. Circuits Syst. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Development of Predictive Reliability Model of Solar Photovoltaic System Using Stochastic Diffusion Process for Distribution System
IEEE Journal on Emerging and Selected Topics in Circuits and Systems ( IF 4.6 ) Pub Date : 2022-01-31 , DOI: 10.1109/jetcas.2022.3148147
P. Manohar , Chandrasekhar Reddy Atla

Reliability assessment of power distribution systems is an essential concern for electric utilities to maintain supply continuity. In the event of supply failure, distributed energy resources play a vital role in restoring the supply to customers. This paper presents the development of a predictive reliability model for distribution system with solar Photovoltaic (PV) system. At the initial stage, the hourly solar irradiance and temperature are forecasted using Stochastic Diffusion Process (SDP)-based Monte Carlo simulation from historical data. Later, the cloud transients are modeled using the Jump Diffusion Process integrated into SDP. The monthly failure rates of PV system components are evaluated from historical data using the Physics of Failure (PoF) reliability model. Finally, the predictive reliability evaluation of the practical distribution system integrated with the proposed solar PV model is carried out. Results demonstrate the capability of the developed model to handle continuous and discrete uncertainties with more accuracy.

中文翻译:

利用随机扩散过程开发太阳能光伏系统配电系统可靠性预测模型

配电系统的可靠性评估是电力公司保持供电连续性的一个重要问题。在供应失败的情况下,分布式能源在恢复对客户的供应方面发挥着至关重要的作用。本文介绍了太阳能光伏 (PV) 系统配电系统预测可靠性模型的开发。在初始阶段,使用基于随机扩散过程 (SDP) 的蒙特卡罗模拟从历史数据中预测每小时太阳辐照度和温度。随后,使用集成到 SDP 中的跳跃扩散过程对云瞬态进行建模。光伏系统组件的每月故障率是使用故障物理 (PoF) 可靠性模型从历史数据中评估的。最后,对与所提出的太阳能光伏模型相结合的实际配电系统进行了预测可靠性评估。结果证明了所开发模型能够更准确地处理连续和离散的不确定性。
更新日期:2022-01-31
down
wechat
bug