RELIABILITY OF SMART GRIDS WITH SMART ASSETS AND LARGE WIND FARMS

P. A. Oyewole, D. Jayaweera
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Abstract

Uncertainties and vulnerabilities exist with extensive integration of renewable energy resources and high dependence of the smart grid system on information communication technology. This paper proposes an innovative four-state smart component model based on Markovian differential time dependent state probabilities concept to capture smart components' intelligent operational behaviour in a smart grid system and to assess detailed reliability performance of the entire system. The proposed approach consists of the four-state smart model of smart component behaviour, stochastic variation of wind power generation outputs, random load variations and quantification of the impacts using Monte Carlo simulation. Also, the approach quantitatively evaluates the impacts of smart components failure in the presence of intermittent power generation of wind farms. The approach is demonstrated by case studies. The results suggest that the four-state smart components model capture the intelligent operational behaviour comprehensively. Findings justify that the intermittent integration of wind power outputs and geographical locations can potentially impact the smart grid system reliability considerably.
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具有智能资产和大型风力发电场的智能电网的可靠性
由于可再生能源资源的广泛集成和对信息通信技术的高度依赖,智能电网系统存在不确定性和脆弱性。本文提出了一种基于马尔可夫微分时变状态概率概念的四状态智能组件模型,以捕捉智能电网系统中智能组件的智能运行行为,并对整个系统的详细可靠性性能进行评估。该方法由智能组件行为的四态智能模型、风力发电输出的随机变化、随机负荷变化和使用蒙特卡洛模拟的影响量化组成。此外,该方法定量评估了在风力发电场间歇性发电的情况下智能组件故障的影响。案例研究证明了这种方法。结果表明,四态智能组件模型全面地捕捉了智能运行行为。研究结果证明,风力发电输出和地理位置的间歇性整合可能会对智能电网系统的可靠性产生相当大的影响。
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