{"title":"A unified analysis of the impacts of stochasticity and low inertia of wind generation","authors":"N. Nguyen, M. Benidris, J. Mitra","doi":"10.1109/PMAPS.2016.7764209","DOIUrl":null,"url":null,"abstract":"This paper proposes a new method to model wind generation in power system reliability evaluation that not only considers the uncertainty of wind speed and mechanical failures of wind turbines but also includes the impacts of wind's low inertia property. Due to the stochasticity and low inertia of wind generation, power system stability and reliability are significantly affected. When wind generators are integrated into the grid, a strategy to ensure the system stability is that wind generators are required to operate at a lower level than their maximum available output power. The effect of this requirement is that not all of the available wind power will be used in the system, which in turn affects the contribution of wind generation in power system availability. The proposed model is implemented using Monte Carlo methods. For every system state, the maximum integrated amount of wind power is determined based on frequency regulation requirements. Then, this amount of power is used along with the stochastic model of wind speed in the reliability modeling. The proposed method is demonstrated on the IEEE RTS system. Power system reliability with and without considering the impacts of wind stochasticity and low inertia are compared to show the effectiveness of the proposed method.","PeriodicalId":265474,"journal":{"name":"2016 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PMAPS.2016.7764209","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8
Abstract
This paper proposes a new method to model wind generation in power system reliability evaluation that not only considers the uncertainty of wind speed and mechanical failures of wind turbines but also includes the impacts of wind's low inertia property. Due to the stochasticity and low inertia of wind generation, power system stability and reliability are significantly affected. When wind generators are integrated into the grid, a strategy to ensure the system stability is that wind generators are required to operate at a lower level than their maximum available output power. The effect of this requirement is that not all of the available wind power will be used in the system, which in turn affects the contribution of wind generation in power system availability. The proposed model is implemented using Monte Carlo methods. For every system state, the maximum integrated amount of wind power is determined based on frequency regulation requirements. Then, this amount of power is used along with the stochastic model of wind speed in the reliability modeling. The proposed method is demonstrated on the IEEE RTS system. Power system reliability with and without considering the impacts of wind stochasticity and low inertia are compared to show the effectiveness of the proposed method.