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Hao Yue,Gengyin Li,Ming Zhou 대한전기학회 2013 Journal of Electrical Engineering & Technology Vol.8 No.6
This paper presents a probabilistic methodology for small signal stability analysis of power system with correlated wind sources. The approach considers not only the stochastic characteristics of wind speeds which are treated as random variables with Weibull distributions, while also the wind speed spatial correlations which are characterized by a correlation matrix. The approach based on the 2m+1 point estimate method and Cornish Fisher expansion, the orthogonal transformation technique is used to deal with the correlation of wind farms. A case study is carried out on IEEE New England system and the probabilistic indexes for eigenvalue analysis are computed from the statistical processing of the obtained results. The accuracy and efficiency of the proposed method are confirmed by comparing with the results of Monte Carlo simulation. The numerical results indicate that the proposed method can actually capture the probabilistic characteristics of mode properties of the power systems with correlated wind sources and the consideration of spatial correlation has influence on the probability of system small signal stability.
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Sibo Nan,Ming Zhou,Gengyin Li,Yong Xia 대한전기학회 2019 Journal of Electrical Engineering & Technology Vol.14 No.2
With the reformation of electric power market and the development of smart grid technology, smart residential community, a new residential demand side entity, tends to play an important role in demand response program. This paper presents a dayahead demand response scheduling model for the novel residential community considering the impact of various residential load uncertainties. In this paper, each residential load with uncertainties is fi rstly modeled using Copula, and the random scenarios are generated by Monte Carlo simulation. Secondly, the residential loads are classifi ed into diff erent categories according to various demand response strategies, and an optimal scheduling scheme for residential loads and distributed generation is modeled. Finally, the generated scenarios are integrated into the scheduling model to form the complete optimal residential demand stochastic scheduling scheme. The presented model can reduce the cost of user’s electricity consumption and decrease the peak load, load peak-valley diff erence, and the energy consumption of residential load profi le without bringing discomfort to the users, through which residential community can participate in demand response effi ciently. Besides, this model can also provide support for the decision of electricity pricing strategies under power market development.
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Yue, Hao,Li, Gengyin,Zhou, Ming The Korean Institute of Electrical Engineers 2013 Journal of Electrical Engineering & Technology Vol.8 No.6
This paper presents a probabilistic methodology for small signal stability analysis of power system with correlated wind sources. The approach considers not only the stochastic characteristics of wind speeds which are treated as random variables with Weibull distributions, while also the wind speed spatial correlations which are characterized by a correlation matrix. The approach based on the 2m+1 point estimate method and Cornish Fisher expansion, the orthogonal transformation technique is used to deal with the correlation of wind farms. A case study is carried out on IEEE New England system and the probabilistic indexes for eigenvalue analysis are computed from the statistical processing of the obtained results. The accuracy and efficiency of the proposed method are confirmed by comparing with the results of Monte Carlo simulation. The numerical results indicate that the proposed method can actually capture the probabilistic characteristics of mode properties of the power systems with correlated wind sources and the consideration of spatial correlation has influence on the probability of system small signal stability.
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MPC-based Two-stage Rolling Power Dispatch Approach for Wind-integrated Power System
Junyi Zhai,Ming Zhou,Shengxiao Dong,Gengyin Li,Jianwen Ren 대한전기학회 2018 Journal of Electrical Engineering & Technology Vol.13 No.2
Regarding the fact that wind power forecast accuracy is gradually improved as time is approaching, this paper proposes a two-stage rolling dispatch approach based on model predictive control (MPC), which contains an intra-day rolling optimal scheme and a real-time rolling base point tracing scheme. The scheduled output of the intra-day rolling scheme is set as the reference output, and the real-time rolling scheme is based on MPC which includes the leading rolling optimization and lagging feedback correction strategy. On the basis of the latest measured thermal unit output feedback, the closed-loop optimization is formed to correct the power deviation timely, making the unit output smoother, thus reducing the costs of power adjustment and promoting wind power accommodation. We adopt chance constraint to describe forecasts uncertainty. Then for reflecting the increasing prediction precision as well as the power dispatcher’s rising expected satisfaction degree with reliable system operation, we set the confidence level of reserve constraints at different timescales as the incremental vector. The expectation of up/down reserve shortage is proposed to assess the adequacy of the upward/downward reserve. The studies executed on the modified IEEE RTS system demonstrate the effectiveness of the proposed approach.
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MPC-based Two-stage Rolling Power Dispatch Approach for Wind-integrated Power System
Zhai, Junyi,Zhou, Ming,Dong, Shengxiao,Li, Gengyin,Ren, Jianwen The Korean Institute of Electrical Engineers 2018 Journal of Electrical Engineering & Technology Vol.13 No.2
Regarding the fact that wind power forecast accuracy is gradually improved as time is approaching, this paper proposes a two-stage rolling dispatch approach based on model predictive control (MPC), which contains an intra-day rolling optimal scheme and a real-time rolling base point tracing scheme. The scheduled output of the intra-day rolling scheme is set as the reference output, and the real-time rolling scheme is based on MPC which includes the leading rolling optimization and lagging feedback correction strategy. On the basis of the latest measured thermal unit output feedback, the closed-loop optimization is formed to correct the power deviation timely, making the unit output smoother, thus reducing the costs of power adjustment and promoting wind power accommodation. We adopt chance constraint to describe forecasts uncertainty. Then for reflecting the increasing prediction precision as well as the power dispatcher's rising expected satisfaction degree with reliable system operation, we set the confidence level of reserve constraints at different timescales as the incremental vector. The expectation of up/down reserve shortage is proposed to assess the adequacy of the upward/downward reserve. The studies executed on the modified IEEE RTS system demonstrate the effectiveness of the proposed approach.
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