An Optimized Swinging Door Algorithm for Identifying Wind Ramping Events

Cui, Mingjian; Zhang, Jie; Florita, Anthony; Hodge, Bri‐Mathias; Ke, Deping; Sun, Yang

doi:10.1109/tste.2015.2477244

Cited by 85 publications

(41 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To sample WPRs, a data mining method [31] was used to detect the ramping events in historical wind power data. A nonlinear least square (NLS) analysis was adopted to estimate all the parameters (ω, µ, and σ) of the mixture components of a Gaussian model [17].…”

Section: Modeling Of Wind Power and Wprsmentioning

confidence: 99%

Power Grid Reliability Evaluation Considering Wind Farm Cyber Security and Ramping Events

Liu

et al. 2019

Applied Sciences

Self Cite

View full text Add to dashboard Cite

The cybersecurity of wind farms is an increasing concern in recent years, and its impacts on the power system reliability have not been fully studied. In this paper, the pressing issues of wind farms, including cybersecurity and wind power ramping events (WPRs) are incorporated into a new reliability evaluation approach. Cyber–physical failures like the instantaneous failure and longtime fatigue of wind turbines are considered in the reliability evaluation. The tripping attack is modeled in a bilevel optimal power flow model which aims to maximize the load shedding on the system’s vulnerable moment. The time-varying failure rate of wind turbine is approximated by Weibull distribution which incorporates the service time and remaining life of wind turbine. Various system defense capacities and penetration rates of wind power are simulated on the typical reliability test system. The comparative and sensitive analyses show that power system reliability is challenged by the cybersecurity of wind farms, especially when the installed capacity of wind power continues to rise. The timely patching of network vulnerabilities and the life management of wind turbines are important measures to ensure the cyber–physical security of wind farms.

show abstract

Section: Modeling Of Wind Power and Wprsmentioning

confidence: 99%

Power Grid Reliability Evaluation Considering Wind Farm Cyber Security and Ramping Events

Liu

et al. 2019

Applied Sciences

Self Cite

View full text Add to dashboard Cite

show abstract

“…It is difficult for the power system to retain secure, reliable and economic operations, especially at a high level of wind power penetrations. According to the actual situation of wind power integration, power system operators (PSOs) find that the large-scale wind power can increase or decrease in a very short time period with large and rapid fluctuations [3,4]. With the recent rapid development of the energy storage system (ESS), it is becoming a hot focus to use the ESS to mitigate the uncertainty and variability of wind power for government policies, power and energy industries and academic research.…”

Section: Introductionmentioning

confidence: 99%

A Chance-Constrained Economic Dispatch Model in Wind-Thermal-Energy Storage System

Yang

et al. 2017

Energies

Self Cite

View full text Add to dashboard Cite

Abstract:As a type of renewable energy, wind energy is integrated into the power system with more and more penetration levels. It is challenging for the power system operators (PSOs) to cope with the uncertainty and variation of the wind power and its forecasts. A chance-constrained economic dispatch (ED) model for the wind-thermal-energy storage system (WTESS) is developed in this paper. An optimization model with the wind power and the energy storage system (ESS) is first established with the consideration of both the economic benefits of the system and less wind curtailments. The original wind power generation is processed by the ESS to obtain the final wind power output generation (FWPG). A Gaussian mixture model (GMM) distribution is adopted to characterize the probabilistic and cumulative distribution functions with an analytical expression. Then, a chance-constrained ED model integrated by the wind-energy storage system (W-ESS) is developed by considering both the overestimation costs and the underestimation costs of the system and solved by the sequential linear programming method. Numerical simulation results using the wind power data in four wind farms are performed on the developed ED model with the IEEE 30-bus system. It is verified that the developed ED model is effective to integrate the uncertain and variable wind power. The GMM distribution could accurately fit the actual distribution of the final wind power output, and the ESS could help effectively decrease the operation costs.

show abstract

“…For the direct method, the wind power ramp rate, or a parameter related to wind power ramps, is forecast directly. Support Vector Machines (SVM) were found to be the most accurate method by Zheng and Kusiakm after comparison of five different algorithms [15]. A combinatorial forecast method known as atom sparse decomposition (ASD) and a back propagation neural network (BPNN) was proposed by Cui et al [15,16].…”

mentioning

confidence: 99%

“…Support Vector Machines (SVM) were found to be the most accurate method by Zheng and Kusiakm after comparison of five different algorithms [15]. A combinatorial forecast method known as atom sparse decomposition (ASD) and a back propagation neural network (BPNN) was proposed by Cui et al [15,16]. This method avoids the effect of instability of the original signal on the predicted result and greatly improves the precision by decomposing the original signal before its prediction and replacing the residual signal for the original signal as an input to the BPNN.…”

mentioning

confidence: 99%

A Hybrid Forecasting Method for Wind Power Ramp Based on Orthogonal Test and Support Vector Machine (OT-SVM)

Liu

Sun

Infield

et al. 2017

IEEE Trans. Sustain. Energy

View full text Add to dashboard Cite

show abstract

An Optimized Swinging Door Algorithm for Identifying Wind Ramping Events

Cited by 85 publications

References 20 publications

Power Grid Reliability Evaluation Considering Wind Farm Cyber Security and Ramping Events

Power Grid Reliability Evaluation Considering Wind Farm Cyber Security and Ramping Events

A Chance-Constrained Economic Dispatch Model in Wind-Thermal-Energy Storage System

A Hybrid Forecasting Method for Wind Power Ramp Based on Orthogonal Test and Support Vector Machine (OT-SVM)

Contact Info

Product

Resources

About