Interval Power Flow Analysis Considering Interval Output of Wind Farms through Affine Arithmetic and Optimizing-Scenarios Method

Weijie Cheng, Renli Cheng, Jun Shi, Cong Zhang, Gaoxing Sun and Dong Hua
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Weijie Cheng: Shenzhen Power Supply Bureau Co., Ltd., Shenzhen 518000, China
Renli Cheng: Shenzhen Power Supply Bureau Co., Ltd., Shenzhen 518000, China
Jun Shi: Shenzhen Power Supply Bureau Co., Ltd., Shenzhen 518000, China
Cong Zhang: College of Electrical and Information Engineering, Hunan University, Changsha 410000, China
Gaoxing Sun: School of Electric Power, South China University of Technology, Guangzhou 510000, China
Dong Hua: School of Electric Power, South China University of Technology, Guangzhou 510000, China

Energies, 2018, vol. 11, issue 11, 1-23

Abstract: Wind power belongs to sustainable and clean energy sources which play a vital role of reducing environment pollution and addressing energy crisis. However, wind power outputs are quite difficult to predict because they are derived from wind speeds, which vary irregularly and greatly all the time. The uncertainty of wind power causes variation of the variables of power grids, which threatens the power grids’ operating security. Therefore, it is significant to provide the accurate ranges of power grids’ variables, which can be used by the operators to guarantee the power grid’s operating security. To achieve this goal, the present paper puts forward the interval power flow with wind farms model, where the generation power outputs of wind farms are expressed by intervals and three types of control modes are considered for imitating the operation features of wind farms. To solve the proposed model, the affine arithmetic-based method and optimizing-scenarios method are modified and employed, where three types of constraints of wind control modes are considered in their solution process. The former expresses the interval variables as affine arithmetic forms, and constructs optimization models to contract the affine arithmetic forms to obtain the accurate intervals of power flow variables. The latter regards active power outputs of the wind farms as variables, which vary in their corresponding intervals, and accordingly builds the minimum and maximum programming models for estimating the intervals of the power flow variables. The proposed methods are applied to two case studies, where the acquired results are compared with those acquired by the Monte Carlo simulation, which is a traditional method for handling interval uncertainty. The simulation results validate the advantages, effectiveness and the applicability of the two methods.

Keywords: affine arithmetic; interval variables; optimizing-scenarios method; power flow; wind power (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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