Calculation of static voltage stability margin(SVSM)of AC/DC power systems with lots of renewable energy sources(RESs)integration requires consideration of uncertain load growth and renewable energy generation output....Calculation of static voltage stability margin(SVSM)of AC/DC power systems with lots of renewable energy sources(RESs)integration requires consideration of uncertain load growth and renewable energy generation output.This paper presents a bi-level optimal power flow(BLOPF)model to identify the worst-case SVSM of an AC/DC power system with line commutation converter-based HVDC and multi-terminal voltage sourced converter-based HVDC transmission lines.Constraints of uncertain load growth’s hypercone model and control mode switching of DC converter stations are considered in the BLOPF model.Moreover,uncertain RES output fluctuations are described as intervals,and two three-level optimal power flow(TLOPF)models are established to identify interval bounds of the system worst-case SVSM.The two TLOPF models are both transformed into max–min bi-level optimization models according to independent characteristics of different uncertain variables.Then,transforming the inner level model into its dual form,max–min BLOPF models are simplified to single-level optimization models for direct solution.Calculation results on the modified IEEE-39 bus AC/DC case and an actual large-scale AC/DC case in China indicate correctness and efficiency of the proposed identification method.展开更多
An optimal preventive-corrective control model for static voltage stability under multiple N-1 contingencies considering the wind power uncertainty is established in this paper.The objective is to minimize the control...An optimal preventive-corrective control model for static voltage stability under multiple N-1 contingencies considering the wind power uncertainty is established in this paper.The objective is to minimize the control variable adjustment cost including the load shedding cost of each contingency.The chance constraints of the static voltage stability margins(SvSMs)in the normal operation state and after each N-1 contingency are included.The approximate functions between the probability density functions(PDFs)of SVSMs and load shedding quantity with respect to preventive control variables are obtained to transform the expectation of load shedding quantity and the SvSM chance constraints into deterministic expressions.An approximate sequential convex quadratically constrained quadratic programming iteration method is proposed to solve the optimal control model.In each iteration,the approximate expressions and range are determined by the generated data samples.Moreover,a fast approximation calculation method of second-order matrices is proposed.By the naive Bayes classifier,the most severe N-1 contingencies are selected to replace all the contingencies to be added to the optimization model to improve the computational efficiency.Case studies on the IEEE-39 bus system and an actual provincial power grid demonstrate the effectiveness and efficiency of the proposed method.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.51977080)the Natural Science Foundation of Guangdong Province(Grant No.2022A1515010332)supported by the U.S.National Science Foundation(Grant#2124849).
文摘Calculation of static voltage stability margin(SVSM)of AC/DC power systems with lots of renewable energy sources(RESs)integration requires consideration of uncertain load growth and renewable energy generation output.This paper presents a bi-level optimal power flow(BLOPF)model to identify the worst-case SVSM of an AC/DC power system with line commutation converter-based HVDC and multi-terminal voltage sourced converter-based HVDC transmission lines.Constraints of uncertain load growth’s hypercone model and control mode switching of DC converter stations are considered in the BLOPF model.Moreover,uncertain RES output fluctuations are described as intervals,and two three-level optimal power flow(TLOPF)models are established to identify interval bounds of the system worst-case SVSM.The two TLOPF models are both transformed into max–min bi-level optimization models according to independent characteristics of different uncertain variables.Then,transforming the inner level model into its dual form,max–min BLOPF models are simplified to single-level optimization models for direct solution.Calculation results on the modified IEEE-39 bus AC/DC case and an actual large-scale AC/DC case in China indicate correctness and efficiency of the proposed identification method.
基金supported by the National Natural Science Foundation of China under Grant 51977080the Natural Science Foundation of Guangdong Province(2023A1515240075).
文摘An optimal preventive-corrective control model for static voltage stability under multiple N-1 contingencies considering the wind power uncertainty is established in this paper.The objective is to minimize the control variable adjustment cost including the load shedding cost of each contingency.The chance constraints of the static voltage stability margins(SvSMs)in the normal operation state and after each N-1 contingency are included.The approximate functions between the probability density functions(PDFs)of SVSMs and load shedding quantity with respect to preventive control variables are obtained to transform the expectation of load shedding quantity and the SvSM chance constraints into deterministic expressions.An approximate sequential convex quadratically constrained quadratic programming iteration method is proposed to solve the optimal control model.In each iteration,the approximate expressions and range are determined by the generated data samples.Moreover,a fast approximation calculation method of second-order matrices is proposed.By the naive Bayes classifier,the most severe N-1 contingencies are selected to replace all the contingencies to be added to the optimization model to improve the computational efficiency.Case studies on the IEEE-39 bus system and an actual provincial power grid demonstrate the effectiveness and efficiency of the proposed method.
