Risk Assessment of Voltage Limit Violation Based on Probabilistic Load Flow in Active Distribution Network

被引:0
作者
Dong, Jing [1 ]
Li, Xue [1 ]
Du, Dajun [1 ]
机构
[1] Shanghai Univ, Shanghai Key Lab Power Stn Automat Technol, Shanghai 200072, Peoples R China
来源
ADVANCES IN GREEN ENERGY SYSTEMS AND SMART GRID, PART III | 2018年 / 925卷
基金
美国国家科学基金会;
关键词
Risk assessment; Voltage limit violation; Active distribution network; EV charging/discharging strategy; Correlation; Loss of load; IMPACTS; POWER;
D O I
10.1007/978-981-13-2381-2_24
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
This paper mainly investigates risk assessment of voltage limit violation in active distribution network with integration of wind generation (WG), photovoltaic generation (PVG) and electric vehicles (EVs). Firstly, to avoid additional peak load caused by random EV charging, a controlled EV charging and discharging strategy is designed. Then, for the correlations of spatially near WGs and PVGs, Nataf transformation and orthogonal transformation (OT) are integrated to solve the problem, and this provides a path for point estimate method (PEM) based probabilistic load flow (PLF) to obtain steady-state voltage of active distribution network. Furthermore, based on the voltage results, a model for quantifying the risk of voltage limit violation is developed by considering loss of load caused by voltage limit violation, which is different from the previous risk indices calculated by possibility and severity of voltage limit violation. Finally, the proposed model is tested on the modified IEEE 33-bus system. Simulation results confirm that the effective EV charging/discharging strategies and penetration increment of WG and PVG help to decrease operation risk of active distribution network.
引用
收藏
页码:253 / 263
页数:11
相关论文
共 14 条
[1]   New Metrics for Evaluating Technical Benefits and Risks of DGs Increasing Penetration [J].
Akbari, Mohammad Amin ;
Aghaei, Jamshid ;
Barani, Mostafa ;
Savaghebi, Mehdi ;
Shafie-Khah, Miadreza ;
Guerrero, Josep M. ;
Catalao, Joao P. S. .
IEEE TRANSACTIONS ON SMART GRID, 2017, 8 (06) :2890-2902
[2]   Probabilistic Optimal PV Capacity Planning for Wind Farm Expansion Based on NASA Data [J].
Cao, Yongji ;
Zhang, Yi ;
Zhang, Hengxu ;
Shi, Xiaohan ;
Terzija, Vladimir .
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY, 2017, 8 (03) :1291-1300
[3]  
Li Xue, 2016, Journal of Donghua University (English Edition), V33, P734
[4]   Transmission Line Overload Risk Assessment for Power Systems With Wind and Load-Power Generation Correlation [J].
Li, Xue ;
Zhang, Xiong ;
Wu, Lei ;
Lu, Pan ;
Zhang, Shaohua .
IEEE TRANSACTIONS ON SMART GRID, 2015, 6 (03) :1233-1242
[5]   Power System Risk Assessment in Cyber Attacks Considering the Role of Protection Systems [J].
Liu, Xindong ;
Shahidehpour, Mohammad ;
Li, Zuyi ;
Liu, Xuan ;
Cao, Yijia ;
Li, Zhiyi .
IEEE TRANSACTIONS ON SMART GRID, 2017, 8 (02) :572-580
[6]   Optimal Siting and Sizing of Distributed Generators in Distribution Systems Considering Uncertainties [J].
Liu, Zhipeng ;
Wen, Fushuan ;
Ledwich, Gerard .
IEEE TRANSACTIONS ON POWER DELIVERY, 2011, 26 (04) :2541-2551
[7]   Risk Assessment for Power System Operation Planning With High Wind Power Penetration [J].
Negnevitsky, Michael ;
Dinh Hieu Nguyen ;
Piekutowski, Marian .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2015, 30 (03) :1359-1368
[8]   Determining charging load of PHEVs considering HVAC system and analyzing its probabilistic impacts on residential distribution network [J].
Pouladi, Jaber ;
Sharifian, M. B. Bannae ;
Soleymani, Soodabeh .
ELECTRIC POWER SYSTEMS RESEARCH, 2016, 141 :300-312
[9]   HPC-Based Probabilistic Analysis of LV Networks With EVs: Impacts and Control [J].
Procopiou, Andreas T. ;
Quiros-Tortos, Jairo ;
Ochoa, Luis F. .
IEEE TRANSACTIONS ON SMART GRID, 2017, 8 (03) :1479-1487
[10]   An over-limit risk assessment of PV integrated power system using probabilistic load flow based on multi-time instant uncertainty modeling [J].
Prusty, B. Rajanarayan ;
Jena, Debashisha .
RENEWABLE ENERGY, 2018, 116 :367-383