Voltage Security Assessment by Using PFDT and CBR Methods in Emerging Power System

被引:5
作者
Nandanwar, S. R. [1 ]
Kolhe, M. L. [2 ]
Warkad, S. B. [3 ]
Patidar, N. P. [4 ]
Singh, V. K. [4 ]
机构
[1] Priyadarshni Coll Engn, Dept Elect Engn, Hingna Rd, Nagpur 440019, Maharashtra, India
[2] Univ Agder, Fac Engn & Sci, POB 422, NO-4604 Kristiansand, Norway
[3] PR Pote Coll Engn, Elect Engn Dept, Kathora Rd, Amravati 444602, India
[4] MA Natl Inst Technol, Dept Elect Engn, Bhopal, India
来源
SPECIAL ISSUE OF THE FOURTH INTERNATIONAL SYMPOSIUM ON HYDROGEN ENERGY, RENEWABLE ENERGY AND MATERIALS, 2018 (HEREM 2018) | 2018年 / 144卷
关键词
Case based reasoning; optimal load shedding; probabilistic fuzzy decision tree; loadability margin;
D O I
10.1016/j.egypro.2018.06.023
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 exhibits varied methods for voltage security assessment in a restructured power system. This paper primarily lays emphasis on two methods that are Probabilistic Fuzzy Decision Tree (PFDT) and Case Based Reasoning (CBR). In PFDT, Decision Tree plays an integral role for classification of system. For further classification of power system security, an algorithm is developed to categorise the buses which trouble the security most. After classification of system, by using minimum amount of load curtailment of voltages on buses which made insecure to secure load. Optimization of load is done by curtailing reactive power from insecure buses. In CBR, old cases from database are used for solving the problems of new case. Hence, PFDT is retrained in system during real operation for solving the new operating states which are found insecure in CBR approach. In case of emergency or a critical situation, structure of the power system networks changes but in such a condition CBR also gives better results by using re-training process. After re-training in real-time, CBR revises its database by accepting new conditions and stored for their further uses. These two methods are analysed on the standard test system i.e. IEEE-30 Bus along with desired accuracy. Copyright (C) 2018 The Authors. Published by Elsevier Ltd.
引用
收藏
页码:170 / 181
页数:12
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