Intentional power system islanding under cascading outages using energy function method

被引:8
作者
Kamali, Sadegh [1 ]
Amraee, Turaj [1 ]
Khorsand, Mojdeh [2 ]
机构
[1] KN Toosi Univ Technol, Fac Elect Engn, Tehran, Iran
[2] Arizona State Univ, Sch Elect Comp & Energy Engn, Tempe, AZ USA
关键词
optimisation; linear programming; integer programming; power system transient stability; load flow; distributed power generation; power distribution faults; power system reliability; power system security; critical island; linear constraint; two-stage model; dynamic IEEE 118-bus system; intentional power system islanding; cascading outages; energy function method; cascading failures; island issue; transient stability constraint; islanding strategy; current available controlled islanding model; transient stability criteria; two-stage transient stability constrained network splitting model; proper transient energy function; conventional intentional splitting problem; mixed-integer linear programming optimisation model; coherency; minimum total power imbalance; network splitting plan; ONLINE COHERENCY IDENTIFICATION; SPLITTING STRATEGIES; OPERATION;
D O I
10.1049/iet-gtd.2019.0317
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In this study, the 'where to island' issue under the transient stability constraints is addressed. Without considering the transient stability, the islanding strategy may fail to stop the propagation of harmful dynamics throughout the network. This study promotes the current available controlled islanding model to handle the transient stability criteria, which is the most important issue during network splitting. Based on the wide area measurements, a two-stage transient stability constrained network splitting model is developed using a proper transient energy function. In the first stage, the conventional intentional splitting problem is formulated as a mixed-integer linear programming (MILP) optimisation model with considering operational, coherency and linear AC load flow constraints. The boundary of each island is determined using an optimisation model to achieve the minimum total power imbalance. To assess the transient stability, the network splitting plan obtained from the first stage is then evaluated in the second stage using a transient energy function. In the second stage, to satisfy the transient stability constraint of the critical island, a linear constraint is constructed and added to the MILP formulation of the first stage. In the second stage, the saddle or control unstable equilibrium points are determined using an optimisation model.
引用
收藏
页码:4553 / 4562
页数:10
相关论文
共 50 条
  • [41] Optimal power scheduling of renewable energy systems in microgrids using distributed energy storage system
    Singh, Shakti
    Singh, Mukesh
    Kaushik, Subhash Chandra
    IET RENEWABLE POWER GENERATION, 2016, 10 (09) : 1328 - 1339
  • [42] Energy, exergy, economic, and environment (4E) assessment of a temperature cascading multigeneration system under experimental off-design conditions
    Chen, W. D.
    Chua, K. J.
    ENERGY CONVERSION AND MANAGEMENT, 2022, 253
  • [43] Risk-based method to secure power systems against cyber-physical faults with cascading impacts: a system protection scheme application
    Calvo, Jose Luis
    Tindemans, Simon H.
    Strbac, Goran
    JOURNAL OF MODERN POWER SYSTEMS AND CLEAN ENERGY, 2018, 6 (05) : 930 - 943
  • [44] Reactive power planning under high penetration of wind energy using Benders decomposition
    Fang, Xin
    Li, Fangxing
    Wei, Yanli
    Azim, Riyasat
    Xu, Yan
    IET GENERATION TRANSMISSION & DISTRIBUTION, 2015, 9 (14) : 1835 - 1844
  • [45] Advanced Energy Management in Virtual Power Plant using Multi Agent System
    Raju, Leo
    Appaswamy, Kaviya
    Vengatraman, Janani
    Morais, Antony Amairaj
    2016 3RD INTERNATIONAL CONFERENCE ON ELECTRICAL ENERGY SYSTEMS (ICEES), 2016, : 133 - 138
  • [46] Optimising power system frequency stability using virtual inertia from inverter-based renewable energy generation
    Farmer, Warren J.
    Rix, Arnold J.
    IET RENEWABLE POWER GENERATION, 2020, 14 (15) : 2820 - 2829
  • [47] Dispatch optimization of a concentrating solar power system under uncertain solar irradiance and energy prices
    Kahvecioglu, Gokce
    Morton, David P.
    Wagner, Michael J.
    APPLIED ENERGY, 2022, 326
  • [48] Assessment of Power System Asset Dispatch under Different Local Energy Community Business Models
    Korotko, Tarmo
    Plaum, Freddy
    Haering, Tobias
    Mutule, Anna
    Lazdins, Roberts
    Borscevskis, Olegs
    Rosin, Argo
    Carroll, Paula
    ENERGIES, 2023, 16 (08)
  • [49] Integrating high share of renewable energy into power system using customer-sited energy storage
    Chen, Siyuan
    Li, Zheng
    Li, Weiqi
    RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2021, 143
  • [50] A new financial loss/gain wind power forecasting method based on deep machine learning algorithm by using energy storage system
    Keynia, Farshid
    Memarzadeh, Gholamreza
    IET GENERATION TRANSMISSION & DISTRIBUTION, 2022, 16 (05) : 851 - 868