Decomposition-Based Stability Analysis for Isolated Power Systems With Reduced Conservativeness

An isolated power system (IPS) usually operates in an islanded mode. Because of the lack of support from an external power grid, stability is a prominent issue for IPSs. This article proposes a novel stability analysis approach for IPSs based on the input-to-state stability (ISS) theory. Compared with existing stability analyses that use simulations and direct methods, the proposed method decomposes the stability analysis process by considering the ISS properties of subsystems and a network equation that reflects their connections. Thus, it has good adaptability for the stability analysis of systems with flexible operating conditions. Algorithms are presented for estimating the ISS properties of subsystems, and asymptotic gains in a piecewise linear form are adopted. The small gain theorem is used for the decomposed stability analysis, and a practical algorithm to numerically check the small gain condition is presented. Time-domain simulations were performed with a test system to verify the effectiveness of the proposed decomposition-based stability analysis approach. Note to Practitioners—Power systems used in shipboards, airplanes, remote areas, and so on are usually classified as isolated power systems (IPSs). The continuity of power supply in IPSs is the prerequisite of fulfilling certain tasks. Due to the lack of support from the bulk power grid, the normal operation of IPSs can be threatened by various external disturbances, such as disasters, battle damages, device failures, and so on. To maintain the survivability and reliability of IPSs under extreme conditions, fast reconfiguration and emergency control approaches are often performed, which lead to system topology changes and frequent connection/disconnection operation of devices in IPSs. Because of the limited generation capacity of an IPS, a stability analysis after an emergency is important for ensuring that the IPS can perform tasks normally, and can provide guidance for designing fast reconfiguration and emergency control strategies. However, current stability analysis approaches have limited applicability or are overly conservative for analyzing the stability of IPSs. To address the challenge of changeable topologies for the stability analysis of an IPS, this article proposes a decomposition-based analysis approach using input-to-state stability (ISS) theory. By decomposing the entire system into several subsystems, the system’s stability can be checked through the ISS properties of subsystems and their connections. The ISS properties of subsystems can be estimated offline, which saves time for online calculation. To reduce the conservativeness of stability analysis, the asymptotic gains in piecewise linear form are adopted in this article. Practical algorithms are designed for efficiently checking the proposed decomposition-based stability conditions. The research outcome provides a fast and flexible stability analysis approach that can adapt to the frequent changes in the operating conditions of IPSs.

[1]  Shengwei Mei,et al.  Estimation of LISS (local input-to-state stability) properties for nonlinear systems , 2010 .

[2]  Fabian R. Wirth,et al.  Numerical verification of local input-to-state stability for large networks , 2007, 2007 46th IEEE Conference on Decision and Control.

[3]  Xiaorong Xie,et al.  An Emergency-Demand-Response Based Under Speed Load Shedding Scheme to Improve Short-Term Voltage Stability , 2017, IEEE Transactions on Power Systems.

[4]  M. A. Abido Optimal des'ign of Power System Stabilizers Using Particle Swarm Opt'imization , 2002, IEEE Power Engineering Review.

[5]  David J. Hill,et al.  Lyapunov formulation of ISS cyclic-small-gain in continuous-time dynamical networks , 2011, Autom..

[6]  Ali Mohammad Ranjbar,et al.  An Input-to-State Stability Approach to Inertial Frequency Response Analysis of Doubly-Fed Induction Generator-Based Wind Turbines , 2017, IEEE Transactions on Energy Conversion.

[7]  Eduardo Sontag Input to State Stability: Basic Concepts and Results , 2008 .

[8]  Shengwei Mei,et al.  Input-to-State Stability Based Control of Doubly Fed Wind Generator , 2018, IEEE Transactions on Power Systems.

[9]  Xu Cai,et al.  Optimal Design of Controller Parameters for Improving the Stability of MMC-HVDC for Wind Farm Integration , 2018, IEEE Journal of Emerging and Selected Topics in Power Electronics.

[10]  Fabian R. Wirth,et al.  An ISS small gain theorem for general networks , 2007, Math. Control. Signals Syst..

[11]  Andrew R. Teel,et al.  On the application of the small-gain theorem to the stability analysis of large-scale power systems with delay , 2012, 2012 American Control Conference (ACC).

[12]  Z. Jarvis-Wloszek,et al.  Lyapunov Based Analysis and Controller Synthesis for Polynomial Systems using Sum-of-Squares Optimization , 2003 .

[13]  Shengwei Mei,et al.  Algorithm for local input-to-state stability analysis , 2016 .

[14]  A. Papachristodoulou,et al.  Analysis of Non-polynomial Systems using the Sum of Squares Decomposition , 2005 .

[15]  Phuong Huynh Stability analysis of large-scale power electronics systems , 1994 .

[16]  Federico Milano,et al.  Algorithmic Construction of Lyapunov Functions for Power System Stability Analysis , 2013, IEEE Transactions on Circuits and Systems I: Regular Papers.

[17]  David J. Hill,et al.  Robust exponential input-to-state stability of impulsive systems with an application in micro-grids , 2014, Syst. Control. Lett..

[18]  Graziano Chesi,et al.  Estimating the domain of attraction for non-polynomial systems via LMI optimizations , 2009, Autom..

[19]  Frank Allgöwer,et al.  Bistable Biological Systems: A Characterization Through Local Compact Input-to-State Stability , 2008, IEEE Transactions on Automatic Control.

[20]  Sergey Dashkovskiy,et al.  Local ISS of large-scale interconnections and estimates for stability regions , 2010, Syst. Control. Lett..

[21]  Babu Narayanan,et al.  POWER SYSTEM STABILITY AND CONTROL , 2015 .

[22]  Zhao Hui,et al.  Optimal Design of Power System Stabilizer Using Particle Swarm Optimization , 2006 .

[23]  Eduardo D. Sontag,et al.  Lyapunov Characterizations of Input to Output Stability , 2000, SIAM J. Control. Optim..

[24]  Eduardo Sontag Smooth stabilization implies coprime factorization , 1989, IEEE Transactions on Automatic Control.

[25]  Xi Liu,et al.  Input-to-state stability of model-based spacecraft formation control systems with communication constraints , 2011 .

[26]  H. Chiang Direct Methods for Stability Analysis of Electric Power Systems: Theoretical Foundation, BCU Methodologies, and Applications , 2010 .

[27]  Eduardo Sontag,et al.  New characterizations of input-to-state stability , 1996, IEEE Trans. Autom. Control..

[28]  Ying Chen,et al.  Decomposed input-output stability analysis and enhancement of integrated power systems , 2018 .