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基于粒子群算法的电力系统状态优化估计

Abstract第7页
摘要第8-11页
Chapter 1 Introduction第11-17页
    1.1 Background第11-12页
    1.2 Literature review第12-14页
        1.2.1 Status state estimation第12-14页
    1.3 Motivation第14-15页
    1.4 Research contribution第15-16页
    1.5 Research Outline第16-17页
Chapter 2 Basic Theory of Power System State Estimation第17-26页
    2.1 Background第17页
    2.2 Introduction第17页
    2.3 The Concept of Power System State Estimation第17-18页
    2.4 The Necessity and Function of Power System State Estimation第18-23页
        2.4.1 The Necessity of power system state estimation第18-19页
        2.4.2 Power system state estimation usage第19-21页
        2.4.3 Mathematical Description of Power System State Estimation第21-23页
    2.5 Network equations of power system第23-24页
    2.6 Power system state estimation steps第24-25页
    2.7 Summary第25-26页
Chapter 3 Modeling of Power System State Estimation第26-35页
    3.1 Introduction第26页
    3.2 Weighted least Square method (WLS)第26-28页
        3.2.1 Weighted Least Absolute Value method (WLAV)第27-28页
    3.3 Weighted Least Square Estimator第28-29页
        3.3.1 Likelihood function第28-29页
    3.4 The WLS state estimation Formulation第29-30页
    3.5 The Model of Measurement Function第30-31页
    3.6 Jacobian Matrix of the Measurement H第31页
    3.7 Weighted Least Square Estimator Algorithm第31-32页
    3.8 Weighted Least Square State Estimation Decoupled Formulation第32页
    3.9 Comparing between WLS & WLAV第32-35页
        3.9.1 Introduction第32页
        3.9.2 State Estimation with WLS第32-33页
        3.9.3 State Estimation with WLAV第33页
        3.9.4 WLS & WLAV第33-35页
Chapter 4 Modified Particle Swarm Optimization Algorithm第35-48页
    4.1 Introduction第35页
    4.2 Standard Particle Swarm Optimization Algorithm第35-39页
        4.2.1 The origin of particle swarm optimization第35-36页
        4.2.2 Principle of basic particle swarm optimization第36-39页
    4.3 Parameter analysis of basic particle swarm optimization第39-41页
        4.3.1 Inertia Weight第39-40页
        4.3.2 Acceleration Factor第40-41页
        4.3.3 Contractile Factor第41页
    4.4 maximum speed limit第41-45页
        4.4.1 The comparison between particle swarm and other algorithms第42页
        4.4.2 Several Modified methods of algorithm第42-45页
    4.5 Modified Particle Swarm Optimization algorithm MPSO第45-48页
        4.5.1 The Modified of the precocious phenomenon第45-46页
        4.5.2 Improvement of convergence speed第46-47页
        4.5.3 The MPSO concrete flow of the algorithm第47页
        4.5.4 Reactive power optimization第47-48页
Chapter 5 Simulation and Result第48-68页
    5.1 State estimation (WLS & WLAV) part第48-62页
        5.1.1 Case Study 1 on the IEEE 5 Bus system test第48-53页
        5.1.2 Case Study 2 on the IEEE 30 Bus system test第53-62页
    5.2 Reactive power optimization part第62-67页
    5.3 summary第67-68页
Chapter 6 Conclusion and Future Work第68-69页
    6.1 Conclusion第68页
    6.2 Future Work第68-69页
References第69-73页
Acknowledgement第73页

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