The Filter Optimal Allocation In The Distribution Network On The Multi-harmonic Source Mutual Influence

With the requirements of environmental protection, energy conservation andsustainable development, more and more new energy power have had access to powersystems. The application of a large amount of power electronics technology makes theharmonic source of electricity network spread from the traditional load of electricityto the power supply, which constitutes the multi-harmonic sources of electricitynetwork and injects a large quantity of harmonics to the power system. Harmoniccurrents interact with each other at the point common coupling, resulting in thephenomenon of offset, attenuate or superimpose, and so on, and the properties ofharmonic spectrum change. In order to suppress the damages to the power systemcaused by the harmonics, this thesis studies the optimal allocation of the filter in thecontext of the interaction of harmonic sources.In this thesis, harmonics of different frequency, amplitude and phase areanalyzed through superimposing and emulating by using MATLAB/simulink, and thelaw of harmonic waveform spectrum after the interaction among harmonics isobtained. By estimating the states of harmonics, the type, location and the number ofthe uncertain harmonic sources are found. And the principle of resonance phenomenaand the resonance detection method are analyzed. The parallel resonance is analyzedaccording to the impedance spectrum curve made by inverse of the eigenvalue of thenodal admittance matrix, while the series resonance is based on adding virtual sliploop impedance.The classification of the filtering devices and their advantages and disadvantagesin engineering applications are introduced briefly in this thesis. In order to suppressharmonic safely, economically and effectively by filtering devices, the mathematicalmodel of the objective function and constraint condition are build on the basis of theanalysis of the filter devices and system parameters. The improved particle swarmoptimization (PSO) is adopted by the improved particle swarm optimization algorithm.According to the relationship of the parametric speed v and the inertia factorωofPSO, the method of time-variant nonlinear trigonometric function is proposed tocontrol the parameters as a result of accelerating the convergence speed andpreventing from falling into local optimum. Finally, three programs of the bestfiltering effect, the optimum economical outcome and both of the previous two are put forward to optimize the allocation of the filter. At the same time, considering theuncertain harmonics’impact on the filtering devices and that whether they willperform resonance with the system, the principle of resonance detection method isadopted to validate the filter parameters and locations. And the effectiveness ofparameters and location of the filter device configured by the improved particleswarm optimization algorithm is verified by MATLAB simulation.