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The Research Of Hybrid Compensation System Of Reactive Power And Negative Sequence For High-speed Railway Traction Supply System Based On AIMAS

Posted on:2014-07-14Degree:DoctorType:Dissertation
Country:ChinaCandidate:C CaiFull Text:PDF
GTID:1222330425967630Subject:High Voltage and Insulation Technology
Abstract/Summary:PDF Full Text Request
High-speed railway for its efficient, fast, safe, energy-saving, environmental protection and other advantages becomes a green form of transportation that countries scramble to develop. At present, there are nearly thousands of kilometers of high speed railways operating in our country, therefore, China owes the world’s longest and highest-speed railway network. Compared to conventional electrified railway locomotives, China’s high-speed railway trains adopt advanced technology, superior performance of high-power "AC-DC-AC " traction drive system, so it has some advantages such as high power factor and a few of harmonic. But high-speed railway locomotive is a single-phase heavy load, possessing the characteristic of instability and asymmetry, which can cause serious unbalanced three-phase power system problems in operate.In order to solve the power quality problem brought by high speed railway, this paper proposes a hybrid reactiveand negative sequence current compensation system, which is based on MSVC(Magnetic control static var compensator) of a large capacity and RPC(Realwaystatic power conditioner) of a small capacity.While MSVC is responsible for compensating most of the negative sequence current and a little reactive current, RPC is mainly responsible for the variation of negative sequence current induced by load’s quick fluctuation. If load’s unbalanced current exceeds the capacity of MSVC, RPC will compensate the rest. Since the conventional TCR(Thyristor controlled reactor) is characterized by large harmonics and high cost, the MSVC adopted in this paper is made up of low cost MSMCR(Multi-Stage Saturable Magnetically Controllable Reactor) paralleled with a LC filter. Output harmonics canbe effectively reduced as a result of the segmented saturation characteristic of different magnetic valve section. Meanwhile, this paper proposes an RPC in BKB structure based on MMC(Modular Multi-level Converter), which overcomesthe low withstand voltage problem of a conventional converter, improves the quality of waveform of current and voltage, makes up for MSVC in active responsible characteristic and reduces the compensating capacity of MSVC.This paper, based on the principle of hybrid reactive and negative sequence compensation, builds the math model of compensation system on the premise of meeting the state and industry standard of power quality, and obtain the smallest install capacity of MSVC under different capacity of RPC by the derived optimizing compensation strategy. When allocate the capacity of RPC under the largest traction load of a single train, the total install capacity of MSVC after optimizing can be reduced by54%, improves the economic characteristic further more.Besides, considering the compensate target for a single site will cause great problems of idle capacity and ignoring the negative sequence component offset effect between the neighboring sites, an immune algorithm and multi-agent system are developed for the compensation around multi-sites of a high-speed rail network in this paper. The presented system not only effectively compensates the three-phase current in220kV power supply system and meets the power quality requirement, but also significantly reduces the capacity of compensation devices and improves the efficient use of each compensation units.Finally this paper built hybrid compensation system simulation model based on the MATLAB simulink software and the high-speed railway hybrid reactive power compensation system experimental platform in the low pressure laboratory environ-ment. Simulations and experiment results related verify the correctness of the theory proposed in this thesis.
Keywords/Search Tags:High-speed Railway, MSMCR, RPC, Negative Sequence Compensation, Optimized Algorithm, Artificial immune, Multi-agent system
PDF Full Text Request
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