Research On The Comprehensive Evaluation Model Of Power Quality For The Wind Power Integration

Power quality directly affects the quality of people’s lives and the overall effectiveness of the national economy. In today’s China to develop wind power in the background to detect and evaluate scientific and reasonable power quality of wind farms, and objectively and accurately measure the merits of its power quality, power quality for the promotion of comprehensive management, continue to meet the electricity needs of users, improve wind power capacity, and promote the healthy development of the wind power industry has great significance.Firstly, on the base of the analysis of wind power’ operating characteristics and the importance of power quality, discusses the important indicators of power quality that are easy to have an impact on the network, these indicators include:voltage deviation, voltage fluctuations, harmonic voltage, phase several aspects of voltage unbalance, voltage fluctuation and flicker; and were discussed the causes and hazards of different indicators and network impact, drawing on international and domestic standards of power quality evaluation, constructed wind farm power quality specific evaluation indicators for research laid the foundation for the subsequent chapters.Secondly, based on the security of the grid after heavy ordered weighted averaging operator and ordered weighted geometric average operator principle, determine the location of the order of index data through gray correlation analysis method, using the decision-making laboratory analysis to determine the different locations of the power quality, enabling the wind farm power quality comprehensive evaluation. The method was applied to various monitoring points in a large wind farm China’s power quality analysis and evaluation, the validity of the method.Thirdly, for the wind farm power quality evaluation of the uncertainty of each index, the set pair analysis theory is applied to power quality comprehensive evaluation. First evaluation samples by contacting the calculation and evaluation between a preliminary classification of the samples, and then further on the same sample, differences, opposing sets of analyzes to determine level of evaluation samples. In determining each index weights, the information theory entropy theory is introduced to the model, using information entropy utility value as reflected in the measured data to calculate the weight of each evaluation index weight, so the weight distribution has a theoretical basis. Finally, through case studies, to determine the set of entropy-based analytical model for the evaluation results are reasonable and objective.Finally, based on cloud matter element model based on a fuzzy neural network power quality of wind farms were evaluated, and then by comparing the results of the four models to verify the differences between the different evaluation methods and their effectiveness. Evaluation examples show the power quality comprehensive evaluation method combining subjective and objective weights can be considered comprehensive power quality evaluation, grid-based power quality evaluation side; set based theory of entropy in information theory for analysis of energy comprehensive evaluation method to achieve a comprehensive evaluation of the quality of the power quality evaluation methods with a strong practical and targeted, with high credibility.