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Based on a region does not have type reactive power adjustment ability of doubly-fed wind power as the research object, analyzes the wind farm reactive power compensation problem, based on MMC - STATCOM reactive power compensation scheme is proposed, and based on this, puts forward the reactive power compensation control strategy based on fuzzy control theory Is verified by the simulation analysis, the control strategy of reactive power compensation scheme and the feasibility and effectiveness.

The rapid development and large-scale utilization of clean energy is not only conducive to alleviate the global fossil energy crisis, but also brings huge economic and environmental benefits. However, the uncertainty of new energy represented by wind power and photovoltaic power brings a lot of impact on the operation and dispatching of the power system. Hence, it’s urgent to explore a new dispatching mode adapted to the power system with high proportion of clean energy. The optimal dispatching method of power system with high proportion clean energy based on multi-energy complementarity is explored with goal of making full use of clean energy and reducing the operating cost. Particle swarm optimization algorithm and branch and bound method are used to solve the cascade hydropower optimal dispatching problem and the wind, photovoltaic, thermal power joint optimal dispatching problem respectively. Finally, the feasibility of the model is verified by an example.

With the trend of increasing dimensions of collected power load data, the data dimension reduction and classification become essential pre-processing steps for data mining and further application. On the basis of adaptive piecewise aggregate approximation(APAA) and k-Shape algorithm, a novel method is proposed. In light of the fluctuation degree and shape characteristics of the original load profiles, the new load dataset with variable temple resolution replace the old one by APAA, and further k-Shape algorithm is adopted for lower dimension load profiles clustering. K-Shape algorithm cluster curves with distance SBD as similarity measurement and also a novel method to extract the representative centroids is mentioned. The experiment testifies that APAA-kShape algorithm has shorter calculating time, higher accuracy and represent better load patterns than other cluster algorithms.