Abstract

Comparing with traditional substation, the reactive power compensation devices used in smart substation need to be more flexible and dynamical, and the control result is not usually effectively that the parallel capacitor device used in traditional substation. Along with the development of FACTS technology, the dynamic reactive power compensation device which can achieve dynamic and real-time compensation is being gradually applied in smart substation. In order to realize the economic investment and real-time compensation ability, it is needed to configure that both of two devices been used in smart substation. Traditional optimal covering method is based on the analyzing of capacitor grouping under differential load level, but it is hard to considering with the coordination means of various compensation devices. Meanwhile, by means of global optimization method, it is difficult to handle the complex models such as multi-objective optimization. Therefore, the traditional optimal covering method needs to be improved by considering with the dynamic reactive power compensation device that coordinating covering in probability load curve together with the capacitor group. At the same time, it needs to be improved by constructing the objective function of minimized uncovering area (mismatch area) which will be used to establish the multi-objective optimization mathematical model together with the investment cost function, converting the multi-objective optimization model to the single objective function of minimized economic indicators, using the intelligent algorithm to optimizing calculate the mathematical model for reactive power optimization configuration scheme of smart substation. In the end, the actual data of one smart substation in state grid are adopted for example analysis and the Static VAR Compensation(referred SVC) and Static Synchronous Compensation(referred STATCOM) are chosen as the dynamic reactive power compensation device to configure the reactive power together with the capacitor group. The results verify the effectiveness and applicability of configuration method.

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