Abstract:This paper presents a fuzzy sliding mode controller used for switched reluctance motor speed regulation. Based on the technique of variable structure control (VSC) with sliding mode, we can construct the controller that possesses the merits of both fuzzy controller and variable structure controller. It is called a "fuzzy sliding mode controller" (FSMC). It provides a simple way to solve the main drawback of VSC by reducing the amount of chattering effect using a fuzzy control part in the proposed controller. Also, the VSC part makes the system stable which treats the main disadvantage of fuzzy controller when being used alone. The speed control simulation results are obtained by using the proposed FSMC and the traditional PI controller under different operating conditions. Also, sensitivity analyses simulation results for parameter variations are obtained to check the robustness of the system when using the proposed controller. Finally, the expermintal controlled system is illustrated for closed loop and experimental results are presented which show the validity and effectiveness of the proposed FSMC.

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One of the biggest concerns associated with incorporating a large amount of renewable energy into power systems is the need to cope with significant ramps in renewable power output. Power system operators need to have statistical information on the power ramping features of renewable generation, load, and net-load that can be used to mitigate ramping events in the case of a large forecast error to ensure the power system's flexibility and reliability; on the other hand, for economic considerations. So far, there is no consensus on a precise definition for the ramp event and so far there are hardly any metrics describing the ramping features of a power system. The paper introduces new metrics describing the power ramping features in a power system. The new metrics are ramp regularity factor (RRF), ramp intensity factor (RIF), and maximum ramp ratio (MRR). In addition, the coefficient of variation (CV) is used to characterize the average value of power ramps. The new ramp metrics are applied to the output power of Belgium's aggregated wind farms in 2017 and 2018. The results obtained by comparing the two years demonstrate that the two years have the same ramping behavior, although the average installed wind capacity has been increased. The new metrics can also be applied to other renewable sources (PV, tidal power, etc.), load, and net-load at any stage of operation.

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