With the increasing penetration of wind power into electric power grids, energy storage devices will be required to dynamically match the intermittency of wind energy. This paper proposes a novel two-layer constant power control scheme for a wind farm equipped with doubly fed induction generator (DFIG) wind turbines. Each DFIG wind turbine is equipped with a supercapacitor energy storage system (ESS) and is controlled by the low-layer wind turbine generator (WTG) controllers and coordinated by a high-layer wind farm supervisory controller (WFSC). The WFSC generates the active power references for the low-layer WTG controllers according to the active power demand from or generation commitment to the grid operator; the low-layer WTG controllers then regulate each DFIG wind turbine to generate the desired amount of active power, where the deviations between the available wind energy input and desired active power output are compensated by the ESS. Simulation studies are carried out in PSCAD/EMTDC on a wind farm equipped with 15 DFIG wind turbines to verify the effectiveness of the proposed control scheme.

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Abstract-This paper proposes a comprehensive framework for multiobjective design optimization of switched reluctance motors (SRMs) based on a combination of the design of experiments and particle swarm optimization (PSO) approaches. First, the definitive screening design was employed to perform sensitivity analyses to identify significant design variables without bias of interaction effects between design variables. Next, optimal third-order response surface (RS) models were constructed based on the Audze-Eglais Latin hypercube design using the selected significant design variables. The constructed optimal RS models consist of only significant regression terms, which were selected by using PSO. Then, a PSObased multiobjective optimization coupled with the constructed RS models, instead of the finite-element analysis, was performed to generate the Pareto front with a significantly reduced computational cost. A sample SRM design with multiple optimization objectives, i.e., maximizing torque per active mass, maximizing efficiency, and minimizing torque ripple, was conducted to verify the effectiveness of the proposed optimal design framework.Index Terms-Design of experiments (DoE), multiobjective optimization, particle swarm optimization (PSO), response surface (RS), sensitivity analysis, switched reluctance motor (SRM).

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