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This paper investigates the modeling, simulation and implementation of a wind power system based on a Permanent Magnet Synchronous Generator (PMSG). A comprehensive portfolio of control schemes are discussed and verified by Matlab/Simulink simulations, in the context of grid integration and Maximum Power Point Tracking (MPPT) operations. Particularly, to investigate the Fault-Ride-Through (FRT) and robustness capabilities, various wind speed scenarios and a line voltage droop are introduced to the wind power system to investigate its dynamic performance. A reference power curve, i.e., power versus generator speed, is employed in the turbine model to implement the MPPT. In addition, a position/speed sensorless operation approach based on Sliding Mode Observer (SMO) is implemented to reduce system cost and improve control reliability. Simulation and experimental results demonstrate the robust control of the power and speed in the PMSG wind power systems.

In this paper, a combined contract composed of option and cost sharing is proposed to investigate coordination and risk‐sharing issues of the supply chain consisting of a dominant retailer and a risk‐averse manufacturer. Demand faced by the retailer is stochastic in nature and dependent on marketing effort. We adopt the conditional value‐at‐risk (CVaR) criterion to model risk aversion of the manufacturer, and derive the optimal strategy for each member with a Stackelberg game in which the retailer acts as the leader. It is verified that the combined contract can coordinate the supply chain and achieve Pareto‐improvement. Moreover, the dominant retailer can allocate the system‐wide profit arbitrarily only by option price in the premise of coordination. It is worth mentioning that coordination of the supply chain is reachable only when the manufacturer is low in risk aversion, and the manufacturer's risk aversion is a significant element for contract design and profit allocation.