Iranian Journal of Electrical and Electronic Engineering

Locational Marginal Pricing (LMP) is a method for energy pricing in deregulated power systems. Loss and congestion cause different prices for energy at load or generation buses. In this pricing method there is a different between payments of customers and revenue of generators which is called Merchandizing Surplus (MS). Independent System Operator (ISO) receives MS and generally renders it to Transmission Company (Transco). It is rational that the MS be allocated among power market participants fairly instead of granting whole MS to Transco. In this paper a novel method is proposed to allocate MS among market participant according to their role in the congestion of system. In the presented method by decomposing LMP and identifying congestion part of LMP, the part of generators’ revenue and customers’ payments which caused by congestion are calculated. Then MS is allocated among market participants as the payment of customers to be equal to revenue of generators. The proposed method has been tested on five bus test system. Results indicate the effectiveness of the proposed method to allocate MS between power market participants.

A novel nonlinear controller is proposed to track active and reactive power for a Brushless Doubly-Fed Induction Generator (BDFIG) wind turbine. Due to nonlinear dynamics and the presence of parametric uncertainties and perturbations in this system, sliding mode control is employed. To generate a smooth control signal, dynamic sliding mode method is used. Uncertainties bound is not required in the suggested algorithm, since the adaptive gain in the controller relation is used in this study. Convergence of the sliding variable to zero and adaptive gain to the uncertainty bound are verified using Lyapunov stability theorem. The proposed controller is evaluated in a comprehensive simulation on the BDFIG model. Moreover, output performance of the proposed control algorithm is compared to the conventional and second-order sliding mode and proportional-integral-derivative (PID) controllers.