Maximum power point tracking (MPPT) through an effective control strategy increases the efficiency of solar panels under rapidly changing atmospheric conditions. Due to the nonlinearity of the I–V characteristics of the PV module, the Sliding Mode Controller (SMC) is considered one of the commonly used control approaches for MPPT in the literature. This paper proposed a Backstepping SMC (BSMC) method that ensures system stability using Lyapunov criteria. A fuzzy inference system replaces the saturation function, and a modified SMC is used for MPPT to ensure smooth behavior. The proposed Fuzzy BSMC (FBSMC) parameters are optimized using a Particle Swarm Optimization (PSO) approach. The proposed controller is tested through various case studies on account of MPP’s dependence on temperature and solar radiation. The controller performance is assessed in partial shading conditions as well. The simulation results show that less settling time, a small error, and enhanced power extraction capability are achieved by applying the PSO-based FBSMC approach compared to the conventional BSMC- and ABC-based PI control presented in previous research in different scenarios. Moreover, the proposed approach provides faster adaptation to temperature and solar radiation variation, ensuring faster convergence to the MPP. Finally, the robustness of the proposed controller is validated by providing variation within the system components. The result of the proposed controller clearly indicates the lowest value of RMSE measured between PV voltage and the reference voltage, as well as the RMSE between PV power and maximum power. The results also show that the proposed MPPT controller exhibits the highest dynamic efficiency and mean power.

Independent System Operator (ISO) needs to draw sufficient attention to transmission congestion management (TCM) for guaranteeing power system security when deciding about a proposed power generation plan (PGP). To this end, this paper proposes a multi-attribute decision-making approach. The proposed decision-making procedure for a considered PGP includes three major stages: (1) Obtaining different attributes of TCM for all considered scenarios, i.e. the normal operating case and contingencies due to outage of power system components before and after implementation of the PGP. (2) Identifying the effective scenarios before and after the implementation of the PGP. For this purpose, two multi-attribute decision-making approaches are applied, one of which ISO could adopt based on its managerial point of view: (a) A conjunctive approach in which scenarios meeting minimal predefined thresholds for their obtained TCM attributes are selected. (b) A pessimistic approach based on data envelopment analysis introduced by Charnes, Cooper, and Rhodes (CCR-DEA) in which the severest scenarios are selected. 3) Calculating each scenario's Degree of Severity (DOS) using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and comparing sum of the DOS of the effective scenarios before and after the implementation of the PGP. For an acceptable PGP, sum of effective scenarios' DOS after implementation of the PGP should be less than that of before. The proposed procedure is applied to the IEEE Reliability Test System (RTS) and the results are analyzed. Copyright © 2014 John Wiley & Sons, Ltd.