Outliers and outlier detection are among the most important concepts of data processing in different applications. While there are many methods for outlier detection, each detection problem needs to be solved with the method most suited to its unique characteristics and features. This paper first classifies different outlier detection methods used in different fields and applications to provide a better understanding, and then presents a new fuzzy method for outlier detection. The proposed method uses the fuzzy logic and the local density to assign a point to data instances, and then determines whether a piece of data is normal or outlier based on the value of resulted membership function. Evaluation of the proposed outlier detection algorithm with synthetic datasets demonstrates its good accuracy; moreover, evaluation of the performance in solving real datasets show that the proposed method outperforms the k-means and K-NN algorithms. تفاصيل المقالة

In this paper, a novel reconfiguration approach for distribution network incorporating distributed generation is introduced aiming to minimize power losses and energy supply costs. Given the temporally variable consumption of residential, industrial and commercial loads and the time-variant energy prices, an hourly reconfiguration scheme for an entire daily cycle is proposed. Also considering the privately-owned nature of distributed sources, the energy supply is carried out within a competitive market. The optimization is based on grey wolf algorithm (GWO), implemented in MATLAB software on an IEEE 33-bus test network. The simulation is done for four scenarios with respective objective functions for the evaluations of the results thereof. By comparing the obtained results it is concluded the configuration of network will be the unique for each of objective function. Finally, the effects of switching at different hours of day are compared in terms of loss minimization and supply costs against single daily switching scheme. تفاصيل المقالة

Microgrids (MGs) contain a diverse mix of energy resources to provide safe and secure power to the consumers. Batteries are utilized in MGs for further energy security assurance as well as cost minimization. In this paper, an efficient approach is introduced for simultaneous energy management and optimal battery sizing to accomplish economic MG operation. Also, demand response programs are employed to further reduce MG operation costs (OCs) and strike a balance between supply and demand. The objectives sought in this context are the optimal values for DG generation levels, level of consumer participation and the respective incentive payments, battery charge and discharge levels and the amount of power exchange with upstream network within a 24-hour scheduling cycle so as to minimize OCs and maximize MG operator’s (MGO) profit as a result of demand response. In order to address the hybrid energy management system (EMS) and battery sizing problem, the proposed model is solved using whale optimization algorithm (WOA) in MATLAB software for a grid-connected MG. The results indicate that battery charge and discharge is significantly lowered through optimal battery sizing incorporated into the proposed approach. تفاصيل المقالة