Recently, due to the global competition companies active in different industries started to be concerned about the customer churn. With a churn rate of 30%, the telecommunications sector takes the first place on the list. The telecommunications operators need to identify customers who are at risk of churning by implementing predictive models. In this paper, we present an advanced data mining methodology which predicts customer churn in the pre-paid mobile telecommunications industry using a call details records dataset that consists of 3333 customers with 21 attributes each. We first apply the principal component analysis algorithm to reduce the dimensionality of the data and eliminate the problem of multicollinearity. To implement the predictive models, on the resulted principal components and discrete variables we initially propose and then apply three machine learning algorithms: neural networks, support vector machines, and Bayesian networks. To evaluate the models, we use the confusion matrix, the gain measure and the ROC curve.

In a context with an increased level of competitiveness, companies are more and more interested in aspects concerning sustainable development. The implications of inadequate power quality (PQ) can determine important financial losses and influence companies’ sustainable development through the generated effects. This article aims to facilitate the management of PQ by proposing a method for estimating the economic consequences of a poor PQ, with priority for the disturbances with significant economic effects. To determine the total cost for each type of PQ perturbation that may occur a classification of cost categories was made such as interruptions, process slowdowns, equipment failure, equipment downtime, reduced energy efficiency, lower product quality, lower labor productivity, and other indirect costs. Each PQ disturbance affects the final end-user differently. For calculating the total value for each type of PQ issues, different calculation formulas have been proposed so that each perturbation includes only those components associated with that perturbation. A case study was used to validate the proposed method. Also, the paper includes a technical and economic analysis of the possible compensation solutions for PQ disturbances that may affect the studied company. In conclusion, an understanding of PQ issues’ consequences and an appropriate approach to PQ compensation solutions can be beneficial to any electrical power end-user.

In the case of adjustable drives systems with an induction motor (IM), a harmonic regime is manifested, whose knowledge and analysis are always necessary. However, most studies are focused on specific drive systems, the results of these works being valid only for drive systems of the same type. The objective of the present paper was to determine the harmonics consequences not only on the technical characteristics of the IM but also on the power supply as well as on the mechanical drive system. Thus, by initiating a methodology for estimating the consequences of each voltage harmonic separately, the aim was to substantiate a generally applicable method, which allows the evaluation, for any application, of the overall effects of the harmonics. The main feature of the method used in this paper was the consideration of the presence of voltage harmonics in the stator voltage of the IM, of certain frequencies and with certain levels, and the determination of all the electrical and mechanical consequences on the model of the drive system. It has been found that the harmonics of the IM affects the power quality (PQ) of the power supply, having significant influences also on the mechanical part of the drive system.

Fuzzy-based control systems have demonstrated a remarkable ability to control nonlinear processes, a characteristic commonly observed in power systems, particularly in the context of power quality enhancement. Despite this, an updated and comprehensive literature review on the applications of fuzzy logic in the domain of power quality control has been lacking. To address this gap, this study critically examines published research on the effective and efficient use of fuzzy logic in resolving quality issues within power systems. Data sources included the Web of Science and academic journal databases, followed by an evaluation of target articles based on predefined criteria. The information was then classified into seven categories, including control system type, features of the fuzzy logic controller, fuzzy logic inference strategy, power quality issue, control device, implementation methodology (efficacy testing), and efficiency improvement. Our study revealed that fuzzy-based control systems have evolved from simple type-1 fuzzy controllers to advanced control systems (type-2 fuzzy and hybrid) capable of effectively addressing complex power quality issues. We believe that the insights gained from this study will be useful to both experienced and inexperienced researchers and industry engineers seeking to leverage fuzzy logic to enhance power quality control.

In contemporary society, electricity has become one of the most prevalent energy sources, with a global distribution network. The significance of energy efficiency has become a prominent subject of interest across various disciplines, leading to a notable surge in research on electricity over the last decade. The present paper explores the significance of examining power losses in power grids and proposes methods to identify and reduce them. The objective of this study is to methodically and systematically review existing databases to identify relevant studies pertinent to electricity losses in power grids. To this end, this study methodically categorizes energy losses into two primary classifications: technical losses and non-technical losses. To this end, two primary analytical approaches have been devised, providing a foundation for the prioritization of the most effective detection methods for each loss category, as well as the most recent findings in the literature on reducing these losses. The issue of power grid instability, stemming from fluctuations and voltage dips, was addressed, with power losses emerging as the primary source of concern. To this end, a comprehensive analysis of major academic databases, including Scopus, Web of Science, IEEE, and Google Scholar, was conducted to identify relevant research articles. This review introduces several important concepts for the energy field by introducing and analyzing the most relevant methods to identify and reduce power losses. The results of our study outlined the comprehensive analysis of 90 relevant studies on the benefits as well as the barriers encountered in the application of methods to identify and reduce electricity losses and the impact they have in the field under review. In conclusion, this paper emphasizes the importance of the in-depth study of the energy domain to achieve performance and contribute to the improvement of power grids. Future research directions are based on the implementation of artificial intelligence (AI) algorithms to achieve this goal.

The design methods of earthing from standards recommend the choice of electrode lengths and propose that the distances between electrodes to be 1–3 times larger than their length. The number of electrodes is determined from the condition of achieving the design earth resistance, while the design ends with the choice of one of the variants. This paper presents the methodology for calculating the earthing system with cylindrical, vertical electrodes arranged in a line. The main variables are the length and the number of earth electrodes, as well as the distance between adjacent ones. Firstly, a set of technologically advantageous values for the earth electrode length is established (e.g., 10 values). For each value of the electrode length and different numbers of electrodes (e.g., 11 values), the distance between adjacent electrodes is determined (e.g., for 110 cases), which leads to the design value resistance. Finally, optimal solutions are identified based on the five optimal applied criteria. The proposed optimal criteria for earthing design are the footprint area, the total earthing volume, the total dispersion surface, the total metal mass, and the investment costs. Comparing the optimal solutions with other technically possible solutions clearly highlights substantial savings concerning space, material, and cost.