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Prompt attitude stabilization is more challenging in Nano CubeSat due to its minimal capacity, weight, energy, and volume-constrained architecture. Fixed gain non-adaptive classical proportional integral derivative control methodology is ineffective to provide optimal attitude stability in low earth orbit under significant environmental disturbances. Therefore, an artificial neural network with fuzzy inference design is developed in a simulation environment to control the angular velocity and quaternions of a CubeSat by autonomous gain tuning of the proportional-derivative controller according to space perturbations. It elucidates the dynamics and kinematics of the CubeSat attitude model with reaction wheels and low earth orbit disruptions, i.e., gravity gradient torque, atmospheric torque, solar radiation torque, and residual magnetic torque. The effectiveness of the proposed ANFIS-PD control scheme shows that the CubeSat retained the three-axis attitude controllability based on initial quaternions, the moment of inertia, Euler angle error, attitude angular rate, angular velocity rate as compared to PID, ANN, and RNN methodologies. Outcomes from the simulation indicated that the proposed controller scheme achieved minimum root mean square errors that lead towards rapid stability in roll, pitch, and yaw axis respectively within 20 s of simulation time.

This paper presents a fuzzy-logic-based framework for aging mitigation of distribution transformers. At the first stage, a model for loading estimation of a transformer installed in the head of a power distribution network was developed in the MATLAB-Simulink environment. The model considers several factors that negatively affect the transformer's operation and lead to overheating of its windings, including high ambient temperatures, harmonic voltage distortions generated by nonlinear loads, reverse power flows, overloads due to high penetration of plug-in electric vehicles. At the second stage, a tuning algorithm was developed and measures aimed at optimizing the transformer's load level and power factor were elaborated. The developed model analyzes the parameters and factors that affect the normal operation of the transformer, and warns of the presence of dangerous factors that pose a threat to reliability and can lead to malfunction. Moreover, the effectiveness of photovoltaic generation units, shunt capacitor banks and battery energy storage systems, installed at the secondary voltage side, for distribution transformers' lifetime preserving were analyzed and discussed. The proposed measures allowed to reduce the transformer's loss of life more than 7 times, compared to the initial scenario.

The article is devoted to solving the problem of managing the mode parameters of an urban electrical network in case of a discrepancy between the actual electrical load and the specific load. Such an issue leads to a deviation of the parameters, in particular, voltage asymmetry in phases due to current asymmetry. To optimize the mode parameters, it is required that the effective value of the electrical load corresponds as much as possible to the values of the specific electrical load. This depends on the following: actual power consumption, external (climatic and meteorological) factors, internal factors (structural design of residential buildings, uneven load when distributed over the phases of three-phase lines and inputs, different number of electrical receivers for consumers), and the provision of consumers with other sources of energy (both gas and heat supply, and hot water supply). To establish the influencing factors on the actual power consumption, it is proposed to generalize the uncertainty accounting coefficient which generalizes both more well-known and less considered factors. Therefore, the authors propose models for determining the electrical loads based on the possibility of assessing the mode parameters of the electrical network by electrical loads. The accuracy of the proposed models is based on the use of the proposed forecasting method considering the actual power consumption and the generalized uncertainty coefficient. Applying the obtained data based on models of electrical loads to the constructed model of a part of a distribution electrical network with real parameters of the electrical network in the MathWorks Simulink environment, the correspondence to the mode parameters of the distribution electrical network is determined. As a result, a device for balancing the voltage depending on the load asymmetry is proposed that is related to the discrepancy between the mode parameters allowing control of the mode parameters by bringing them to acceptable values.

Many problems arise in the operation of photovoltaic systems. Each of these problems affects the operation of photovoltaic systems by reducing the power of the entire system. Some problems can be avoided during the design of photovoltaic systems. For example, when designing photovoltaic systems, it is possible to eliminate the shading of photovoltaic panels from surrounding objects. It is also necessary to look at the shading from neighboring photovoltaic panels when designing photovoltaic systems. It is necessary to calculate the inclination of the sunlight based on the position of the sun and calculate the distance between the two panels accordingly. However, some problems appear during the operation of photovoltaic systems. These problems can be partially eliminated. The magnitude of the series resistance can be eliminated by reducing the transition resistance throughout the system. The paper describes these problems and their possible solutions in practice. In the practical part, we focused on simulations and experiments in the field of photovoltaic systems (PV). The simulations focused on both the influence of temperature and the series resistance of photovoltaic panels on the production of electricity. The experiments were focused on the influence of various faults/defects on the power and V-A characteristics of photovoltaic panels connected in strings. The paper also discusses the impact of bypass diodes on the operation of photovoltaic systems and determines the need to use bypass diodes.

Due to high electricity prices and possible shortages of gas and other energy commodities, various fluctuations in electricity generation will need to be regulated. Given the increasing expansion of wind power plants in Europe and worldwide. It is necessary and essential to put power regulation into practice, as mandated by regulation 2016/631 EU. A significant power balance problem may arise on the grid, which may lead to cyclical and recurring blackouts in the future. The motivation for this paper is to raise awareness of the controllability of wind turbines and to highlight the gentle pace of research in this area for pitch angle control. Therefore, the chief idea of the paper is to develop a proposal for wind power plant power control by changing the rotor blade rotation, following previous research in this area, and determining the shortcomings and possibilities. The paper provides a numerical method for controlling the power output of a wind power plant, for which an algorithm has been proposed. This control is intended to provide a framework for the design and implementation of a wind power plant control program. Coordination between the multiple sources will fulfil a leading role in smooth power management.

This article addresses the reduction of power losses in smart grids. Two optimization algorithms are used in this article. The first method is the enumerative method. The second method of the optimization calculation is based on the self-organizing migrating algorithm. In the first step, the network parameters are calculated based on the input data, and then the target function is determined. In this article, the target function is used to reduce the active power losses that occur during the operation of an electric network. More specifically, we attempt to determine the reactive power with the enumerative and SOMA algorithms to reduce the value of the active power losses. This article intends to illustrate the differences between the selected optimization algorithms. As observed, the optimization algorithm determines the computation time.

The world demands a smart and green future in every sector, which directly corresponds to increases in electrical energy demand one way or another. It is unfeasible to attain future energy demand with the present electrical infrastructure. That means more research and development is required. Future energy sources should be intermittent, and, in addition, the energy sector should be more inwards for distributed energy generation with demand side control. In such cases, the smartest and most autonomous system would be essential to deliver an adequate power supply with all electrical properties. A real-time monitoring and control system with a self-healing infrastructure is a forthcoming desideratum. By accepting these challenges, we have designed a smart street. The basic idea of the smart street is presented in this paper as a landing page; the paper is more focused on emphasizing information regarding the electrical energy flow algorithm for the household, street, and street battery storages. This algorithm is helpful for two-way energy flow and the automatic detection of islanding and the grid connection mode. It will be not only helpful for the users but to the utility as well.

One way of handling short-time short-circuits without causing equipment failure is the management of the reclose function integrated into smart switchboard which is described in this article. Due to the cost of the application, the optimal placement of such equipment must be well-planned. During the planning of the placement optimization of a low-voltage electricity network quality, the increase of the consumer supply security must be considered along with the best economic utilization. The research presented in this article aims to introduce a new special decision support methodology calculated with these variables. The management of smart switchboard (SSB) tool installation into low voltage (LV) network was investigated. The selection of the placement nodes is based on the complex investigation of the network characteristics. Investigation is performed by empiric analysis. This method can support the power companies to make the optimal decision. The presented new device can have outstanding importance for the electric industry and for further research as no testing results of such investigations have been published yet.