The unevenness of the electricity consumption schedule at enterprises leads to a peak power increase, which leads to an increase in the cost of electricity supply. Energy storage devices can optimize the energy schedule by compensating the planned schedule deviations, as well as reducing consumption from the external network when participating in a demand response. However, during the day, there may be several peaks in consumption, which lead to a complete discharge of the battery to one of the peaks; as a result, total peak power consumption does not decrease. To optimize the operation of storage devices, a day-ahead forecast is often used, which allows to determine the total number of peaks. However, the power of the storage system may not be sufficient for optimal peak compensation. In this study, a long-term forecast of power consumption based on the use of exogenous parameters in the decision tree model is used. Based on the forecast, a novel algorithm for determining the optimal storage capacity for a specific consumer is developed, which optimizes the costs of leveling the load schedule.

Marine renewable sources can make a significant contribution to the development of electrical energy generation and can increase the power supply reliability of mineral complexes. The development of alternative energy sources is happening at a fast pace, and this is due to the improvement of technologies that allow for generating more energy and operating in more extreme conditions, with almost no negative effect on the environment. However, currently, renewable sources are not able to meet all the energy requirements of the platforms. Hence, a key point is to gradually introduce and develop new technologies. This article explores the advantages of combining power generation by wave converters and offshore wind turbines. It investigates the possibilities of improving the combined systems’ reliabilities through justification of their mutual topology and accounting for the shadow effect from the wave installations.

The microgrid is an emerging trend in modern power systems. Microgrids consist of controllable power sources, storage, and loads. An elaborate control infrastructure is established to regulate and synchronize the interaction of these components. The control scheme is divided into a hierarchy of several layers, where each layer is composed of multi-agents performing their dedicated functions and arriving at a consensus of corrective values. Lateral and horizontal interaction of such multi-agents forms a comprehensive hierarchical control structure that regulates the microgrid operation to achieve a compendium of objectives, including power sharing, voltage, and frequency regulation. The success of a multi-agent-based control scheme is dependent on the health of the communication media that is used to relay measurements and control signals. Delays in the transmission of control signals result in an overall deterioration of the control performance and non-convergence. This paper proposes novel multi-agent moving average estimators to mitigate the effect of latent communication links and establishes a hierarchical control scheme incorporating these average estimators to accurately arrive at system values during communication delays. Mathematical models are established for the complete microgrid system to test the stability of the proposed method against conventional consensus-based methods. Case-wise simulation studies and lab-scale experimental verification further establish the efficacy and superiority of the proposed control scheme in comparison with other conventionally used control methods.

The efficiency of electrical complexes depends directly on the level of power supply system reliability, which comprises extensive and branched distribution networks. A complex of single-phase ground fault (SPGF) relay protection and automation devices (RPA) is used to reduce the economic losses from the failure of the electrical receivers’ distribution networks. This paper presents a study of the protection sensitivity factor, taking into account the influence of the network capacity and the resistance during a fault. The results of this study determined the minimum permissible values of the sensitivity factor that ensures the stable operation of the protection device. This was achieved by taking into account the influence of the transient resistance at the point of short circuit. The practical significance of the study is as follows: the obtained characteristics will allow for the development of new functional logic circuits for SPGF protection. The practical implementation of the obtained results will allow for the following: to increase the sensitivity and selectivity of current non-directional protections in conditions of incomplete short circuits; to ensure the reliable functioning of technological equipment and responsible consumers; to reduce the level of electrical injuries of service personnel; and to reduce economic losses associated with the repair of damaged electrical receivers.

To protect power lines, distance relays are used which can rely on a modified distance resistance. But usually the operating range of these relays changes as the network conditions change (network topology, load value, output value, etc.) and leads to false trips, by using methods that can process information and recognize patterns. For example, the use of micro and intelligent processor algorithms can use the new relays with high precision and thus provide adequate protection. In this study, a distance relay was modeled using a neural network, and it was observed that the neural relay had higher accuracy than the conventional relay. In addition to detecting the fault and its location, type and phase of the fault, three-stage simultaneous protection can be performed. As a result, the number of linear relays can be reduced by using relays based on neural technologies. An MLP (multilayer perceptron) neural network is used to model a sequence of distances.

The article highlights and optimizes a controller for the single ended primary inductance converter (SEPIC) direct current-direct current (DC-DC) converter. The SEPIC converter adjusts a range of dc input voltages and delivers a constant and stable output voltage. Three different models of the SEPIC converter are presented in order to derive its transfer function. Being a 4th order, an approximation method for the reduction of this transfer function to 2nd and 1st order is implemented. Two methods for controlling the converter are presented, the first one is based on guessing techniques and the second explains the design steps of the controller based on the internal model control (IMC). Furthermore, an improvement on the IMC controller is proposed and results were shown and discussed. IMC is based on integrating the “process model” in the control operation of the actual system. By using an approximation of the original transfer function of the system, it is expected that the IMC control will be able to achieve the desired results. Control schemes of the SEPIC will be presented and results will be shown. The response of the controller was tested with mathematical models for batteries and supercapacitors in MATLAB, as non-ideal DC-sources, and results were presented.