+This paper has considered improving the management of energy consumption by a photovoltaic system with a storage device for a local object connected to the network. The aim of the study is to reduce expenditures when paying for electricity consumed from the network, when loading an object, independent of the time of year, and to eliminate energy generation to the grid. An energy generation control algorithm has been improved whereby the state of battery charge during the day is based on a forecast. That could reduce electricity consumption at night with better utilization of rechargeable battery and photovoltaic battery power during the day. It is proposed to use autonomous operation by disconnecting from the network during peak tariff hours and during the day with enough energy generation by a photovoltaic battery. This would ensure the normal functioning of an object in the event of a possible deterioration in the quality of voltage in the network while reducing the loss of energy in the inverter. Predictive control of the expected battery charge at the next checkpoint (at 0.5 hours or less between control points) has been proposed. A control system structure has been developed whereby a rechargeable battery current is set depending on an operational mode, the tariff zone, and the projected generation by a photovoltaic battery while reducing the modulation frequency under an autonomous mode. In this case, the modes are switched and the structure is changed taking into consideration the state of battery charge. Simulation in the daily cycle has shown the possibility of reducing the cost of electricity consumed from the network by 1.7‒8 times at two or three tariff rates. Simulation of electromagnetic processes in the system confirms acceptable regulation indicators when switching the structure, as well as a decrease in the energy loss in an inverter under an autonomous mode by up to 40 %
source inverter (VSI) that combines the functions of an active power filter (APF) [2]. This contributes to increasing the utilization factor of CU due to its round-the-clock use [2-5] to maintain the maximum (close to one) power factor at the PCC to DG. The result is reduced load and energy loss in the DG. It is also possible to provide an autonomous mode of operation during the daytime [2, 3], stabilization of the load voltage [4]. Thus, improving the indicators of CU for systems with RES is an urgent task and contributes to the further development of energy with distributed sources of electricity.
Distributed generation (DG) units have an important number of economic, environmental and technical features, which can contribute to the improvement of the reliability and security of the electric grid. However, all benefits that mentioned before cannot be maximised and enhanced unless the best sizing and position of distributed generation units are accurately determined. The arbitrary placement of DG units can lead to negative influences on the electrical networks. A noteworthy number of methods have been suggested to compute the optimal sizing and position of Distributed generation (DG) units in distribution networks. However, some of them focused on an analytical approach to estimate the optimum allocation of DG units in the radial distribution networks. Indeed, although this method was considered both constant and variable loads, as well as this method, overcome the problem of convergence, but the optimal sizing of DG units was not considered. The main intention of this study is to improve a technique that based on an intelligent algorithm for optimal planning and operation of DG technologies to minimise the real power losses, boost the voltage profile and enhance the overall reliability. IEEE Node-15 system has been taken to perform this study based on a MATLAB environment.in a single paragraph.
<p><span>In this work; we present an enhancement in blue laser diodes with new factors and applications for modern technology such as underwater telecommunications, bio-sensor and bio-medical systems etc. Years of advance meanwhile have much enhanced laser performance, and extremely improved their diversity, making lasers significant parts in scientific research, telecommunications, engineering, bio-medical imaging, materials working, and a swarm of other applications. This article viewing how laser technology has progressed to chance application requirements. The enhanced blue laser building diagrams to get a peak efficiency% at room temperature with modification. Moreover, we have as well estimated electro-optical performance packing of blue laser diodes been significantly various associated to GaAs laser method and novel developments and performances are required to enhance the optical power from anther laser diodes. Researchers need enhanced approaches to accurately make new the blue laser applications to use control of modern experimental measurements and optical communication.</span></p>
One of the damaging diseases among people in the world is skin cancer. Skin cancer leftovers an important scientific, clinical and public task. Swarm intelligence techniques (SITs) are new, improved and modern methods for optimization algorithms. Failure of detection in skin cancer images can be seen in SITs. This work proposes an efficient image and examines for some samples in this disease. The study presents a simple technique for a pre-processing and an automatic detection of SITs to make the needed analysis. This paper estimated all these various models using the PH2, Dermis, ISIC (2016, 2017, 2018) segmentation challenge dataset. The input images are improved for better processing than, the lesion sampling is segmented from the improved image by using Otsu thresholding and median filter operations. In the earlier studies, skin cancer is analyzed by means of several optimization algorithms. Now, the outcomes of the above algorithms were compared with the dice coefficient and it was demonstrated that the value of 97.35% which is nearer to manual segmentation. The accuracy the value of 98.58% when used for solving the same problem. To this end, a somewhat comprehensive analysis was showed to compare the effectiveness of many parameters’ combinations.
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