Harmonics management and hosting capacity enhancement: Optimal double-resistor damped double-tuned power filter with artificial hummingbird optimization.

This paper introduces a novel and improved double-resistor damped double-tuned passive power filter (DR-DDTF), designed using multi-objective optimization algorithms to mitigate harmonics and increase the hosting capacity of distribution systems with distributed energy resources. Although four different topologies of single-resistor damped double-tuned filters (DDTFs) have been studied before in the literature, the effectiveness of two different DR-DDTF configurations has not been examined. This work redresses this gap by demonstrating that via comprehensive simulations on two power systems, DR-DDTF provides better harmonic suppression and resonance mitigation than single-resistor alternatives. When it comes to optimizing the DR-DDTF for maximum hosting capacity and minimum system active power losses, the multi-objective artificial hummingbird outperformed six other algorithms in the benchmark. To allow for higher penetration of distributed generation without requiring grid upgrades, this newly developed harmonic mitigation filter provides a good alternative.

Current-voltage curves of planar heterojunction perovskite solar cells - Novel expressions based on Lambert W function and Special Trans Function Theory.

INTRODUCTION: At the present time, much attention has been focused on new types of solar cells, called perovskite solar cells. They are highly efficient devices with more than 25% power conversion efficiency. However, perovskite solar cell performance has not yet been fully explored. OBJECTIVES: We aimed to mathematically investigate the analytical modeling of current-voltage curves of planar heterojunction perovskite solar cells using Perovich Special Trans Function Theory (STFT). Furthermore, we proposed novel analytical closed-form solutions for short-circuit current and open-circuit voltage of these cells in terms of STFT. We evaluated the safety for laying the theoretical foundation by comparing the accuracy of the proposed expressions by the known methods. METHODS: A novel hybrid metaheuristic algorithm, called particle swarm optimization (PSO) - evaporation rate water cycle algorithm (ERWCA), is proposed to determine equivalent circuit parameters of the perovskite solar cell. A novel objective function is introduced for estimating the parameters for that purpose too. RESULTS: It was shown that STFT is very applicable and efficient for representing current-voltage expressions of perovskite solar cells. STFT provides a more accurate solution and requires fewer order members than the solutions provided by the conventional Taylor series. Based on these expressions and numerical calculations, it is verified that the characteristic values ​​of variables (short-circuit current, no-load voltage, efficiency, and fill factor) were not accurately calculated in the literature. Also, parameters of equivalent circuits of these cells were not accurately estimated. The equivalent circuit parameters were determined using the algorithm proposed in this work, which fit the verified values ​​of characteristic quantities much better than the literature. CONCLUSION: This work lays the foundation for developing the planar-structured perovskite solar cell models, in which the proposed estimation method and expressions are highly effective and provide excellent results.

Single Diode Solar Cells-Improved Model and Exact Current-Voltage Analytical Solution Based on Lambert's W Function.

There are three standard equivalent circuit models of solar cells in the literature-single-diode, double-diode, and triple-diode models. In this paper, first, a modified version of the single diode model, called the Improved Single Diode Model (ISDM), is presented. This modification is realized by adding resistance in series with the diode to enable better power loss dissipation representation. Second, the mathematical expression for the current-voltage relation of this circuit is derived in terms of Lambert's W function and solved by using the special trans function theory. Third, a novel hybrid algorithm for solar cell parameters estimation is proposed. The proposed algorithm, called SA-MRFO, is used for the parameter estimation of the standard single diode and improved single diode models. The proposed model's accuracy and the proposed algorithm's efficiency are tested on a standard RTC France solar cell and SOLAREX module MSX 60. Furthermore, the experimental verification of the proposed circuit and the proposed solar cell parameter estimation algorithm on a solar laboratory module is also realized. Based on all the results obtained, it is shown that the proposed circuit significantly improves current-voltage solar cell representation in comparison with the standard single diode model and many results in the literature on the double diode and triple diode models. Additionally, it is shown that the proposed algorithm is effective and outperforms many literature algorithms in terms of accuracy and convergence speed.

Attractive study of the antimicrobial, antiviral, and cytotoxic activity of novel synthesized silver chromite nanocomposites.

Antibiotic resistance is a global problem. This is the reason why scientists search for alternative treatments. In this regard, seven novel silver chromite nanocomposites were synthesized and assayed to evaluate their antimicrobial, antiviral, and cytotoxic activity. Five bacterial species were used in this study: three Gram-positive (Bacillus subtilis, Micrococcus luteus, and Staphylococcus aureus) and two Gram-negative (Escherichia coli and Salmonella enterica). Three fungal species were also tested: Candida albicans, Aspergillus niger, and A. flavus. The MIC of the tested compounds was determined using the bifold serial dilution method. The tested compounds showed good antibacterial activity. Maximum antibacterial activity was attained in the case of 15 N [Cobalt Ferrite (0.3 CoFe2O4) + Silver chromite (0.7 Ag0.5Cr2.5O4)] against M. luteus. Concerning antifungal activity, C. albicans was the most susceptible fungal species. The maximum inhibition was recorded also in case of 15 N [Cobalt Ferrite (0.3 CoFe2O4) + Silver chromite (0.7 Ag0.5Cr2.5O4)]. The most promising antimicrobial compound 15 N [Cobalt Ferrite (0.3 CoFe2O4) + Silver chromite (0.7 Ag0.5Cr2.5O4)] was assayed for its antiviral and cytotoxic activity. The tested compound showed weak antiviral activity. The cytotoxic activity against Mammalian cells from African Green Monkey Kidney (Vero) cells was detected. The inhibitory effect against Hepatocellular carcinoma cells was detected using a MTT assay. The antimicrobial effect of the tested compounds depends on the tested microbial species. The tested compounds could be attractive and alternative antibacterial compounds that open a new path in chemotherapy.

Environmental impacts and risk factors of renewable energy paradigm-a review.

The transition to a low carbon society is dependent on renewable energy-based electrification. Nevertheless, energy programs have resulted in growing societal polarization in several regions. Therefore, around the globe, government and legislative authorities at the local, regional, national, and international levels are highly concerned about the environmental impacts and risk factors that influence the energy paradigm. Thus, to minimize and/or limit the environmental insecurity issues, the world needs swift and effective actions to secure the climate for a better tomorrow. Moreover, there is a dire need to look for new energy alternatives, along with reducing the complete dependence on petro-based energy sources. Keeping this burning issue in mind, herein, an effort has been made to present the potential of several renewable energy sources, including wind-based renewable energy, solar-based renewable energy, hydro-based renewable energy, and biomass-based renewable energy. Following a brief introduction of energy-related problems and opportunities, a comparative overview is given to renewable vs. non-renewable energy sources. Then, several renewable energy sources, including wind, solar, hydro, and biomass, along with the worldwide energy capacity of each energy source are given with suitable examples and statistics. Finally, risk factors, concluding remarks, and future guidelines are discussed towards the end.

Internet of Things based real-time electric vehicle load forecasting and charging station recommendation.

Electric vehicles (EVs) are emerging as a favorable strategy to meet the increasing environmental concerns and energy insufficiency, and this trend is expected to grow in the near future. However, the inadequate charging infrastructure is becoming a major barrier to the wide acceptance of EVs. Deployment of this infrastructure is expected to maximize the adoption of EVs to facilitate users' range anxiety. Therefore, connectivity between the charging stations (CS) is mandatory. Understanding the real-time status of CSs can provide valuable information to users such as availability of charging provisions, reserves and the time to reach the CS. The intent of this paper is to provide a better EV charging system by utilizing the advantages of the Internet of Things (IoT) technology. The IoT paradigm offers the present facilities a real-time interactional view of the physical world by a variety of sensors and broadcasting tools. This research article proposes a real-time server-based forecasting application: i) to provide scheduling management to avoid waiting time; and ii) to provide a real-time CS recommendation for EVs with an economic cost and reduced charging time. In addition, the proposed scheme avoids third-party intervention and protects EV user privacy and complex information exchange between the user and CS. The end users can easily use the CS based on their requirements. This synergetic application is built up through the PHP programming language in the Linux UBUNTU 16.04 LTS operating system, and all relevant information is processed and managed through Cloud Structured Query Language (CSQL) from a Google cloud platform. The effectiveness of this application is also validated through a low-cost test system using LTC 4150, ESP 8266 Wi-Fi module and Arduino.

An improved approach for robust control of dynamic voltage restorer and power quality enhancement using grasshopper optimization algorithm.

This paper presents a novel contribution of a low complexity control scheme for voltage control of a dynamic voltage restorer (DVR). The scheme proposed utilizes an error-driven proportional-integral-derivative (PID) controller to guarantee better power quality performance in terms of voltage enhancement and stabilization of the buses, energy efficient utilization, and harmonic distortion reduction in a distribution network. This method maintains the load voltage close to or equal to the nominal value in terms of various voltage disturbances such as balanced and unbalanced sag/swell, voltage imbalance, notching, different fault conditions as well as power system harmonic distortion. A grasshopper optimization algorithm (GOA) is used to tune the gain values of the PID controller. In order to validate the effectiveness of the proposed DVR controller, first, a fractional order PID controller was presented and compared with the proposed one. Further, a comparative performance evaluation of four optimization techniques, namely Cuckoo search (CSA), GOA, Flower pollination (FBA), and Grey wolf optimizer (GWO), is presented to compare between the PID and FOPID performance in terms of fault conditions in order to achieve a global minimum error and fast dynamic response of the proposed controller. Second, a comparative analysis of simulation results obtained using the proposed controller and those obtained using an active disturbance rejection controller (ADRC) is presented, and it was found that the performance of the optimal PID is better than the performance of the conventional ADRC. Finally, the effectiveness of the presented DVR with the controller proposed has been assessed by time-domain simulations in the MATLAB/Simulink platform.