Maximizing solar radiations of PV panels using artificial gorilla troops reinforced by experimental investigations.

This article's main objective is to maximize solar radiations (SRs) through the use of the gorilla troop algorithm (GTA) for identifying the optimal tilt angle (OTA) for photovoltaic (PV) panels. This is done in conjunction with an experimental work that consists of three 100 W PV panels tilted at three different tilt angles (TAs). The 28°, 30°, and 50° are the three TAs. The experimental data are collected every day for 181-day and revealed that the TA of 28° is superior to those of 50° and 30°. The GTA calculated the OTA to be 28.445°, which agrees with the experimental results, which show a TA of 28°. The SR of the 28o TA is 59.3% greater than that of the 50° TA and 4.5% higher than that of the 30° TA. Recent methods are used to compare the GTA with the other nine metaheuristics (MHTs)-the genetic algorithm, particle swarm, harmony search, ant colony, cuckoo search, bee colony, fire fly, grey wolf, and coronavirus disease optimizers-in order to figure out the optimal OTA. The OTA is calculated by the majority of the nine MHTs to be 28.445°, which is the same as the GTA and confirms the experimental effort. In only 181-day, the by experimentation it may be documented SR difference between the TAs of 28° and 50° TA is 159.3%. Numerous performance metrics are used to demonstrate the GTA's viability, and it is contrasted with other recent optimizers that are in competition.

Consolidation of LVFRT capabilities of microgrids using energy storage devices.

The performance and dependability of distribution networks may be enhanced by the incorporation of microgrids (MGs). However, it is necessary to enhance low voltage fault-ride-through (LVFRT), which has the capacity to prevent abrupt grid disconnections during LV occurrences under problematic circumstances. In this study, a control strategy for energy storage elements (ESDs) which includes batteries and supercapacitors is proposed to enhance LVFRT under balanced and unbalanced faults. The MG comprises wind farms and/or photovoltaic arrays. Based on the dynamic simulations using MATLAB/SIMULINK, the ESDs can enhance LVFRT capability. A comparison of the conventional crowbar scheme and ESDs is realized, and the latter has a better performance than the former in retaining the DC-link voltage within satisfactory bounds. For the purpose of maintaining the DC-link voltage at a reference level, the battery stores extra power in the DC-bus of three systems. LVFRT is improved by the crowbar circuit, however the resistance consumes the extra power. Super capacitors (SCs) prevent DC voltage fluctuations, reduce active power oscillations, and hasten system stabilization when present. At an advanced stage of this effort, the coot bird optimizer (CBO) is applied to generate the best gains of bi-directional converter PI-controller and the ESDs ratings to have minimum ripples in the DC-bus voltage and to boost the LVFRT capability of the MGs. The viability of the proposed method based on the CBO's results is indicated with further validations under different operating scenarios.

Accurate emulation of steady-state and dynamic performances of PEM fuel cells using simplified models.

The current effort addresses a novel attempt to extract the seven ungiven parameters of PEMFCs stack. The sum of squared deviations (SSDs) among the measured and the relevant model-based calculated datasets is adopted to define the cost function. A Kepler Optimization Algorithm (KOA) is employed to decide the best values of these parameters within viable ranges. Initially, the KOA-based methodology is applied to assess the steady-state performance for four practical study cases under several operating conditions. The results of the KOA are appraised against four newly challenging algorithms and the other recently reported optimizers in the literature under fair comparisons, to prove its superiority. Particularly, the minimum values of the SSDs for Ballard Mark, BCS 0.5 kW, NedStack PS6, and Temasek 1 kW PEMFCs stacks are 0.810578 V2, 0.0116952 V2, 2.10847 V2, and 0.590467 V2, respectively. Furthermore, the performance measures are evaluated on various metrics. Lastly, a simplified trial to upgrade Amphlett's model to include the PEMFCs' electrical dynamic response is introduced. The KOA appears to be viable and may be extended in real-time conditions according to the presented scenarios (steady-state and transient conditions).

Electrical parameters extraction of PV modules using artificial hummingbird optimizer.

The parameter extraction of PV models is a nonlinear and multi-model optimization problem. However, it is essential to correctly estimate the parameters of the PV units due to their impact on the PV system efficiency in terms of power and current production. As a result, this study introduces a developed Artificial Hummingbird Technique (AHT) to generate the best values of the ungiven parameters of these PV units. The AHT mimics hummingbirds' unique flying abilities and foraging methods in the wild. The AHT is compared with numerous recent inspired techniques which are tuna swarm optimizer, African vulture's optimizer, teaching learning studying-based optimizer and other recent optimization techniques. The statistical studies and experimental findings show that AHT outperforms other methods in extracting the parameters of various PV models of STM6-40/36, KC200GT and PWP 201 polycrystalline. The AHT's performance is evaluated using the datasheet provided by the manufacturer. To highlight the AHT dominance, its performance is compared to those of other competing techniques. The simulation outcomes demonstrate that the AHT algorithm features a quick processing time and steadily convergence in consort with keeping an elevated level of accuracy in the offered solution.

Fuel-cell parameter estimation based on improved gorilla troops technique.

The parameter extraction of the proton exchange membrane fuel cells (PEMFCs) is an active study area over the past few years to achieve accurate current/voltage (I/V) curves. This work proposes an advanced version of an improved gorilla troops technique (IGTT) to precisely estimate the PEMFC's model parameters. The GTT's dual implementation of the migration approach enables boosting the exploitation phase and preventing becoming trapped in the local minima. Besides, a Tangent Flight Strategy (TFS) is incorporated with the exploitation stage for efficiently searching the search space. Using two common PEMFCs stacks of BCS 500W, and Modular SR-12, the developed IGTT is effectively applied. Furthermore, the two models are evaluated under varied partial temperature and pressure. In addition to this, different new recently inspired optimizers are employed for comparative validations namely supply demand optimization (SDO), flying foxes optimizer (FFO) and red fox optimizer (RFO). Also, a comparative assessment of the developed IGTT and the original GTT are tested to ten unconstrained benchmark functions following to the Congress on Evolutionary Computation (CEC) 2017. The proposed IGTT outperforms the standard GTT, grey wolf algorithm (GWA) and Particle swarm optimizer (PSO) in 92.5%, 87.5% and 92.5% of the statistical indices. Moreover, the viability of the IGTT is proved in comparison to various previously published frameworks-based parameter's identification of PEMFCs stacks. The obtained sum of squared errors (SSE) and the standard deviations (STD) are among the difficult approaches in this context and are quite competitive. For the PEMFCs stacks being studied, the developed IGTT achieves exceedingly small SSE values of 0.0117 and 0.000142 for BCS 500 and SR-12, respectively. Added to that, the IGTT gives superior performance compared to GTT, SDO, FFO and RFO obtaining the smallest SSE objective with the least STD ever.

Estimation of optimal tilt angles for photovoltaic panels in Egypt with experimental verifications.

The principal target of this work is to compute the optimal tilt angle (OTA) for Photovoltaic (PV) panels. To perform this task, comprehensive simulations are done starting from altering the tilt angle (TA) daily, to use one fixed TA for all the year. The mathematical models for extra-terrestrial radiation (ETR) of both horizontal and inclined surfaces are presented firstly. At a later stage, the optimization formulation for the maximizing the solar radiation (SR) is adapted, and then the daily, monthly, seasonally, half-yearly and optimal fixed TAs are obtained. Although, the daily OTA produces the maximum SR, it is costly and impractical. It is found that altering the TA twice a year at optimal values that are computed as 5° and 50° for Suez city, gives the best results that are very near to the daily altering of the OTA. The difference between the two methods is 1.56% which is very small. Also, the two OTAs has SR better than that of the fixed OTA which is 28° by 7.77%. Also, it is found that the yearly fixed OTA (28°) is nearly equal to the latitude angle of Suez city which is 30°. The two OTAs method of this paper is different from the commonly used method that suggests two TAs. The first TA is used for winter months which is obtained by adding 15° to the latitude angle while the second TA is obtained by subtracting 15° from the latitude angle for the summer months. This commonly used method produces lesser SR than the two OTAs method of this paper. The theoretical work has been proved by an experimental work on two PV systems constructed at 25° and 30° TAs. The results of the experimental work agree with the theoretical results.

Estimation of electrical transformer parameters with reference to saturation behavior using artificial hummingbird optimizer.

This paper offers an efficient tool to define the unknown parameters of electrical transformers. The proposed methodology is developed based on artificial hummingbird optimizer (AHO) to generate the best values of the transformer's unknown parameters. At initial stage, the parameters' extraction of the transformer electrical equivalent is adapted as an optimization function along with the associated operating inequality constraints. In which, the sum of absolute errors (SAEs) among many variables from nameplate data of transformers is decided to be minimized. Two test cases of 4 kVA and 15 kVA transformers ratings are demonstrated to indicate the ability of the AHO compared to other recent challenging optimizers. The proposed AHO achieves the lowest SAE's value than other competing algorithms. At advanced stage of this effort, the capture of percentage of loading to achieve maximum efficiency is ascertained. At later stage, the performance of transformers utilizing the extracted parameters cropped by the AHO to investigate the principal behavior at energization of these transformer units is made. At the end, it can be confirmed that the AHO produces best values of transformer parameters which help much in achieving accurate simulations for steady-state and inrush behaviors.

Frequency control of the islanded microgrid including energy storage using soft computing.

Today, with the increasing penetration of microgrids, the degree of complexity and non-linearity of power systems has increased, causing conventional and inflexible controllers not to perform well in a wide range of operating points. In this paper, a self-tuning proportional-integral (PI)-controller based on a soft computation of a combination of genetic algorithm (GA) and artificial neural network (ANN). The GA-ANN is used to control the frequency of a microgrid in an island mode to automatically adjust and optimize the coefficients of a PI-controller. The proposed PI-controller is located in the frequency control secondary loop of an island microgrid. Since the ANN is a local search algorithm and can be located in local minimum points and on the other hand improving its performance requires a lot of training data. The ANN parameters are optimized using the GA algorithm's proposed controller. Train ANN online to adapt to the system and change the PI-control coefficients without a lot of training data, in addition to avoiding being in the local minimum points.The microgrid tested included various distributed generation units including battery energy storage that tried to create a more realistic frequency response for the microgrid by considering nonlinear factors on the model of these resources. Finally, the simulation results with different perturbations indicate the proper performance of the proposed controller.