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Among the various methods proposed for modeling solar panels, those based on equivalent circuits have received significant attention. In these approaches, determining unknown parameters varies depending on the modeling objective. To model voltage–current characteristics, circuit analysis methods are employed to extract these unknown parameters. However, this modeling method relies on data provided by the solar panel manufacturer, leading to increased modeling error over time as coefficients change. In this article, a method independent of the manufacturer's data for modeling solar panels is presented. This method enables accurate modeling of pre‐installed solar power plants. By utilizing genetic programming on a single day's worth of data from a solar panel, the proposed method can establish relationships with a high degree of fit for the open‐circuit voltage, maximum power point, and short‐circuit current based on weather conditions. Through these relationships, the voltage–current characteristics can be modeled with greater precision compared to traditional circuit analysis methods, and without the need for data from the solar panel manufacturer. Finally, for further evaluation, a 3 kW solar power plant is modeled, which demonstrates the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

A new framework for controlling load frequency in a complex, interconnected power system with multiple sources has been developed. This framework combines a fuzzy logic controller (FLC) and a tilted integral derivative (TID) controller, creating a self-tuning fuzzy tilted integral derivative (STFTID) controller. The purpose of this controller is to conduct and reduce load frequency perturbations during the operation of a multi-area interconnected multi-source power system. The STFTID controller is optimized using a particle swarm optimization algorithm to minimize the frequency fluctuations effectively. Investigations of the proposed STFTID controller were performed for power systems with generation units of a conventional system and renewable energy sources. In the design process of the STFTID controller, various nonlinearities, uncertainties, and fluctuations are considered to simulate practical challenges. These challenges include generation rate constraints, governor deadband, and communication time delays (as the sources of nonlinearity), as well as fluctuations caused by step load switching and the connection of renewable power plants to the system. The STFTID controller is compared with the proportional integral derivative (PID), titled integral derivative, and integral tilted-derivative (I-TD) controllers. Simulation results show that the developed STFTID controller significantly enhances the system frequency control under various applied conditions, including multi-step load perturbation, renewable power plant integration, communication time delays, and generation rate constraints. [ABSTRACT FROM AUTHOR]

One of the most serious pests of walnut trees in recent years in Kermanshah Province is the pear lace bug, Stephanitispyri (F.) (Hemiptera: Tingidae). Damage of lace bug is not usually economic, but serious invasions can cause considerable damage or even death to the host. A field study was carried out to evaluate the fluctuations of S. pyri population on walnut trees in Kermanshah from January to December 2015. Data were analyzed using Taylor's power law and Iwao's patchiness regression methods to determine spatial distribution. In order to estimate the biological parameters of S. pyri in two different laboratory and semi-field conditions, the theory of age-stage two-sex life table was used. None of the life table parameters (r intrinsic rate of natural increase; R: net reproductive rate; A: finite rate of increase; T: mean generation time; and, GRR: gross reproductive rate) in the laboratory conditions had a significant difference from the field conditions, and more than 70% of individuals successfully passed the pre-imaginal developmental stages. The pear lace bug overwintered as adult within weeds until late March; after that, they migrated to the walnut trees and distributed on the leaves. As a result, there was no significant relationship between the fluctuations of the pear lace bug population and changes in temperature or relative humidity. Spatial distribution of the pear lace bug population was determined based on both Taylor and Iwao regression methods of aggregated type. [ABSTRACT FROM AUTHOR]

This paper develops a novel robust tracking model predictive control (MPC) without terminal constraint for discrete‐time nonlinear systems capable to deal with changing setpoints and unknown non‐additive bounded disturbances. The MPC scheme without terminal constraint avoids difficult computations for the terminal region and is thus simpler to design and implement. However, the existence of disturbances and/or sudden changes in a setpoint may lead to feasibility and stability issues in this method. In contrast to previous works that considered changing setpoints and/or additive slowly varying disturbance, the proposed method is able to deal with changing setpoints and non‐additive non‐slowly varying disturbance. The key idea is the addition of tightened input and state (tracking error) constraints as new constraints to the tracking MPC scheme without terminal constraints based on artificial references. In the proposed method, the optimal tracking error converges asymptotically to the invariant set for tracking, and the perturbed system tracking error remains in a variable size tube around the optimal tracking error. Closed‐loop input‐to‐state stability and recursive feasibility of the optimization problem for any piece‐wise constant setpoint and non‐additive disturbance are guaranteed by tightening input and state constraints as well as weighting the terminal cost function by an appropriate stabilizing weighting factor. The simulation results of the satellite attitude control system are provided to demonstrate the efficiency of the proposed predictive controller. [ABSTRACT FROM AUTHOR]

In power systems planning, economic load dispatch considering the uncertainty of renewable energy sources is one of the most important challenges that researchers have been concerned about. Complex operational constraints, non-convex cost functions of power generation, and some uncertainties make it difficult to solve this problem through conventional optimization techniques. In this article, an improved dynamic differential annealed optimization (IDDAO) meta-heuristic algorithm, which is an improved version of the dynamic differential annealed optimization (DDAO) algorithm has been introduced. This algorithm has been used to solve the economic emission load dispatch (EELD) problem in power systems that include wind farms, and the performance of the proposed technique was evaluated in the IEEE 40-unit and 6-unit standard test systems. The results obtained from numerical simulations demonstrate the profound accuracy and convergence speed of the proposed IDDAO algorithm compared to conventional optimization algorithms including, PSO, GSA, and DDAO, while independent runs indicate the robustness and stability of the proposed algorithm. [ABSTRACT FROM AUTHOR]

The application of the fractional-order PID (FOPID) controller is recently becoming a topic of research interest for vibration control of structures. Some researchers have successfully implemented the FOPID controller in a single-input single-output (SISO) control structural system subjected to earthquake excitations. However, there is a lack of research that focuses on its application in multi-input multi-output (MIMO) control systems to implement it in seismic-excited structures. In this case, the cross-coupling of the process channels in the MIMO control structural system may result in a complex design process of controllers so that each loop is independently designed. From an operational point of view, the time delay and saturation limit of the actuators are other challenges that significantly affect the performance and robustness of the controller so that ignoring them in the design process may lead to unrealistic results. According to the challenges, the present study proposed an optimal fractional-order PID control design approach for structural control systems subjected to earthquake excitation. Gases Brownian motion optimization (GBMO) algorithm is utilized for optimal tuning of the controller parameters. Considering six real earthquakes and seven performance indices, the performance of the proposed controller, implemented on a ten-story building equipped with an active tendon system (ATS), is compared with those provided by the classical PID controller. Simulation results indicate that the proposed FOPID controller is more efficient than the PID in both terms of seismic performance and robustness against time-delay effects. The proposed FOPID controller can maintain suitable seismic performance in small time delays, while a significant performance loss is observed for the PID controller. [ABSTRACT FROM AUTHOR]

Simple Summary: The ladybird Stethorus gilvifrons is an important natural enemy of herbivorous two-spotted spider mites, Tetranychus urticae. Here, we modeled the effect of temperature, which is the most significant abiotic environmental factor, on the development and thermal thresholds of S. gilvifrons. Thermal parameters and developmental trajectories were estimated by fitting two linear and 20 non-linear models to experimental data measured at seven temperature regimes ranging from 15 to 38 °C. Our findings demonstrate that S. gilvifrons is able to complete development at a broad range of temperatures and is well-adapted to temperatures occurring in temperate, Mediterranean, and subtropical climates. The thermal development models presented here represent a significant step towards an in-depth evaluation of S. gilvifrons as a biological control agent of T. urticae under different temperature regimes. The models can be used to predict the phenology of this predator, to forecast its population dynamics in the field, and to optimize mass-rearing efforts. The development rate of the predatory ladybird, Stethorus gilvifrons (Mulsant), fed on Tetranychus urticae Koch, was determined at 15, 20, 25, 27, 30, 34, and 38 °C. The total development time from egg to adult emergence for females was estimated to be 61.4, 31.6, 14.4, 13.3, 12.5, and 11.7 days, respectively. The development time decreased with increasing temperature from 15 to 34 °C, but all eggs failed to hatch at 38 °C. The lower temperature threshold (T0) for the entire development period and the thermal constant (K) for female S. gilvifrons were estimated to be 11.64 °C and 194.50 degree-days (DD) using the common linear model, and 11.96 °C and 187.87 DD using the Ikemoto and Takai model, respectively. Data were fitted to 20 non-linear development rate models and the thermal thresholds (Tmin and Tmax) and optimal temperature (Topt) were estimated. Among non-linear models, the Briere-2 and Ikemoto and Takai linear model provided adequate descriptions of the temperature-dependent development of S. gilvifrons. The upper-temperature threshold was estimated to be about 44 °C using the Logan-10 non-linear model. The estimated thermal development characteristics can be used to predict the occurrence and the population dynamics, as well as to improve the mass rearing and release, of S. gilvifrons for the biological control of T. urticae. [ABSTRACT FROM AUTHOR]