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Integration of photovoltaic (PV) power to the grid is achieved using three-phase inverters with high quality current waveforms. The new grid codes impose a limit on the total harmonic distortion (THD) value of the inverter’s current waveforms. Due to simple structure and ease of design, proportional integral (PI) controllers are the most widely ado...
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... proportional 230 gain k p , system exhibits fast transient response: Resonant gain k i offers improved damping around fundamental frequencyω o . Figure 6 presents the system's root locus plot with PR regulator. ...
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... the measured current components track the reference values of the current perfectly and without any phase difference. Figures 15 and Figure 16 show the % THD in the current 305 wave forms using fixed gain and adaptive gains PR controller, respectively. The presented results show that with the adaptive gain PR controller ensures a THD value of 1.77% as compared to the fixed gain PR controller with a THD of 2.01%. ...
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... proportional 230 gain k p , system exhibits fast transient response: Resonant gain k i offers improved damping around fundamental frequencyω o . Figure 6 presents the system's root locus plot with PR regulator. ...
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... the measured current components track the reference values of the current perfectly and without any phase difference. Figures 15 and Figure 16 show the % THD in the current 305 wave forms using fixed gain and adaptive gains PR controller, respectively. The presented results show that with the adaptive gain PR controller ensures a THD value of 1.77% as compared to the fixed gain PR controller with a THD of 2.01%. ...
Citations
... These MPPT methods can be classified into four categories: conventional, intelligent, metaheuristic optimization and advanced. Conventional MPPT approaches such as perturb and observe (P&O) method [1,2], hill climbing (HC) method [3,4], proportional integral (PI) controller [5,6] and incremental conductance (IC) [7,8] are widely used in this field due to their simplicity and ease of implementation. However, these methods offer poor performance and also suffer from the problem of oscillations around the MPP, which leads to low efficiency of the power generation system. ...
This paper presents a novel maximum power point tracking control for a stand-alone photovoltaic (PV) system based on a robust polynomial static output feedback control law subject to input saturation. In detail, a DC/DC boost converter is used to regulate the load and extract the maximum power from the photovoltaic panel. First, a polynomial fuzzy model is used to represent the photovoltaic system. Then, as this control method is based on a reference model, a regression plane is used to generate the desired trajectory representing the optimal dynamics where the PV system supplies maximum power. Then, in order to reduce the number of required sensors, a polynomial output feedback controller was developed, in which the problem of converter performance degradation resulting from duty cycle saturation was avoided by using a saturated control approach. The controller gains have been obtained by solving a sum-of-squares optimization problem, where the H∞\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\mathcal {H}}_\infty $$\end{document} performance criterion is applied to guarantee the stability of the closed-loop system while achieving an optimal rejection level of external disturbances. To evaluate the performance of the suggested controller, a number of simulations and comparisons were carried out in MATLAB/Simulink environment and under various scenarios of weather conditions.
... Proportional integral (PI) controllers are the most extensively used techniques for controlling three-phase gridconnected inverters because of their simple construction and ease of design; yet, PI controllers can encounter instability issues in unexpected grid events. An expert knowledge-based proportional resonant (PR) regulation for the integration of PV power to the grid during abnormal grid circumstances in order to solve the aforementioned issue [25]. The operating parameters of photovoltaic (PV) solar power systems have a significant impact on their techno-economic viability. ...
This study utilized Harris Hawk optimization to analyze the harmonic distortions of a symmetric capacitor based multilevel converter. The proposed multilevel converter uses identical and symmetric DC sources in its input. The proposed topology for a multilevel converter uses fewer switches than typical cascaded designs. It can output 9-level outputs and can be scaled up to higher levels. The proposed multilevel converter can be improved by implementing a low frequency pulse width modulation technique to reduce the stress on the switches. The optimization of the switching angles using Harris Hawk was able to solve the non-linear aspects of the Selective Harmonic Elimination Pulse Width Modulation. The output voltage's THD was compared with that of other optimization methods, such as ant colony and particle swarm. The comparison shows that the output THD of the Harris Hawk optimizer is lower than that of other methods, which is about 5%, according to the standards of IEEE-519.
... For example, the utilisation of wind energy and photovoltaic parks is selected as a viable and sustainable course of action for government implementation. [33,34]. Some characteristic examples are presented as Supplementary Material in Tables S1 and S2. ...
The citizen’s carbon footprint is affected by various factors, but mostly by electricity consumption, daily transportation, travelling habits, as well as municipal solid waste management, a critical factor that is not frequently incorporated in carbon footprint estimations. This paper proposes a new carbon footprint calculator, the Carbon Footprint Simulation Dashboard—COMPAIR’s CO2 calculator. The CO2 calculator employs Citizen Science (CS) information in order to assist citizens in understanding and comparing how future carbon emissions will be modified in accordance with changes in their daily routines. The calculator offers several statistics, e.g., the country’s average carbon footprint and comparisons between EU members with respect to sectors that shape it, along with several recommendations for those domains where carbon footprint is significantly higher than the desired limits. The novelty of this tool is the integration of waste management strategies as a dimension of the total CO2 calculation. In this framework, the study presents the development of the Carbon Footprint Simulation Dashboard while two different waste management scenarios are applied with different citizen behaviours on recycling and composting. The applications highlighted the consumption in buildings that account for almost 50% of the total CO2 emissions, while the crucial role of transportation is also a key parameter. The different waste management scenarios showed a correlation between the CO2 footprint and the overall consumption/disposal habits of citizens. In the case of advanced recycling and composting, waste management accounted for up to 7% of the CO2 emissions, and this highlights the significance of behavioural choices.
... Another challenge in DPC is the changeability of the frequency switching which makes the filter design more challenging [23]. These issues are resolved somehow with the use of proportional resonant (PR) control system [24], however; fixed gain PR controllers can also lead to poor performance under large system disturbances. ...
This article outlines how to optimize the parameters of proportional integral (PI) and proportional resonant (PR) controllers of a grid connected three-phase inverter system using Particle Swarm Optimization (PSO). The optimization of the control parameters is constrained to a low total harmonic distortion (THD) in the injected currents to the grid. In contrast to conventional PI and PR tuning methods, the PSO optimized controller inherits a wide-ranging operating condition, having better performance in steady-state and rapid dynamic response under abnormal grid conditions. This approach is used to provide the simulation results under both abnormal and normal grid conditions. Some important characteristics of this technique are that its complexity is not altered, no additional hardware is required, and no additional cost is added. From the presented results, it is observed that the proposed control optimization method ensured a low THD of 0.59% in the injected grid currents. Moreover, the control parameter optimization error converges to zero in finite time. © 2023,Mathematical Modelling of Engineering Problems.All Rights Reserved.
... In the PSO algorithm, the process of finding a solution is performed by a population containing some particles [39]. PSO is an optimization technique with a concept of population-based activities in a food-searching procedure where each individual is called a particle. ...
Since the power grid grows and the necessity for higher system efficiency is due to the increasing number of renewable energy penetrations, power system operators need a fast and efficient method of operating the power system. One of the main problems in a modern power system operation that needs to be resolved is optimal power flow (OPF). OPF is an efficient generator scheduling method to meet energy demands with the aim of minimizing the total production cost of power plants while maintaining system stability, security, and reliability. This paper proposes a new method to solve OPF by using incremental particle swarm optimization (IPSO). IPSO is a new algorithm of particle swarm optimization (PSO) that modifies the PSO structure by increasing the particle size, where each particle changes its position to determine its optimal position. The advantage of IPSO is that the population increases with each iteration so that the optimization process becomes faster. The results of the research on optimal power flow for energy generation costs, system voltage stability, and losses obtained by the IPSO method are superior to the conventional PSO method.
... Some more optimization techniques like predictive function control can be used to regulate the temperature-efficient energy consumption (Nassima et al., 2021). Furthermore, the limitation of a proportional integral (PI) controller can be resolved by using some advanced expert approaches (Ahmed et al., 2022;Kim et al., 2014). For tuning the control parameters, there is a need for advanced optimization techniques so that we can get better system response parameters (Khan et al., 2022). ...
This article compares the conventional model predictive control (MPC) and active disturbance rejection control (ADRC) with a novel MPADRC technique for controlling a non-minimum phase behavior in the DC–DC boost converter. The control of the boost converter is challenging as it is nonlinear, and it shows non-minimum phase behavior in a continuous conduction mode (CCM). Moreover, in this article, the comparison is presented for the boost converter and the two-phase interleaved boost converter using MPC and ADRC, and the effectiveness of the interleaving technique is shown. Finally, it is proved that the interleaving method has much more efficiency and less output ripple than the simple boost converter. To conclude, a novel technique has been introduced that combines both the techniques, that is, MPC and ADRC, in the outer and inner loop with a boost converter, respectively, and the response is clearly the best when compared to the said techniques individually. The overall impact of this technique includes the advantages of both the techniques, that is, the use of MPC allows us to optimize the current value by predicting the future values, and the use of ADRC ensures that the disturbance factor is well tackled and cancels the effect caused by all the disturbances including ignored quantities as well.
... In Fig. 6, Proportional Resonant (PR) controllers are used in the inner (current) and outer (voltage) control loops, and their design can be done using the referenced methods [110], [111], [112], [113], [114]. DSOGI based Positive Sequence Calculation (DSOGI-PSC) method can obtain positive sequence components from three-phase voltages and currents, and instantaneous powers can be calculated using the sequence components [115], [116]. ...
In recent years, integrating renewable energy sources (RESs) has achieved significant attention due to the growing demand for sustainable energy solutions. Inverter-interfaced Islanded Microgrids (IGs) have appeared as an advantageous approach to integrating RESs into the power grid. Grid-forming inverters (GFIs) are a critical component of IGs, and their synchronization is essential for stable and reliable operation. The literature has widely proposed soft transition, pre-synchronization, and re-synchronization to synchronize IGs to the main grid. However, methods for synchronizing GFIs in the islanded microgrid are restricted. Parallel operation of GFIs is required to guarantee the high power demand of IG and improve voltage-frequency stability. For parallel operation, GFIs must be synchronized with each other. In the conventional synchronization control systems that are highly nonlinear, the linear proportional-integral (PI) controllers are commonly used in synchronization loops without considering the nonlinearity resulting from the initial condition dependency and cross-coupling. Thus, conventional synchronization methods can be exposed to concerns of stable operation, narrow operation area, and performance degradation. This study proposes a new linearized synchronization control system for GFIs in IGs. In this way, it is possible to analytically design robust linear controllers and ensure a stable operation, high performance, and wide (full) operation area. In addition, a new soft-commissioning method is proposed to deactivate synchronization loops and soft-start the synced GFI. The proposed system has been tested in real-time and CHIL hardware setups for two 550 kW GFIs operating in parallel, and the results in the perfect agreement are presented in this study.
... Khunkitti [31] solved MO-OPF using PSO to minimize fuel cost and power losses emission. Conventional OPF solely considers thermal energy sources but growing fuel prices and environmental impact have prompted governments to investigate renewable energy sources such as wind, solar, and wave energy [32,33]. Wind and solar energy penetration need to be addressed in the electrical system. ...
The growing usage of renewable energy sources, such as solar and wind energy, has increased the electrical system’s unpredictability. The stochastic behavior of these sources must be considered to obtain significantly more accurate conclusions in the analysis of power systems. To depict renewable energy systems, the three-component mixture distribution (TCMD) is introduced in this study. The mixture distribution (MD) is created by combining the Weibull and Gamma distributions. The results show that TCMD is better than original distributions in simulating wind speed and solar irradiance by reducing the error between real data and the distribution curve. Additionally, this study examines the optimal power flow (OPF) in electrical networks using the two stochastic models of solar and wind energy. The parameters of the probability distribution function (PDF) are optimized using the Mayfly algorithm (MA), which also solves single- and multi-objective OPF issues. Then, to prove the accuracy of the MA method in solving the OPF problem, single- and multi-objective OPF is applied on a standard IEEE-30 bus system to minimize fuel cost, power loss, thermal unit emissions, and voltage security index (VSI), and results are compared with other metaheuristic methods. The outcomes show that the MA technique is dependable and effective in overseeing this challenging problem. Additionally, the suggested OPF MA-based is studied in the OPF problem while accounting for the uncertainty in the models of the wind and solar systems and taking the emissions, VSI, power loss, and fuel cost into consideration in the objective function. The significance of the work lies in the application of a unique optimization technique to a hybrid electrical system using TCMD stochastic model using actual wind and solar data. The proposed MA method could be valuable to system operators as a decision-making aid when dealing with hybrid power systems.
... According to formula (1), the AC side current i d and i q of MMC converter is affected by control quantity u d and u q , grid electromotive force v d and v q , and cross coupling term ωLi d and ωLi q , so feedforward decoupling control is required. By introducing Equation (6) into Equation (2), the sliding mode variable structure control law of the current inner loop of the grid-connected composite device can be obtained, as shown in Equation (7). Figure 3 is the sliding mode variable structure control block diagram of the current inner loop of the GCCD. ...
In order to make the grid-connected composite device (GCCD) controller meet the requirements of different operating modes and complex working conditions of power grid, this paper proposes to introduce sliding mode control (SMC) into GCCD controller. Firstly, the mathematical model of MMC converter is established, and the sliding mode controller is designed based on the SMC principle. Then, aiming at the problems of complex controller structure and difficult parameter tuning in multiple modes of the GCCD, this paper proposes a controller parameter optimization method based on improved Month Flame optimization (IMFO) algorithm. This method improves the MFO algorithm by introducing good point set (GPS) initialization and Levy flight strategy, which accelerates the convergence speed of the algorithm while avoiding falling into local optimization, and realizes the optimization of converter controller parameters. Under a variety of standard test functions, the advantages of the proposed IMFO algorithm are verified by comparing it with the traditional algorithm. Finally, in order to realize the automatic tuning of control parameters, the Python–PSCAD joint simulation method is studied and implemented. Taking the comprehensive integral of time and absolute error (CITAE) index as the objective function, the parameters of the sliding mode controller are optimized. The simulation results show that the controller parameters optimized by the IMFO algorithm can make the GCCD have better dynamic performance.
... Actually, the use of batteries has some problems related to their lifespan and the necessity of maintenance work; therefore, the interest in the development of new autonomous energy sources capable of transforming surrounding wasted energy into electrical energy has grown [5][6][7][8][9][10], including the use of storage systems like smart batteries and supercapacitors [11]. On the other hand, studies related to the incorporation of clean energy sources into the grid [12] and the search for faults in the electrical distribution network [13] are being realized with promising results in improving the efficiency of electricity generation and transmission. ...
A piezoelectric energy harvester generator is a device capable of transforming environmental mechanical energy into electrical energy. The piezoelectric electromechanical parameters determine the maximum electrical power which is able to be transferred to an electric load. In this research work, an exhaustive study of the electromechanical parameters related to the piezoelectric material is carried out, modeling them as components of an electrical circuit, in order to analyze their influence on the transmitted power. On the other hand, some electrical loads are simulated to determine different matrix scenarios for a model developed by state-space equations in the Laplace transform domain. The results obtained have allowed to know how the piezoelectric material properties and mechanical characteristics influence the electrical power output of the energy harvester generator and the energy transmission behavior for different electric loads. The conclusions show how the different electromechanical parameters are related to each other, and how their combination transforms the mechanical environmental energy into the required electrical energy. The novelty of this research is the presentation of a model capable of obtaining the optimized working point of the harvester, taking into account not only the electric loads and current demands but also the piezoelectric material parameters.
