This paper presents a novel application of continuous mixed p-norm (CMPN) algorithm-based adaptive control strategy with the purpose of enhancing the low voltage ride through (LVRT) capability of ...grid-connected photovoltaic (PV) power plants. The PV arrays are connected to the point of common coupling (PCC) through a DC-DC boost converter, a DC-link capacitor, a grid-side inverter, and a three-phase step up transformer. The DC-DC converter is used for a maximum power point tracking operation based on the fractional open circuit voltage method. The grid-side inverter is utilized to control the DC-link voltage and terminal voltage at the PCC through a vector control scheme. The CMPN algorithm-based adaptive proportional-integral (PI) controller is used to control the power electronic circuits due to its very fast convergence. The proposed algorithm updates the PI controller gains online without the need to fine tune or optimize. For realistic responses, the PV power plant is connected to the IEEE 39-bus New England test system. The effectiveness of the proposed control strategy is compared with that obtained using Taguchi approach-based an optimal PI controller taking into account subjecting the system to symmetrical, unsymmetrical faults, and unsuccessful reclosing of circuit breakers due to the existence of permanent fault. The validity of adaptive control strategy is extensively verified by the simulation results, which are carried out using PSCAD/EMTDC software. With the proposed adaptive-controlled PV power plants, the LVRT capability of such system can be improved.
Till this moment, the model of interconnected power systems in the automatic generation control (AGC) loops relies only on the synchronous generating units. In today's world, a high level of ...penetration of renewable energy sources (RES) is integrated to the power grids. This paper presents a novel power system model, which includes both conventional generating units and RES for studying the AGC problem of such systems. The control strategy in the AGC loops is based on the proportional–integral–derivative (PID) controller, which is optimally designed by the whale optimization algorithm (WOA). It represents a great challenge to this controller to deal with the RES uncertainties. The effectiveness of the WOA-based PID controller is compared with other computation evolutionary algorithms-based PID controller. The system performance is evaluated under different operating conditions. For achieving a realistic study, 1) real wind speed data that extracted from Zafarana location in Egypt are used, 2) solar irradiation and temperature data that extracted from a field test are implemented, and 3) an irregular wave energy condition is applied. The validity of the control strategy is verified using the simulation results, which are carried out using MATLAB environment.
•We present performance improvement of PV systems in this paper.•The objective is to enhance system performance using optimal control strategy.•The control strategy depends on whale optimization ...algorithm-based PI controller.•The effectiveness of proposed controller is compared with GRG-based PI controller.•The validity of the proposed system is verified by simulation results.
Photovoltaic (PV) installations are consistently increasing all over the world, leading to a high penetration to the electric grid. Tremendous efforts should be exerted to maintain the operation of the PV systems at optimal conditions. This paper introduces an optimal control strategy with the purpose of enhancing the performance of PV systems. This control strategy is based on the proportional-integral (PI) controller, which is designed by using the whale optimization algorithm (WOA). The response surface methodology (RSM) model is established to create the objective function and its constraints. The proposed WOA-based PI controllers are utilized to control the DC chopper and grid-side inverter in order to achieve a maximum power point tracking operation and improve the dynamic voltage response of the PV system, respectively. The effectiveness of the control strategy is tested under different operating conditions of the PV system such as (1) subject the system to symmetrical and unsymmetrical fault conditions, (2) study the system responses under different irradiation and temperature conditions using real data extracted from a field test, and (3) subject the system to a sudden load disturbance in an autonomous operation. This effectiveness is compared with that achieved using the generalized reduced gradient (GRG) algorithm-based PI controller. The validity of the proposed control strategy is extensively verified by the simulation results, which are performed using PSCAD/EMTDC environment.
•A novel application of SFO algorithm to extract PV model parameters is presented.•Three-diode PV model is used in this paper.•Parameters of SFO-TDPV model are compared with other optimization based ...models.•The SFO-TDPV model is verified by comparing its results with measured data.•The error among these results records a value less than 0.5%.
This article proposes an accurate and straightforward method for modeling and simulation of photovoltaic (PV) modules. The main target is to find the nine-parameter of a three-diode (TD) model based on the datasheet parameters, which are given by all commercial PV modules. The objective function is formulated based on short circuit, open circuit, power derivative, and maximum power equations. Two parameters (parallel resistance and photo-generated current) are calculated analytically and rest parameters are optimally designed using the sunflower optimization (SFO) algorithm. The presented method is applied to model three types of commercial PV modules (multicrystal KC200GT, poly-crystalline MSX-60, and mono-crystalline CS6K-280M). The optimal nine-parameters obtained in this paper are paralleled with that attained by other approaches. In order to assess the efficiency of the offered approach, I-V and P-V characteristics are validated with measured data under various temperatures and solar irradiations. The error among these results records a value less than 0.5%. Therefore, the simulation results indicate an excellent agreement with the measured data. This proposed approach can be utilized to model any marketable PV module based on given datasheet parameters only.
This paper introduces a novel optimum design of the proportional-integral (PI) controller in the power converter circuits using the water cycle algorithm (WCA) to augment the transient stability of a ...grid-connected wave energy conversion (WEC) system. The proposed system relies on the Archimedes wave swing device, which is coupled with a linear permanent magnet synchronous generator (LPMSG). The WEC system is interfaced with the power grid via a generator-side converter (GSC) and a grid-side inverter (GSI). The GSC is used to control both of the d -axis and q -axis current of the LPMSG to minimize its power losses and extract its maximum real power, respectively. The GSI is implemented to control the terminal voltage at the point of common coupling and the dc-link voltage through a complete vector control scheme. The proposed optimal WCA-based PI control strategy is applied to both converters. The optimization process depends on the simulation-based optimization approach. In the proposed approach, the criterion of integral squared error is chosen as a multiobjective function. To validate the proposed WEC system model, the simulation results are compared with the practical results, and their error reaches less than 1%. The effectiveness of the proposed WCA-based PI control strategy is tested and compared with that obtained using the genetic-algorithm-based PI control scheme under symmetrical and unsymmetrical grid fault conditions taking into account a successful and unsuccessful reclosure of circuit breakers. The validity of the proposed control strategy is extensively checked based on simulation studies in the PSCAD/EMTDC environment.
The accurate electrical modeling of photovoltaic (PV) module is vital due to the extensive installation of photovoltaic power plants. Therefore, the scientists suggested a three-diode photovoltaic ...(TDPV) model for precise modeling of PV losses. However, TDPV is a complex and nonlinear model that contains nine unknown parameters. Hence, this paper presents a new method that is combining the computation and Harris Hawk Optimization (HHO) algorithm to extract the unknown parameters of the TDPV model. Also, this paper exhibits a new objective function based on the datasheet values instead of using extensive experiments for PV modeling for time-saving. The industrialists provided the datasheet values of PV modules at standard test conditions (STC) and normal operating cell temperature (NOCT). Therefore, this paper utilized these data to compute four parameters using equations and identify the remaining five parameters using the HHO algorithm. In this paper, the offered method is employed to find the TDPV model of two commercial PV panels, such as multi-crystal KC200GT and monocrystalline CS6K280M. After that, the I–V and P–V curves of these TDPV models plotted and compared with the curves of the measured data under different temperatures and solar irradiations. Moreover, the absolute current error of the proposed method compared with that obtained by using other methods. Accordingly, the results revealed that the proposed method is efficient and can be easily applied to identify the electrical parameters of any commercial PV panel based on the datasheet values only.
•This paper presents a novel method for PV modeling, combined computation and optimization.•A novel application of Harris Hawk Optimization is presented.•Three-diode PV (TDPV) model with nine electrical parameters is used in this paper.•The effectiveness of the proposed method verified using experimental data.•Two commercial PV modules are used in this paper (CS6K-280M and KC200GT).
An accurate identification of the parameters of solid oxide fuel cell (SOFC) models is the first step to provide a reliable design for an energy storage system using SOFC. Therefore, in the current ...work, a novel developed variant for the marine predators algorithm (MPA) is proposed based on comprehensive learning and dynamic multi-swarm approaches to extract highly accurate, precise, and efficient parameters of the SOFC model that achieve the closely matching between the actual and estimated system responses. The proposed comprehensive learning dynamic multi-swarm marine predators algorithm (CLDMMPA) is examined with two scenarios that are SOFC steady-state and dynamic state-based models under variable operating conditions. The results of the proposed algorithm are validated via an intensive comparison based on statistical metrics and non-parametric tests with other recent counterparts. Furthermore, the accuracy of identified parameters in the case of the dynamic model is evaluated with two cases of sudden power load variations, and the dynamic responses of the stack voltage and current are analyzed. The comparisons and analyses have confirmed the superiority of the proposed CLDMMPA to provide highly accurate identified parameters that exhibit the minimum deviation between the measured and estimated stack current–voltage and stack current–power curves. Moreover, the consistency of the CLDMMPA results and the smooth decaying in its convergence curves are other remarkable points superior to other counterparts.
•A newly comprehensive learning dynamic multi-swarm marine predators algorithm is introduced.•The proposed approach is validated numerically using CEC2020.•The approach is applied to SOFC steady-state and dynamic models.•Two phases of load power changes are used to test the quality of estimated parameters.•Various case studies at diffident temperatures are evaluated.
This article presented a novel modification and application of the salp swarm algorithm (SSA) that is inspired by the chain behavior of salp fishes that live in deep oceans. Firstly, the enhanced ...salp swarm algorithm (ESSA) is proposed to improve the inadequate results of the SSA compared to the other algorithms, especially for the high dimensional functions. The ESSA algorithm is verified using twenty-three benchmark test functions and compared with the original SSA algorithm and other algorithms. The statistical analysis of the obtained results revealed that the ESSA algorithm is significantly improved and the convergence curves showed the fast convergence to the best solution. Secondly, The SSA and ESSA algorithms are applied to enhance the maximum power point tracking and the fault-ride through ability of a grid-tied permanent magnet synchronous generator driven by a variable speed wind turbine (PMSG-VSWT). The multi-objective function (integral squared error) is minimized to find the high dimensional parameters of Takagi–Sugeno–Kang fuzzy logic controllers (TSK-FLC) used in the cascaded control of grid-tied PMSG-VSWT. The simulation results using PSCAD/EMTDC proved that the produced power when using ESSA is higher than when using SSA which mean higher efficiency and lower cost.
•This paper proposes an enhancement to the salp swarm algorithm (ESSA).•The ESSA is tested with twenty-three benchmark functions.•The ESSA is compared with eight published algorithms.•The ESSA and SSA are applied to the variable speed wind generators.
•A novel optimization method is presented for photovoltaic modeling.•An accurate three-diode photovoltaic model is used in this paper.•Transient search optimization is compared with other ...algorithms.•The simulation results of the Photovoltaic model are verified by the measured data.
This paper presents a novel efficient metaheuristic algorithm called Transient Search Optimization (TSO), which is inspired by the transient process of the inductive and capacitive circuits. Also, this paper presents an objective function based on the datasheet of PV modules at standard test conditions (STC). Then, the TSO algorithm is applied to minimize the objective function to find the optimal nine parameters of the three-diode model (TDM) of the PV module. Also, the results of the proposed TSO algorithm are compared with that obtained by using other metaheuristic algorithms, where in this regard the TSO achieved the best results. The proposed technique is verified by applying it to find the optimal TDM of three commercially common PV modules with different cell types, rated power, and terminal voltage. Then, the simulated I-V and P-V characteristics of these PV modules matched with the measured data under many environmental conditions. Accordingly, the results have proved that the offered technique is useful to find the optimal TDM of all PV modules based on the dataset given by the manufacturers.
•Salp swarm algorithm (SSA) is applied for fine-tuning of PID parameters.•System nonlinearity and wind farms uncertainty are considered.•The effect of cross-coupling between the excitation and LFC ...loop is investigated.•Real wind speed data and real sun irradiations are utilised for realistic studies.•The dynamic responses are investigated and analyzed plus comparisons.
This paper proposes a new application of the salp swarm algorithm (SSA) to fine-tune the gains of proportional-integral-derivative (PID) controllers of load frequency control (LFC) of a multi-area hybrid renewable nonlinear power system. To analyze the system nonlinearity, a dead-band is implemented in the governor model, a generation rate constraint is employed with the turbine model, and a communication delay time of phase measuring unit devices is carried out in the secondary automatic LFC loop. An exact model is established to take into consideration the effect of cross-coupling between the excitation control system and LFC loop. A single and multi-objective functions are performed to test the validity of the proposed controllers. To obtain a more realistic study, real wind speed data are involved in the wind farm model and real sun irradiations for a photovoltaic system that captured from a field test are incorporated to check the validity of the SSA-PID controllers under power system nonlinearities and renewable energy sources variability and uncertainties. The effectiveness of SSA-PID controller is compared with other optimization methods based-PID controller under several operating conditions. With the proposed controller, the LFC dynamic responses of multi-area hybrid nonlinear power systems shall be further enhanced.
