Grid-connected Power Generation System Research Articles

Research on active participation of distributed photovoltsics in power grid primary frequency control strategy

Distributed photovoltaic systems can actively contribute to the primary frequency regulation of the power grid by reserving capacity. Traditional power reduction methods often employ fixed load reduction ratios, potentially resulting in inadequate frequency regulation capacity and unnecessary reserve power. This paper centers on optimizing power reserve control, starting with the construction of a two-stage model for a photovoltaic grid-connected inverter power generation system. It includes the design of a maximum power estimation method and the implementation of photovoltaic power reduction operation. The article proposes a strategy to utilize photovoltaic backup capacity for achieving primary frequency modulation effects in a short time scale. Additionally, it adopts a variable power reserve ratio operation strategy over the long term, aiming to enhance photovoltaic power generation and optimize solar energy utilization without compromising the grid’s frequency and quality. Finally, a MATLAB/Simulink model is developed to validate the effectiveness of the control strategy. Simulation results indicate that the proposed strategy satisfies frequency regulation requirements, enhances power generation efficiency, and improves the economic viability of photovoltaic operations.

Comprehensive Quantitative Evaluation of the Photovoltaic Grid-Connected Power Generation System Adopting nX DC/DC Converter

Comprehensive Quantitative Evaluation of the Photovoltaic Grid-Connected Power Generation System Adopting nX DC/DC Converter

Simulation system of intelligent photovoltaic grid-connected inverter considering fuzzy PI control

The grid connected inverter is the core component of the photovoltaic grid connected power generation system, which mainly converts the direct current of the photovoltaic matrix into alternating current that meets the grid connected requirements, playing a key role in the efficient and stable operation of the photovoltaic grid connected power generation system.This paper uses fuzzy PI control model which to improve the performance of intelligent photovoltaic grid-connected inverter to simulate the intelligent photovoltaic inverter system, using mathematical analysis and reasoning methods for model analysis,adopts two-stage three-phase LCL grid-connected inverter, establishes mathematical models in two-phase synchronous rotating and two-phase static coordinate systems, and adopts an active damping strategy based on grid-connected current. Based on existing research and empirical analysis,aiming at the disadvantage of poor dynamic response of repetitive control, an improved repetitive control strategy is adopted, and the controller is analyzed from two aspects of stability and dynamic performance, and the simulation model of photovoltaic grid-connected power generation system is built. Use experimental analysis method to verify the effectiveness of the model in this article,The experimental results show that the simulation system of intelligent photovoltaic grid-connected inverter considering fuzzy PI control proposed in this paper has certain effects.

A decentralized control strategy for single‐phase cascaded photovoltaic inverters with MPPT ability

AbstractCascaded inverters can improve efficiency and reduce cost, so it is widely used in photovoltaic (PV) grid connected power generation system. However, aging or partial shielding of PV panels will lead to their different maximum power points (MPP). This paper proposes a decentralized control strategy for grid‐connected cascaded PV inverters without any communication, which is capable of integrating PV inverters of different capacities connected in series into the grid, and enable them to achieve maximum power point tracking (MPPT) independently. Compared with the traditional centralized control method relying on real‐time communication, the proposed scheme has advantages of improved reliability and decreased costs. The overall system stability is analysed, and the stability condition is derived as well. The Hardware‐In‐the‐Loop test results show that all the inverters in the cascaded system have their output frequency and voltage phase synchronized autonomously, and achieve MPPT independently even in the presence of variation of light condition. Thus, the feasibility of the proposed method is verified.

Grid Integration of Livestock Biogas Using Self-Excited Induction Generator and Spark-Ignition Engine

This study developed a grid-connected biogas power generation system for a rural community using a 3-phase 2.2 kW squirrel-cage induction machine as the self-excited induction generator. The generator was driven by a 196 cc single-cylinder spark-ignition engine fueled by biogas. We developed a back-to-back converter that consists of a 3-phase PWM rectifier as the generator-side converter and a single-phase LCL-filtered grid-connected inverter. The generator-side converter transferred the active power to the grid-side converter and supplied the reactive power control back to the generator. The notch filter-based bus voltage control on the generator side mitigated the inter-harmonics in the generator current. The injected grid current complied with the IEEE 1547 standard because of the multi-frequency unbalanced synchronous reference frame control. The proposed system was validated with biogas produced from pig manure at a pig farm in central Thailand, which found a maximum output of 1.2 kW with a thermal system efficiency of 10.7%. The proposed system was scheduled to operate at 1.2 kW for 8 h per day with a levelized cost of 0.07 US$/kWh, 42% cheaper than the retail electricity price, and a payback period of 2.76 years. The proposed system is suitable for a farm with a minimum of 34 pigs.

Different DC-Link Control Methods with Multilevel Inverter for Low Harmonic and Efficient Power Transfer in Grid-Tied Hydrogen Fuel Cell Systems

In grid-connected power generation systems, dc-link voltage control is needed to prevent energy losses, reduce voltage fluctuations and provide a stable energy flow. In addition, control of the power factor via the voltage source inverter is a process that supports the efficient use of the energy produced. Moreover, keeping the total harmonic distortion (THD) of the current injected into the grid in accordance with IEEE-519 harmonic standards (

Dynamic phasor-based hybrid simulation for multi-inverter grid-connected system

To realize the efficient transient simulation of a grid-connected power generation system based on multiple inverters, this paper proposes a hybrid simulation method integrating the models of electromagnetic transient and dynamic phasors. Based on a demonstration of the concepts and properties of dynamic phasors, the models of single-phase and three-phase inverters described by dynamic phasors are established first. Considering the numerical compatibility problem between dynamic phasors and instantaneous values, an interface scheme between dynamic phasors and instantaneous values is designed, and the efficiency and precision differences of various transformation methods are compared in detail. Finally, by utilizing MATLAB/Simulink, a hybrid simulation platform of a multi-inverter grid-connected system is built, and the efficiency and accuracy of the hybrid simulation are validated via comparison with the full electromagnetic transient simulation.

A Survey of the Researches on Grid-Connected Solar Power Generation Systems and Power Forecasting Methods Based on Ground-Based Cloud Atlas

Photovoltaic power generating is one of the primary methods of utilizing solar energy resources, with large-scale photovoltaic grid-connected power generation being the most efficient way to fully utilize solar energy. In order to provide reference strategies for pertinent researchers as well as potential implementation, this paper tries to provide a survey investigation and technical analysis of machine learning-related approaches, statistical approaches and optimization techniques for solar power generation and forecasting. Deep learning-related methods, in particular, can theoretically handle arbitrary nonlinear transformations through proper model structural design, such as hidden layer topology optimization and objective function analysis to save information that can increase forecasting accuracy while filtering out irrelevant or less affected data for forecasting. The research’s results indicate that RBFNN-AG performed the best when applying the predetermined number of days, with an NRMSE value of 4.65%. RBFNN-AG performs better than sophisticated models like DenseNet (5.69%), SLFN-ELM (5.95%), and ANN-k-means-linear regression correction (6.11%). Additionally, scenario application and PV system investment techniques are provided to evaluate the current condition of new energy development and market trends both domestically and internationally.

Artificial intelligence based active and reactive power control method for single-phase grid connected hydrogen fuel cell systems

In grid-connected power generation systems, power factor fluctuations caused by non-linear power circuits used between the grid and source should be controlled with the help of voltage source inverters (VSI). In addition, in order to improve the quality of the electrical energy injected into the grid and to prevent possible electrical faults, the total harmonic distortion (THD) in the grid current should be controlled in accordance with IEEE-519 standards. In other respects, uncontrolled injected energy may causes losses, excessive electrical energy demand and overloading. In this study, an artificial neural network based active and reactive power control method is proposed for grid-connected single-phase Proton Exchange Membrane Hydrogen Fuel Cell (PEMFC). The aim of the proposed control structure is to have low harmonic distortion, high power factor performance as well as an easy and understandable structure. The proposed method was applied to a 6 kW prototype. Five different scenarios and nine different activation function were tried to verify the performance of the proposed control method. As a result of these processes, the power factor was measured as unity (>0.99) and the total harmonic distortion (THD) of the grid current, under all operation states, is <2%. In addition, it has been observed that the success rate of artificial neural networks is >97%.

Game theoretic of sizing optimization for Wind/PV/EVs based on representative days selection

• Game theory solves the problem of new energy power generation equipment capacity planning. • Electric vehicles connect to hybrid power generation systems as auxiliary equipment to replace energy storage batteries. • Establish a representative days selection model based on mixed integer multi-objective linear programming (MIMLP). • Consider the uncertainty of electric vehicle traffic attributes. In recent years, hybrid power systems (HPSs) with renewable energy sources, such as wind power and photovoltaic (PV) power, have been used as one of the most effective methods to address resource shortages and environmental pollution. In this paper, a model based non-cooperative game theory is developed to optimize the capacity configuration problem with wind power, PV power, and electric vehicles (EVs). The model is integrated with economic factors, such as electricity sales income, investments, and power supply reliability costs. An iterative search algorithm is used to solve the proposed game model, and the particle swarm optimization algorithm was used to optimize the income of each player. Mixed integer multi-objective linear programming (MIMLP) is used to establish the representative days selection model of resources and load demands. To verify the rationality of the model, the grid-connected hybrid power generation system with different game participants and line transmission capacities was studied. Furthermore, the representative days results of the daily load rate and peak valley ratio generated by MIMLP are compared with those obtained using k -means clustering and a scenario reduction method. The results reveal that the proposed model and related strategies can realize a reasonable allocation of resources and effectively improve the operation economy of power systems.

Power coupling and grid-connected support control of the PV/ESS power generation system with virtual inertia

Under virtual synchronous control, the photovoltaic energy storage grid-connected system can realize synchronous grid connection. However, the power coupling relationship between units needs to be analyzed to reduce additional operation risks and improve the support performance of virtual synchronous control. In this paper, the definition of virtual inertia of the energy storage device is described, and the power coupling relationship between the virtual synchronous generator and synchronous generator is analyzed by establishing a small-signal model of photovoltaic energy storage grid-connected power generation system. The influence of the power coupling control coefficient on the static and transient stability of the grid-connected system is analyzed by the extended equal area rule and eigenvalue method. Based on this, a power coupling control strategy is proposed to improve inertia and damping support performance. Finally, a grid-connected power generation simulation system with a high proportion of photovoltaic energy storage is built to test and verify. The results demonstrate that the proposed control can reduce the risk of power oscillation induced by virtual inertia and improve the grid-connected system’s frequency support and power oscillation suppression ability.

Study on the influence of grid connected capacity difference of photovoltaic power generation on power grid performance

Due to the integration of photovoltaic power generation system, the structure of traditional distribution network will change, and then the grid system after grid connection is in an abnormal working state. If relevant measures are not taken, the operation quality of grid cannot be guaranteed. Therefore, based on the working principle of photovoltaic cells, this paper studies its equivalent model and output characteristics, builds a single-stage three-phase photovoltaic grid connected system on PSCAD platform, verifies the correctness of power control strategy, analyses the impact of photovoltaic grid connection on distribution network loss and voltage, establishes a 33 node model for example analysis, and simulates the grid connection of photovoltaic power generation system under different capacities and locations for many times, the calculation example of determining the location and capacity of photovoltaic grid connected power generation system is analysed, and a multi-objective mathematical model is proposed based on DG cost and active power loss. The installation quantity, capacity and location of DG are deeply studied, and the optimization function is carried out based on genetic algorithm, so as to realize the minimum impact condition of photovoltaic grid connected power generation on power quality of distribution network, and then realize the optimal configuration of photovoltaic power generation system.

Tidal current prediction based on a hybrid machine learning method

Accurate and reliable tidal current forecasting plays a key role in application of grid-connected tidal current power generation systems. Hence, a novel tidal current prediction method based on a hybrid machine learning method is proposed in this paper. Compared with previous tidal current prediction method, the proposed tidal current prediction method considers the influence of turbulence on multi-layer tidal velocity difference. A hybrid machine learning method based on hierarchical extreme learning machine(H-ELM) and long short-term memory (LSTM) is adopted to reduce effect of the turbulent flow, which enables to increase the accuracy of the prediction result. The tidal data that collected by using acoustic doppler current profiler (ADCP) in Zhejiang province China is used to validate the effectiveness of the proposed method. The results of the case study show that the proposed method has higher accuracy than results from standard harmonic analysis using UTide (a freely available academic research product).

Optimization of stand-alone and grid-connected hybrid solar/wind/fuel cell power generation for green islands: Application to Koh Samui, southern Thailand

This paper presents the optimization of stand-alone and grid-connected hybrid power generation systems for green islands, with application to Koh Samui in southern Thailand. A techno-economic optimization analysis is applied using the Hybrid Optimization Model for Electric Renewable (HOMER) Pro simulation tool. Four scenarios are identified to select the most suitable solution for a hybrid renewable energy system (HRES) integrating solar photovoltaic (PV), wind turbine generator (WTG), fuel cell (FC), and battery energy storage (Li-Ion), with backup diesel generation or grid connection with the mainland as options. The NASA-SSE and MERRA databases are used as inputs to analyze the solar and wind energy potentials, respectively. The results show that the levelized cost of energy (LCOE) of the HRES with a grid connection to the mainland (Scenario 3) has the lowest LCOE (0.132 US$/kWh), but at large greenhouse gas (GHG) emission costs (20.5 ktonnes/year) due to the high carbon intensity of Thailand’s power portfolio. A stand-alone, 100% renewable energy system (Scenario 4) includes a PV capacity of 182 MW, a wind power capacity of 8 MW, a fuel cell system of 10 MW, a 17.9 MW power converter, and 211 MWh of battery storage. The net present cost (NPC) of this system is 542 MUS$ and the LCOE is 0.309 US$/kWh, with 89% of the energy generated by the solar PV system. Therefore, a 100% renewable energy-based microgrid system is possible on Koh Samui as it can provide a more suitable and reliable solution when considering a HRES system for the total load demand (104 MW of peak load) of the island. Finally, the economic analysis also reveals that the investment in a HRES system is feasible as the payback period is 9 years under an internal rate of return (IRR) of 10% and an appropriate Feed-in-Tariff (FiT) of 0.385 US$/kWh.

Design of a Three Phase Z-Source Inverter for Photovoltaic Systems

Due to the danger of extinction of fossil energy resources and their harmful effects on the environment, interest in renewable energy sources has increased today. Furthermore, the photovoltaic energy, which is among renewable energy sources, has started to gain importance day by day. Especially, grid-connected Photovoltaic (PV) power generation systems have begun to be installed and used widely. In the grid-connected power generation systems, variable environmental conditions cause the DC voltage obtained from the PV systems to vary continuously. In the applications where traditional inverters are used, additional DC/DC converters are required to obtain an output at the desired frequency and amplitude. On the other hand, Z-source inverters which are a new concept can perform this raising and lowering process without the need for any intermediate circuit elements, thanks to the impedance network in their structures. For this reason, in this paper, Z-source inverter is designed for the PV systems. Z-source inverter modeling with impedance network is realized by using a simple boost switching method, and the modulation index and duty cycle parameters are adjusted to increase the DC voltage applied to its input. It is observed from the simulation results that using of the Z-source inverter is proper and efficient in the PV power generation systems.

Dynamic Circulating Current Suppression Method for Multiple Hybrid Power Parallel Grid-Connected Inverters With Model Reference Adaptive System

Aiming at the problem of large harmonic distortion of grid-connected current in high-power grid-connected power generation system under weak sunlight, multiple hybrid power parallel inverters (MHPPIs) composed of some identical high-power inverters and one low-power inverter in parallel are proposed. According to the irradiance change of sunlight, the low-power inverter operates alone or cooperates with the switching process between the high-power inverters to ensure the low grid-connected current harmonics. Where, any inverters operate in four common working processes, such as soft start-up, steady-state operation, abrupt change of current, and soft stop. Due to the short running time of the dynamic process, most of the existing researches focus on the circulating current suppression under the steady-state condition. However, in engineering practice, the dynamic circulating current in the switching process between inverters is more likely to cause the over-current protection and other safe and stable operation problems of parallel inverters. Therefore, a dynamic circulating current suppression method with dynamic impedance matching for parallel inverters is proposed in this article. The working process of the MHPPIs is equivalent to that of two inverters. The dynamic working process is analyzed in detail, and the dynamic impedance mismatch is the main cause of the dynamic circulating current, so the dynamic virtual inductance matching is introduced to suppress it. Meanwhile, an online inductance identification method based on the model reference adaptive system is presented to compensate for the influence of inaccurate inductance parameter on the circulating current suppression and current control. An experimental prototype of equivalent MHPPIs is built and experimental results prove the validity of the proposed control method.

Dynamic Performance Evaluation of Grid-Connected Hybrid Renewable Energy-Based Power Generation for Stability and Power Quality Enhancement in Smart Grid

Today’s stochastic grid system is experiencing huge voltage fluctuations, which is responsible for power quality issues in the smart microgrid network due to its intermittent nature as well as penetration of hybrid renewable resources. Thus, the dynamic performance evaluation and their control are essential to sustaining the stability of the grid network. A d-q controller mechanism is suggested to maintain the balance of the distributed generation network and grid side network. A dynamic control mechanism of voltage source converter (VSC) is presented in the MPPT-based wind power generating station, where an induction generator generates the power by the optimal control of the wind energy-based subsystem. The distributed hybrid generation (solar PV and wind) subsystem’s output terminal is linked to the DC bus bar’s common link via the VSC. A VSI is utilized to convert the desired DC power to alternating current power. To regulate and improve the performance of the proposed hybrid power generating systems (HPGS), a supercapacitor (SC) is used to smooth out the ripple on the distribution side in the power grid. Furthermore, the dynamic stability of grid-connected solar PV and wind power generation systems is investigated. This article also proposed an effective control scheme for the SC in HPGS under the influence of weak grid conditions. This article aimed to validate the efficiency of the VSI topology; a PI controller stability enhancement approach is used in a proposed grid system under various disturbance conditions. Finally, the simulation results and FFT-based power quality response analysis are validated through the effective utilization of an SC.

A modified power decoupling control strategy for a grid-connected inverter with a low switching frequency under unbalanced grid voltages

In the photovoltaic grid-connected power generation system, when proportional resonant (PR) control is adopted for the grid-side inverter in the two-phase stationary coordinate (αβ), there is a coupling problem between active power (P) and reactive power (Q). Under unbalanced grid conditions, especially in high-power applications where the switching frequency of the grid inverter needs to be reduced, the power coupling problem will be exacerbated. Based on the instantaneous power response characteristics of the grid inverter, expressions of the power coupling coefficient under unbalanced power grids are derived in this paper, and the influence of the unbalanced grid voltage on the power coupling is revealed. Moreover, a decoupled grid-side model of the grid inverter is established, and a modified controller based on positive and negative sequence (P–N sequence) decoupling is proposed to solve the power coupling problem. The closed-loop transfer function of the system with the modified current controller is studied, and the stability of the modified controller is analyzed according to the bilateral frequency response diagram. Based on analysis of the coupling coefficient, the degree of coupling between P and Q can be reduced significantly by applying the proposed control method. Furthermore, in order to solve the influence of the delay on the power coupling caused by the low switching frequency, the decoupling compensation link for the delay is introduced, which can eliminate the influence of delay on power coupling. Finally, experiments are performed on a grid-connected inverter prototype. The experimental results show that when the grid voltage is unbalanced, the proposed control method can reduce the coupling degree of the P and Q, which also improves the dynamic performance of the grid-connected inverter with a low switching frequency.

Current PIλ Control of the Single-Phase Grid Inverter

In a grid-connected power generation system, the grid-connected current of the inverter is sensitive to nonlinear factors such as periodic disturbance of grid voltage, which results in grid-connected current waveform distortion. By establishing a single-phase photovoltaic grid-connected inverter control system model, designing an inverse current fractional-order PI (PIλ or FO-PI) controller and the dynamic and steady-state performance, antidisturbance and grid connection inversion characteristics of the system are simulated and compared under the action of the integer-order PI controller and fractional-order PI controller. The quality of the inverter grid-connected current is analyzed by using the fast Fourier transform (FFT). The simulation results show that the fractional-order control system can reduce the total harmonic distortion (THD) of the grid-connected current and dynamic performance and antidisturbance ability of the improving system while satisfying the steady-state performance indexes.

Model predictive control of grid-connected PV power generation system considering optimal MPPT control of PV modules

Because of system constraints caused by the external environment and grid faults, the conventional maximum power point tracking (MPPT) and inverter control methods of a PV power generation system cannot achieve optimal power output. They can also lead to misjudgments and poor dynamic performance. To address these issues, this paper proposes a new MPPT method of PV modules based on model predictive control (MPC) and a finite control set model predictive current control (FCS-MPCC) of an inverter. Using the identification model of PV arrays, the module-based MPC controller is designed, and maximum output power is achieved by coordinating the optimal combination of spectral wavelength and module temperature. An FCS-MPCC algorithm is then designed to predict the inverter current under different voltage vectors, the optimal voltage vector is selected according to the optimal value function, and the corresponding optimal switching state is applied to power semiconductor devices of the inverter. The MPPT performance of the MPC controller and the responses of the inverter under different constraints are verified, and the steady-state and dynamic control effects of the inverter using FCS-MPCC are compared with the traditional feedforward decoupling PI control in Matlab/Simulink. The results show that MPC has better tracking performance under constraints, and the system has faster and more accurate dynamic response and flexibility than conventional PI control.