This article investigates the robust current tracking control problem of three-phase grid-connected inverters with LCL filter under external disturbance by a dynamic state feedback control method.First,this paper cons...This article investigates the robust current tracking control problem of three-phase grid-connected inverters with LCL filter under external disturbance by a dynamic state feedback control method.First,this paper constructs an internal model to learn the information of the states and input of the grid-connected inverter under steady state.Second,by utilizing the internal model principle,the paper turns the tracking control problem into the robust stabilization control problem based on some appropriate coordinate transformations.Then,The paper designs a dynamics state feedback control law to deal with this robust stabilization problem,and thus the solution of the robust current tracking control problem of three-phase grid-connected inverters can be obtained.This control method can ensure the asymptotic stability of the closedloop system.Finally,the paper illustrates the effectiveness of the proposed control approach through several groups of simulations,and compares it with the feedforward control method to verify the robustness of the proposed control method to uncertain parameters.展开更多
The hybrid series-parallel microgrid attracts more attention by combining the advantages of both the series-stacked voltage and parallel-expanded capacity.Low-voltage distributed generations(DGs)are connected in serie...The hybrid series-parallel microgrid attracts more attention by combining the advantages of both the series-stacked voltage and parallel-expanded capacity.Low-voltage distributed generations(DGs)are connected in series to form the intra-string,and then multiple strings are interconnected in parallel.For the existing control strategies,both intra-string and inter-string depend on the centralized or distributed control with high communication reliance.It has limited scalability and redundancy under abnormal conditions.Alternatively,in this study,an intra-string distributed and inter-string decentralized control framework is proposed.Within the string,a few DGs close to the AC bus are the leaders to get the string power information and the rest DGs are the followers to acquire the synchronization information through the droop-based distributed consistency.Specifically,the output of the entire string has the active power−angular frequency(ω-P)droop characteristic,and the decentralized control among strings can be autonomously guaranteed.Moreover,the secondary control is designed to realize multi-mode objectives,including on/off-grid mode switching,grid-connected power interactive management,and off-grid voltage quality regulation.As a result,the proposed method has the ability of plug-and-play capabilities,single-point failure redundancy,and seamless mode-switching.Experimental results are provided to verify the effectiveness of the proposed practical solution.展开更多
The integration of renewable energy sources into modern power systems necessitates efficient and robust control strategies to address challenges such as power quality,stability,and dynamic environmental variations.Thi...The integration of renewable energy sources into modern power systems necessitates efficient and robust control strategies to address challenges such as power quality,stability,and dynamic environmental variations.This paper presents a novel sparrow search algorithm(SSA)-tuned proportional-integral(PI)controller for grid-connected photovoltaic(PV)systems,designed to optimize dynamic perfor-mance,energy extraction,and power quality.Key contributions include the development of a systematic SSA-based optimization frame-work for real-time PI parameter tuning,ensuring precise voltage and current regulation,improved maximum power point tracking(MPPT)efficiency,and minimized total harmonic distortion(THD).The proposed approach is evaluated against conventional PSO-based and P&O controllers through comprehensive simulations,demonstrating its superior performance across key metrics:a 39.47%faster response time compared to PSO,a 12.06%increase in peak active power relative to P&O,and a 52.38%reduction in THD,ensuring compliance with IEEE grid standards.Moreover,the SSA-tuned PI controller exhibits enhanced adaptability to dynamic irradiancefluc-tuations,rapid response time,and robust grid integration under varying conditions,making it highly suitable for real-time smart grid applications.This work establishes the SSA-tuned PI controller as a reliable and efficient solution for improving PV system performance in grid-connected scenarios,while also setting the foundation for future research into multi-objective optimization,experimental valida-tion,and hybrid renewable energy systems.展开更多
The advantages and promoting applications of the microgrids community(MGC)allows for a critical step being taken toward a smart grid.An energy management strategy(EMS)is essential to intelligently coordinate the opera...The advantages and promoting applications of the microgrids community(MGC)allows for a critical step being taken toward a smart grid.An energy management strategy(EMS)is essential to intelligently coordinate the operations of the MGC.This paper presents a multi-time-scale EMS consid-ering battery operational modes for grid-connected MGCs.The proposed strategy consists of two modules:day-ahead integrated optimization and realtime distributed compensation.The first module aims to minimize the operational cost of the MGC considering battery free-overcharging protecting.This problem is solved by the mixed integer linear programming(MILP)sim-ulating two charging/discharging modes:limited-current mode and constant-voltage mode.The second module is installed in local MGs to correct the optimizing deviations of the day-ahead static scheduling,which are caused by predicting errors of renewable energy and loads.The main contribution of this work is integrating the advantages of global optimization of the centralized method and the fast computing speed of the distributed method.Experimental results prove the proposed EMS is feasible and effective.The computing time at each updating step is reduced by 75%on average,which has the potential to be adopted in engineering.展开更多
This paper presents the development of improved synergetic current control for the injected current of an inverter in the grid-connected microgrid and the distributed generation system(DGS). This paper introduces new ...This paper presents the development of improved synergetic current control for the injected current of an inverter in the grid-connected microgrid and the distributed generation system(DGS). This paper introduces new formulas of the macro-variable functions for integral synergetic control(SC)and integral fast terminal SC, which both have an integral term to guarantee zero steady-state error. The proposed integral SC and integral fast terminal SC achieve a seamless performance such as the fast convergence, minimal overshoot, zero steady-state error, and chattering-free operation. To demonstrate the meritorious performance of the proposed scheme for injected current control, it is compared with the performance of a proportional-integral(PI) controller and advanced exponential sliding mode control(SMC). Finally, the practicality of the proposed scheme is justified by experimental results obtained through rapid control prototyping(RCP) using the dSPACESCALEXIO platform.展开更多
This paper presents a real-time power flow controller for VSIs （voltage source inverters） interfaced to low voltage microgrids. The proposed controller is modular, flexible, intelligent, inexpensive, portable, adapt...This paper presents a real-time power flow controller for VSIs （voltage source inverters） interfaced to low voltage microgrids. The proposed controller is modular, flexible, intelligent, inexpensive, portable, adaptive and designed to positively contribute in low voltage microgrids in which the lines R/X ratio is greater than the transmission lines. Therefore, the proposed control strategy is developed for operation in distribution lines. The controller strategy is different from the conventional grid-connected inverters which are designed based on transmission line characteristics. This controller, using a Texas Instrument general purpose DSP （digital signal processor）, is programmed and tuned using MATLAB/SIMULINK in order to enhance self-healing, reliability and stability of the grid. This general purpose controller makes proper decisions using its local measurements as the primary source of data. The controller has the capability of communicating with the adjacent controllers and sharing the information if/when needed. The power flow output of the inverter is tested for both islanded and grid-connected modes of operation. The inverter positively contributes to active and reactive power supply while operating in grid-connected mode. The proposed control method has been implemented on a Texas Instrument DSC （digital signal controller） chip and tested on a hardware test bench at the Alternative Energy Laboratory at WVU1T （West Virginia University Institute of Technology）. The system＇s experimental results veri~ the validity and efficiency of the proposed controller.展开更多
This paper presents a novel machine learning(ML)enhanced energy management framework for residential microgrids.It dynamically integrates solar photovoltaics(PV),wind turbines,lithium-ion battery energy storage system...This paper presents a novel machine learning(ML)enhanced energy management framework for residential microgrids.It dynamically integrates solar photovoltaics(PV),wind turbines,lithium-ion battery energy storage systems(BESS),and bidirectional electric vehicle(EV)charging.The proposed architecture addresses the limitations of traditional rule-based controls by incorporating ConvLSTM for real-time forecasting,a Twin Delayed Deep Deterministic Policy Gradient(TD3)reinforcement learning agent for optimal BESS scheduling,and federated learning for EV charging prediction—ensuring both privacy and efficiency.Simulated in a high-fidelity MATLAB/Simulink environment,the system achieves 98.7%solar/wind forecast accuracy and 98.2% Maximum Power Point Tracking(MPPT)tracking efficiency,while reducing torque oscillations by 41% and peak demand by 22%.Compared to baseline methods,the solution improves voltage and frequency stability(maintaining 400V±2%,50Hz±0.015Hz)and achieves a 70% reduction in battery State of Charge(SOC)management error.The EV scheduler,informed by data from over 500 households,reduces charging costs by 31% with rapid failover to critical loads during outages.The architecture is validated using ISO 8528-8 transient tests,demonstrating 99.98% uptime.These results confirm the feasibility of transitioningmicrogrids fromreactive systems to adaptive,cognitive infrastructures capable of self-optimization under highly variable renewable generation and EV behaviors.展开更多
Most developing countries continue to face challenges in accessing sustainable energy.This study investigates a solar panel and battery-powered system for an urban off-grid microgrid in Nigeria,where demand-sideflexib...Most developing countries continue to face challenges in accessing sustainable energy.This study investigates a solar panel and battery-powered system for an urban off-grid microgrid in Nigeria,where demand-sideflexibility and strategic interactions between households and utilities can optimize system sizing.A nonlinear programming model is built using bilevel problem formulation that incorporates both the households’willingness to reduce their energy consumption and the utility’s agreement to provide price rebates.The results show that,for an energy community of 10 households with annual energy demand of 7.8 MWh,an oversized solar-storage system is required(12 kWp of photovoltaic solar panels and 26 kWh of battery storage).The calculated average cost of 0.31€/kWh is three times higher than the current tariff,making it unaffordable for most Nigerian households.To address this,the utility company could implement Demand Response programs with direct load control that delay the use of certain appliances,such as fans,irons and air conditioners.If these measures reduce total demand by 5%,both the required system size and overall costs could decrease significantly,by approximately one-third.This adjustment leads to a reduced tariffof 0.20€/kWh.When Demand Response is imple-mented through negotiation between the utility and households,the amount of load-shaving achieved is lower.This is because house-holds experience discomfort from curtailment and are generally less willing to provideflexibility.However,negotiation allows for greaterflexibility than direct control,due to dynamic interactions and more active consumer participation in the energy transition.Nonetheless,tariffs remain higher than current market prices.Off-grid contracts could become competitive iffinancial support is pro-vided,such as low-interest loans and capital grants covering up to 75%of the upfront cost.展开更多
Three-phase grid-connected inverters(GCIs)are essential components in distributed generation systems,where the accuracy of current measurement circuits is fundamental for reliable closed-loop operation.Nevertheless,th...Three-phase grid-connected inverters(GCIs)are essential components in distributed generation systems,where the accuracy of current measurement circuits is fundamental for reliable closed-loop operation.Nevertheless,the presence of a DC offset in the measured current can disrupt the regulation of grid currents and significantly degrade system performance.In this work,a fault-tolerant control approach is introduced to counteract the impact of such offset faults through a dedicated current compensation mechanism.The proposed solution is built around two main stages:(i)detecting and isolating DC offset faults that may appear in one or multiple phases of the measured grid currents,and(ii)estimating the fault magnitude and reconstructing the corrected current signal.The offset magnitude is obtained analytically by examining the grid current projected onto the synchronous d-axis at the grid angular frequency,eliminating the need for any additional sensing hardware.Simulation and experimental investigations conducted under several fault scenarios confirm the robustness of the proposed strategy and highlight significant improvements in detection speed and diagnostic accuracy.展开更多
The supply of electricity to remote regions is a significant challenge owing to the pivotal transition in the global energy landscape.To address this issue,an off-grid microgrid solution integrated with energy storage...The supply of electricity to remote regions is a significant challenge owing to the pivotal transition in the global energy landscape.To address this issue,an off-grid microgrid solution integrated with energy storage systems is proposed in this study.Off-grid microgrids are self-sufficient electrical networks that are capable of effectively resolving electricity access problems in remote areas by providing stable and reliable power to local residents.A comprehensive review of the design,control strategies,energy management,and optimization of off-grid microgrids based on domestic and international research is presented in this study.It also explores the critical role of energy stor-age systems in enhancing microgrid stability and economic efficiency.Additionally,the capacity configurations of energy storage systems within off-grid networks are analyzed.Energy storage systems not only mitigate the intermittency and volatility of renewable energy gen-eration but also supply power support during peak demand periods,thereby improving grid stability and reliability.By comparing different energy storage technologies,such as lithium-ion batteries,pumped hydro storage,and compressed air energy storage,the optimal energy storage capacity configurations tailored to various application scenarios are proposed in this study.Finally,using a typical micro-grid as a case study,an empirical analysis of off-grid microgrids and energy storage integration has been conducted.The optimal con-figuration of energy storage systems is determined,and the impact of wind and solar power integration under various scenarios on grid balance is explored.It has been found that a rational configuration of energy storage systems can significantly enhance the utilization rate of renewable energy,reduce system operating costs,and strengthen grid resilience under extreme conditions.This study provides essential theoretical support and practical guidance for the design and implementation of off-grid microgrids in remote areas.展开更多
Around the world,there has been a notable shift toward the use of renewable energy technology due to the growing demand for energy and the ongoing depletion of conventional resources,such as fossil fuels.Following thi...Around the world,there has been a notable shift toward the use of renewable energy technology due to the growing demand for energy and the ongoing depletion of conventional resources,such as fossil fuels.Following this worldwide trend,Brunei’s government has initiated several strategic programs aimed at encouraging the establishment of energy from renewable sources in the nation’s energy mix.These initiatives are designed not only to support environmental sustainability but also to make energy from renewable sources increasingly competitive in comparison to more conventional energy sources like gas and oil,which have historically dominated Brunei’s energy market.The optimization of a hybrid energy system that combines diesel generators,solar photovoltaic(PV)panels,and the national power grid is the focus of this study.The objective is to identify the most cost-effective and environmentally sustainable configuration that can reliably meet local energy demands.During optimization,several configuration was tried and tested,including only grid,PV and Grid and PV-generator.HOMER(Hybrid Optimization of Multiple Energy Resources)software,a popular simulation tool that makes it possible to simulate and analyze hybrid energy systems,is utilized in the optimization process.Inside the HOMER Pro optimization,various system configuration is taken into account for the optimization.While simulating,it takes into account different combinations of components such as solar panels,wind turbines and batteries.Later on,it is being ranked by different factors such as net present cost(NPC),Cost of Energy(COE),etc.A comprehensive techno-economic research is carried out to evaluate various system configurations,considering key performance indicators such as total energy generation cost,operational expenditure,and greenhouse gas emissions.The results provide valuable insights into how renewable-based hybrid systems can reduce environmental impact while maintaining economic viability,supporting Brunei’s broader goals of energy diversification and sustainability.The study also emphasizes how such hybrid systems could be scaled for off-grid and rural populations in Brunei,where a dependable electricity supply is still a problem.Furthermore,sensitivity analyses were performed to evaluate the effects of variations in solar irradiation,load demand,and fuel prices on the overall system performance.Policymakers and energy planners can use these insights to help them make data-driven decisions about future investments in infrastructure for renewable energy.展开更多
The dynamic average consensus(DAC)algorithm is to enable a group of networked agents to track the average of their time-varying reference signals.For most existing DAC algorithms,a necessary assumption is that the upp...The dynamic average consensus(DAC)algorithm is to enable a group of networked agents to track the average of their time-varying reference signals.For most existing DAC algorithms,a necessary assumption is that the upper bounds of the reference signals and their derivatives are known in advance,thereby posing significant challenges in practical scenarios.Introducing adaptive gains in DAC algorithms provides a remedy by relaxing this assumption.However,the current adaptive gains used in this type of DAC algorithms are non-decreasing and may increase to infinity if persist disturbance exists.In order to overcome this defect,this paper presents a novel DAC algorithm with modified adaptive gains.This approach obviates the necessity for prior knowledge concerning the upper bounds of the reference signals and their derivatives.Moreover,the adaptive gains are able to remain bounded even in the presence of external disturbances.Furthermore,the proposed adaptive DAC algorithm is employed to address the distributed secondary control problem of DC microgrids.Comparative case studies are provided to verify the superiority of the proposed DAC algorithm.展开更多
The proliferation of distributed and renewable energy resources introduces additional operational challenges to power distribution systems.Transactive energy management,which allows networked neighborhood communities ...The proliferation of distributed and renewable energy resources introduces additional operational challenges to power distribution systems.Transactive energy management,which allows networked neighborhood communities and houses to trade energy,is expected to be developed as an effective method for accommodating additional uncertainties and security mandates pertaining to distributed energy resources.This paper proposes and analyzes a two-layer transactive energy market in which houses in networked neighborhood community microgrids will trade energy in respective market layers.This paper studies the blockchain applications to satisfy socioeconomic and technological concerns of secure transactive energy management in a two-level power distribution system.The numerical results for practical networked microgrids located at IllinoisTech−Bronzeville in Chicago illustrate the validity of the proposed blockchain-based transactive energy management for devising a distributed,scalable,efficient,and cybersecured power grid operation.The conclusion of the paper summarizes the prospects for blockchain applications to transactive energy management in power distribution systems.展开更多
Given the rapid development of advanced information systems,microgrids(MGs)suffer from more potential attacks that affect their operational performance.Conventional distributed secondary control with a small,fixed sam...Given the rapid development of advanced information systems,microgrids(MGs)suffer from more potential attacks that affect their operational performance.Conventional distributed secondary control with a small,fixed sampling time period inevitably causes the wasteful use of communication resources.This paper proposes a self-triggered secondary control scheme under perturbations from false data injection(FDI)attacks.We designed a linear clock for each DG to trigger its controller at aperiodic and intermittent instants.Sub-sequently,a hash-based defense mechanism(HDM)is designed for detecting and eliminating malicious data infiltrated in the MGs.With the aid of HDM,a self-triggered control scheme achieves the secondary control objectives even in the presence of FDI attacks.Rigorous theoretical analyses and simulation results indicate that the introduced secondary control scheme significantly reduces communication costs and enhances the resilience of MGs under FDI attacks.展开更多
Low-voltage direct current(DC)microgrids have recently emerged as a promising and viable alternative to traditional alternating cur-rent(AC)microgrids,offering numerous advantages.Consequently,researchers are explorin...Low-voltage direct current(DC)microgrids have recently emerged as a promising and viable alternative to traditional alternating cur-rent(AC)microgrids,offering numerous advantages.Consequently,researchers are exploring the potential of DC microgrids across var-ious configurations.However,despite the sustainability and accuracy offered by DC microgrids,they pose various challenges when integrated into modern power distribution systems.Among these challenges,fault diagnosis holds significant importance.Rapid fault detection in DC microgrids is essential to maintain stability and ensure an uninterrupted power supply to critical loads.A primary chal-lenge is the lack of standards and guidelines for the protection and safety of DC microgrids,including fault detection,location,and clear-ing procedures for both grid-connected and islanded modes.In response,this study presents a brief overview of various approaches for protecting DC microgrids.展开更多
Interconnection planning involving bi-directional converters(BdCs)is crucial for enhancing the reliability and robustness of hybrid alternating current(AC)/direct current(DC)microgrid clusters with high penetrations o...Interconnection planning involving bi-directional converters(BdCs)is crucial for enhancing the reliability and robustness of hybrid alternating current(AC)/direct current(DC)microgrid clusters with high penetrations of renewable energy resources(RESs).However,challenges such as the non-convex nature of BdC efficiency and renewable energy uncertainty complicate the planning process.To address these issues,this paper proposes a tri-level BdC-based planning framework that incorporates dynamic BdC efficiency and a data-correlated uncertainty set(DcUS)derived from historical data patterns.The proposed framework employs a least-squares approximation to linearize BdC efficiency and constructs the DcUS to balance computational efficiency and solution robustness.Additionally,a fully parallel column and constraint generation algorithm is developed to solve the model efficiently.Numerical simulations on a practical hybrid AC/DC microgrid system demonstrate that the proposed method reduces interconnection costs by up to 21.8%compared to conventional uncertainty sets while ensuring robust operation under all considered scenarios.These results highlight the computational efficiency,robustness,and practicality of the proposed approach,making it a promising solution for modern power systems.展开更多
This paper presents a novel active disturbance rejection control(ADRC)scheme based on a cascade connection of generalized proportional integral observers(GPIOs)with internal models designed to estimate both polynomial...This paper presents a novel active disturbance rejection control(ADRC)scheme based on a cascade connection of generalized proportional integral observers(GPIOs)with internal models designed to estimate both polynomial and resonant disturbances.In this estimator structure,referred to as Cascade GPIO(CGPIO),the total disturbance sensitivity is the product of the sensitivities at each cascade level.This approach improves system performance against both periodic and non-periodic disturbances and enhances robustness under frequency variations in harmonic components.Additionally,the decoupled nature of the estimator reduces the order of the GPIOs,thereby simplifying tuning and limiting observer gains.The proposed control scheme is supported by a frequency-domain analysis and is experimentally validated in the current control of a grid-connected converter subject to control gain uncertainties,harmonic distortion,frequency deviations,and measurement noise.Experimental results demonstrate that the CGPIO-based ADRC outperforms benchmark solutions,including proportional-integral(PI)and proportional-resonant(PR)controllers.展开更多
The growing interest in energy conservation has inspired companies to seek alternatives to highly polluting fuel electricity generation. This study designed an optimised solar wind power generation system to fulfil th...The growing interest in energy conservation has inspired companies to seek alternatives to highly polluting fuel electricity generation. This study designed an optimised solar wind power generation system to fulfil the energy requirement of a cold chain logistics centre. This study first conducted a thorough analysis of the clarity indicators and daily temperature positions of the cold chain logistics centre, determined the average daily electricity demand, and proposed an effective design scheme. The energy simulation software, RETScreen 8.0, was used to determine the scale of solar photovoltaic and wind power projects that meet the expected energy needs of the cold chain logistics centre. The results indicated that the estimated annual total energy demand was 833689.2 kWh. The annual power generation of 6 kW from solar photovoltaic projects and 150 kW from wind power projects was found to be enough to meet the expected electricity demand. Solar photovoltaic power generation and wind power generation account for 2.44% and 97.56%, respectively. The hybrid energy system achieved a 96.6% reduction in carbon emissions and provides a reasonable payback period of 6.1 years and an electricity generation of 904368.674 kWh per year. The feasibility of the project and the calculated period of investment return are very reasonable. Therefore, this hybrid renewable energy system provides reliable power by combining energy sources.展开更多
As the proportion of renewable energy power generation continues to increase,the number of grid-connected microgrids is gradually increasing,and geographically adjacent microgrids can be interconnected to form a Micro...As the proportion of renewable energy power generation continues to increase,the number of grid-connected microgrids is gradually increasing,and geographically adjacent microgrids can be interconnected to form a Micro-Grid Community(MGC).In order to reduce the operation and maintenance costs of a single micro grid and reduce the adverse effects caused by unnecessary energy interaction between the micro grid and the main grid while improving the overall economic benefits of the micro grid community,this paper proposes a bi-level energy management model with the optimization goal of maximizing the social welfare of the micro grid community and minimizing the total electricity cost of a single micro grid.The lower-level model optimizes the output of each equipment unit in the system and the exchange power between the system and the external grid with the goal of minimizing the operating cost of each microgrid.The upper-level model optimizes the goal ofmaximizing the socialwelfare of themicrogrid.Taking amicrogrid community with four microgrids as an example,the simulation analysis shows that the proposed optimization model is beneficial to reduce the operating cost of a single microgrid,improve the overall revenue of the microgrid community,and reduce the power interaction pressure on the main grid.展开更多
Recently, the smart grid has been considered as a next-generation power system to modernize the traditional grid to improve its security, connectivity, efficiency and sustainability.Unfortunately, the smart grid is su...Recently, the smart grid has been considered as a next-generation power system to modernize the traditional grid to improve its security, connectivity, efficiency and sustainability.Unfortunately, the smart grid is susceptible to malicious cyber attacks, which can create serious technical, economical, social and control problems in power network operations. In contrast to the traditional cyber attack minimization techniques, this paper proposes a recursive systematic convolutional(RSC) code and Kalman filter(KF) based method in the context of smart grids.Specifically, the proposed RSC code is used to add redundancy in the microgrid states, and the log maximum a-posterior is used to recover the state information, which is affected by random noises and cyber attacks. Once the estimated states are obtained by KF algorithm, a semidefinite programming based optimal feedback controller is proposed to regulate the system states, so that the power system can operate properly. Test results show that the proposed approach can accurately mitigate the cyber attacks and properly estimate and control the system states.展开更多
基金Supported by the Fundamental Research Funds for the Central Universities(2024ZYGXZR047)the National Natural Science Foundation of China(62373156)the Guangdong Basic and Applied Basic Research Foundation(2024A1515011736)。
文摘This article investigates the robust current tracking control problem of three-phase grid-connected inverters with LCL filter under external disturbance by a dynamic state feedback control method.First,this paper constructs an internal model to learn the information of the states and input of the grid-connected inverter under steady state.Second,by utilizing the internal model principle,the paper turns the tracking control problem into the robust stabilization control problem based on some appropriate coordinate transformations.Then,The paper designs a dynamics state feedback control law to deal with this robust stabilization problem,and thus the solution of the robust current tracking control problem of three-phase grid-connected inverters can be obtained.This control method can ensure the asymptotic stability of the closedloop system.Finally,the paper illustrates the effectiveness of the proposed control approach through several groups of simulations,and compares it with the feedforward control method to verify the robustness of the proposed control method to uncertain parameters.
基金supported by the Smart Grid-National Science and Technology Major Project(2025ZD0804500)the National Natural Science Foundation of China under Grant 52307232the Hunan Provincial Natural Science Foundation of China under Grant 2024JJ4055.
文摘The hybrid series-parallel microgrid attracts more attention by combining the advantages of both the series-stacked voltage and parallel-expanded capacity.Low-voltage distributed generations(DGs)are connected in series to form the intra-string,and then multiple strings are interconnected in parallel.For the existing control strategies,both intra-string and inter-string depend on the centralized or distributed control with high communication reliance.It has limited scalability and redundancy under abnormal conditions.Alternatively,in this study,an intra-string distributed and inter-string decentralized control framework is proposed.Within the string,a few DGs close to the AC bus are the leaders to get the string power information and the rest DGs are the followers to acquire the synchronization information through the droop-based distributed consistency.Specifically,the output of the entire string has the active power−angular frequency(ω-P)droop characteristic,and the decentralized control among strings can be autonomously guaranteed.Moreover,the secondary control is designed to realize multi-mode objectives,including on/off-grid mode switching,grid-connected power interactive management,and off-grid voltage quality regulation.As a result,the proposed method has the ability of plug-and-play capabilities,single-point failure redundancy,and seamless mode-switching.Experimental results are provided to verify the effectiveness of the proposed practical solution.
文摘The integration of renewable energy sources into modern power systems necessitates efficient and robust control strategies to address challenges such as power quality,stability,and dynamic environmental variations.This paper presents a novel sparrow search algorithm(SSA)-tuned proportional-integral(PI)controller for grid-connected photovoltaic(PV)systems,designed to optimize dynamic perfor-mance,energy extraction,and power quality.Key contributions include the development of a systematic SSA-based optimization frame-work for real-time PI parameter tuning,ensuring precise voltage and current regulation,improved maximum power point tracking(MPPT)efficiency,and minimized total harmonic distortion(THD).The proposed approach is evaluated against conventional PSO-based and P&O controllers through comprehensive simulations,demonstrating its superior performance across key metrics:a 39.47%faster response time compared to PSO,a 12.06%increase in peak active power relative to P&O,and a 52.38%reduction in THD,ensuring compliance with IEEE grid standards.Moreover,the SSA-tuned PI controller exhibits enhanced adaptability to dynamic irradiancefluc-tuations,rapid response time,and robust grid integration under varying conditions,making it highly suitable for real-time smart grid applications.This work establishes the SSA-tuned PI controller as a reliable and efficient solution for improving PV system performance in grid-connected scenarios,while also setting the foundation for future research into multi-objective optimization,experimental valida-tion,and hybrid renewable energy systems.
基金This work was supported in part by the China Scholarship Council under the Grant(201606290197).
文摘The advantages and promoting applications of the microgrids community(MGC)allows for a critical step being taken toward a smart grid.An energy management strategy(EMS)is essential to intelligently coordinate the operations of the MGC.This paper presents a multi-time-scale EMS consid-ering battery operational modes for grid-connected MGCs.The proposed strategy consists of two modules:day-ahead integrated optimization and realtime distributed compensation.The first module aims to minimize the operational cost of the MGC considering battery free-overcharging protecting.This problem is solved by the mixed integer linear programming(MILP)sim-ulating two charging/discharging modes:limited-current mode and constant-voltage mode.The second module is installed in local MGs to correct the optimizing deviations of the day-ahead static scheduling,which are caused by predicting errors of renewable energy and loads.The main contribution of this work is integrating the advantages of global optimization of the centralized method and the fast computing speed of the distributed method.Experimental results prove the proposed EMS is feasible and effective.The computing time at each updating step is reduced by 75%on average,which has the potential to be adopted in engineering.
基金supported by the University of Sharjah (No. 20020403142 and No. 21020403178)。
文摘This paper presents the development of improved synergetic current control for the injected current of an inverter in the grid-connected microgrid and the distributed generation system(DGS). This paper introduces new formulas of the macro-variable functions for integral synergetic control(SC)and integral fast terminal SC, which both have an integral term to guarantee zero steady-state error. The proposed integral SC and integral fast terminal SC achieve a seamless performance such as the fast convergence, minimal overshoot, zero steady-state error, and chattering-free operation. To demonstrate the meritorious performance of the proposed scheme for injected current control, it is compared with the performance of a proportional-integral(PI) controller and advanced exponential sliding mode control(SMC). Finally, the practicality of the proposed scheme is justified by experimental results obtained through rapid control prototyping(RCP) using the dSPACESCALEXIO platform.
文摘This paper presents a real-time power flow controller for VSIs （voltage source inverters） interfaced to low voltage microgrids. The proposed controller is modular, flexible, intelligent, inexpensive, portable, adaptive and designed to positively contribute in low voltage microgrids in which the lines R/X ratio is greater than the transmission lines. Therefore, the proposed control strategy is developed for operation in distribution lines. The controller strategy is different from the conventional grid-connected inverters which are designed based on transmission line characteristics. This controller, using a Texas Instrument general purpose DSP （digital signal processor）, is programmed and tuned using MATLAB/SIMULINK in order to enhance self-healing, reliability and stability of the grid. This general purpose controller makes proper decisions using its local measurements as the primary source of data. The controller has the capability of communicating with the adjacent controllers and sharing the information if/when needed. The power flow output of the inverter is tested for both islanded and grid-connected modes of operation. The inverter positively contributes to active and reactive power supply while operating in grid-connected mode. The proposed control method has been implemented on a Texas Instrument DSC （digital signal controller） chip and tested on a hardware test bench at the Alternative Energy Laboratory at WVU1T （West Virginia University Institute of Technology）. The system＇s experimental results veri~ the validity and efficiency of the proposed controller.
基金supported by a grant fromtheUniversity of Tabuk,SaudiArabia(GrantNo.UT-2024-CIT-0527)Additional funding was provided by the Saudi Arabian Ministry of Education through the Scientific Research Support Program.
文摘This paper presents a novel machine learning(ML)enhanced energy management framework for residential microgrids.It dynamically integrates solar photovoltaics(PV),wind turbines,lithium-ion battery energy storage systems(BESS),and bidirectional electric vehicle(EV)charging.The proposed architecture addresses the limitations of traditional rule-based controls by incorporating ConvLSTM for real-time forecasting,a Twin Delayed Deep Deterministic Policy Gradient(TD3)reinforcement learning agent for optimal BESS scheduling,and federated learning for EV charging prediction—ensuring both privacy and efficiency.Simulated in a high-fidelity MATLAB/Simulink environment,the system achieves 98.7%solar/wind forecast accuracy and 98.2% Maximum Power Point Tracking(MPPT)tracking efficiency,while reducing torque oscillations by 41% and peak demand by 22%.Compared to baseline methods,the solution improves voltage and frequency stability(maintaining 400V±2%,50Hz±0.015Hz)and achieves a 70% reduction in battery State of Charge(SOC)management error.The EV scheduler,informed by data from over 500 households,reduces charging costs by 31% with rapid failover to critical loads during outages.The architecture is validated using ISO 8528-8 transient tests,demonstrating 99.98% uptime.These results confirm the feasibility of transitioningmicrogrids fromreactive systems to adaptive,cognitive infrastructures capable of self-optimization under highly variable renewable generation and EV behaviors.
基金support from Nantes Universite through the project AAP II GENOME(Ges-tion des Energies Nouvelles et Optimisation Electrique)and LEAP-RE MiDiNa project,grant N°NR-23-LERE-0002-01.
文摘Most developing countries continue to face challenges in accessing sustainable energy.This study investigates a solar panel and battery-powered system for an urban off-grid microgrid in Nigeria,where demand-sideflexibility and strategic interactions between households and utilities can optimize system sizing.A nonlinear programming model is built using bilevel problem formulation that incorporates both the households’willingness to reduce their energy consumption and the utility’s agreement to provide price rebates.The results show that,for an energy community of 10 households with annual energy demand of 7.8 MWh,an oversized solar-storage system is required(12 kWp of photovoltaic solar panels and 26 kWh of battery storage).The calculated average cost of 0.31€/kWh is three times higher than the current tariff,making it unaffordable for most Nigerian households.To address this,the utility company could implement Demand Response programs with direct load control that delay the use of certain appliances,such as fans,irons and air conditioners.If these measures reduce total demand by 5%,both the required system size and overall costs could decrease significantly,by approximately one-third.This adjustment leads to a reduced tariffof 0.20€/kWh.When Demand Response is imple-mented through negotiation between the utility and households,the amount of load-shaving achieved is lower.This is because house-holds experience discomfort from curtailment and are generally less willing to provideflexibility.However,negotiation allows for greaterflexibility than direct control,due to dynamic interactions and more active consumer participation in the energy transition.Nonetheless,tariffs remain higher than current market prices.Off-grid contracts could become competitive iffinancial support is pro-vided,such as low-interest loans and capital grants covering up to 75%of the upfront cost.
文摘Three-phase grid-connected inverters(GCIs)are essential components in distributed generation systems,where the accuracy of current measurement circuits is fundamental for reliable closed-loop operation.Nevertheless,the presence of a DC offset in the measured current can disrupt the regulation of grid currents and significantly degrade system performance.In this work,a fault-tolerant control approach is introduced to counteract the impact of such offset faults through a dedicated current compensation mechanism.The proposed solution is built around two main stages:(i)detecting and isolating DC offset faults that may appear in one or multiple phases of the measured grid currents,and(ii)estimating the fault magnitude and reconstructing the corrected current signal.The offset magnitude is obtained analytically by examining the grid current projected onto the synchronous d-axis at the grid angular frequency,eliminating the need for any additional sensing hardware.Simulation and experimental investigations conducted under several fault scenarios confirm the robustness of the proposed strategy and highlight significant improvements in detection speed and diagnostic accuracy.
基金funded by Humanities and Social Sciences of Ministry of Education Planning Fund of China(21YJA790009)National Natural Science Foundation of China(72140001).
文摘The supply of electricity to remote regions is a significant challenge owing to the pivotal transition in the global energy landscape.To address this issue,an off-grid microgrid solution integrated with energy storage systems is proposed in this study.Off-grid microgrids are self-sufficient electrical networks that are capable of effectively resolving electricity access problems in remote areas by providing stable and reliable power to local residents.A comprehensive review of the design,control strategies,energy management,and optimization of off-grid microgrids based on domestic and international research is presented in this study.It also explores the critical role of energy stor-age systems in enhancing microgrid stability and economic efficiency.Additionally,the capacity configurations of energy storage systems within off-grid networks are analyzed.Energy storage systems not only mitigate the intermittency and volatility of renewable energy gen-eration but also supply power support during peak demand periods,thereby improving grid stability and reliability.By comparing different energy storage technologies,such as lithium-ion batteries,pumped hydro storage,and compressed air energy storage,the optimal energy storage capacity configurations tailored to various application scenarios are proposed in this study.Finally,using a typical micro-grid as a case study,an empirical analysis of off-grid microgrids and energy storage integration has been conducted.The optimal con-figuration of energy storage systems is determined,and the impact of wind and solar power integration under various scenarios on grid balance is explored.It has been found that a rational configuration of energy storage systems can significantly enhance the utilization rate of renewable energy,reduce system operating costs,and strengthen grid resilience under extreme conditions.This study provides essential theoretical support and practical guidance for the design and implementation of off-grid microgrids in remote areas.
基金funded through Deanship of Scientific Research at Northern Border University,Arar,Saudi Arabia—project number“NBU-FFR-2025-3623-06”.
文摘Around the world,there has been a notable shift toward the use of renewable energy technology due to the growing demand for energy and the ongoing depletion of conventional resources,such as fossil fuels.Following this worldwide trend,Brunei’s government has initiated several strategic programs aimed at encouraging the establishment of energy from renewable sources in the nation’s energy mix.These initiatives are designed not only to support environmental sustainability but also to make energy from renewable sources increasingly competitive in comparison to more conventional energy sources like gas and oil,which have historically dominated Brunei’s energy market.The optimization of a hybrid energy system that combines diesel generators,solar photovoltaic(PV)panels,and the national power grid is the focus of this study.The objective is to identify the most cost-effective and environmentally sustainable configuration that can reliably meet local energy demands.During optimization,several configuration was tried and tested,including only grid,PV and Grid and PV-generator.HOMER(Hybrid Optimization of Multiple Energy Resources)software,a popular simulation tool that makes it possible to simulate and analyze hybrid energy systems,is utilized in the optimization process.Inside the HOMER Pro optimization,various system configuration is taken into account for the optimization.While simulating,it takes into account different combinations of components such as solar panels,wind turbines and batteries.Later on,it is being ranked by different factors such as net present cost(NPC),Cost of Energy(COE),etc.A comprehensive techno-economic research is carried out to evaluate various system configurations,considering key performance indicators such as total energy generation cost,operational expenditure,and greenhouse gas emissions.The results provide valuable insights into how renewable-based hybrid systems can reduce environmental impact while maintaining economic viability,supporting Brunei’s broader goals of energy diversification and sustainability.The study also emphasizes how such hybrid systems could be scaled for off-grid and rural populations in Brunei,where a dependable electricity supply is still a problem.Furthermore,sensitivity analyses were performed to evaluate the effects of variations in solar irradiation,load demand,and fuel prices on the overall system performance.Policymakers and energy planners can use these insights to help them make data-driven decisions about future investments in infrastructure for renewable energy.
基金supported in part by the National Natural Science Foundation of China(20221017-10,62573258,62188101)the National Natural Science Foundation of Shandong Province(ZR2024 JQ018,ZR2022MF227).
文摘The dynamic average consensus(DAC)algorithm is to enable a group of networked agents to track the average of their time-varying reference signals.For most existing DAC algorithms,a necessary assumption is that the upper bounds of the reference signals and their derivatives are known in advance,thereby posing significant challenges in practical scenarios.Introducing adaptive gains in DAC algorithms provides a remedy by relaxing this assumption.However,the current adaptive gains used in this type of DAC algorithms are non-decreasing and may increase to infinity if persist disturbance exists.In order to overcome this defect,this paper presents a novel DAC algorithm with modified adaptive gains.This approach obviates the necessity for prior knowledge concerning the upper bounds of the reference signals and their derivatives.Moreover,the adaptive gains are able to remain bounded even in the presence of external disturbances.Furthermore,the proposed adaptive DAC algorithm is employed to address the distributed secondary control problem of DC microgrids.Comparative case studies are provided to verify the superiority of the proposed DAC algorithm.
基金funded in part by Grant No.RG-15-135-43 from the Deanship of Scientific Research(DSR)at King Abdulaziz University in Saudi Arabia.
文摘The proliferation of distributed and renewable energy resources introduces additional operational challenges to power distribution systems.Transactive energy management,which allows networked neighborhood communities and houses to trade energy,is expected to be developed as an effective method for accommodating additional uncertainties and security mandates pertaining to distributed energy resources.This paper proposes and analyzes a two-layer transactive energy market in which houses in networked neighborhood community microgrids will trade energy in respective market layers.This paper studies the blockchain applications to satisfy socioeconomic and technological concerns of secure transactive energy management in a two-level power distribution system.The numerical results for practical networked microgrids located at IllinoisTech−Bronzeville in Chicago illustrate the validity of the proposed blockchain-based transactive energy management for devising a distributed,scalable,efficient,and cybersecured power grid operation.The conclusion of the paper summarizes the prospects for blockchain applications to transactive energy management in power distribution systems.
基金supported by Hainan Provincial Natural Science Foundation of China(No.524RC532)Research Startup Funding from Hainan Institute of Zhejiang University(No.0210-6602-A12202)Project of Sanya Yazhou Bay Science and Technology City(No.SKJC-2022-PTDX-009/010/011).
文摘Given the rapid development of advanced information systems,microgrids(MGs)suffer from more potential attacks that affect their operational performance.Conventional distributed secondary control with a small,fixed sampling time period inevitably causes the wasteful use of communication resources.This paper proposes a self-triggered secondary control scheme under perturbations from false data injection(FDI)attacks.We designed a linear clock for each DG to trigger its controller at aperiodic and intermittent instants.Sub-sequently,a hash-based defense mechanism(HDM)is designed for detecting and eliminating malicious data infiltrated in the MGs.With the aid of HDM,a self-triggered control scheme achieves the secondary control objectives even in the presence of FDI attacks.Rigorous theoretical analyses and simulation results indicate that the introduced secondary control scheme significantly reduces communication costs and enhances the resilience of MGs under FDI attacks.
文摘Low-voltage direct current(DC)microgrids have recently emerged as a promising and viable alternative to traditional alternating cur-rent(AC)microgrids,offering numerous advantages.Consequently,researchers are exploring the potential of DC microgrids across var-ious configurations.However,despite the sustainability and accuracy offered by DC microgrids,they pose various challenges when integrated into modern power distribution systems.Among these challenges,fault diagnosis holds significant importance.Rapid fault detection in DC microgrids is essential to maintain stability and ensure an uninterrupted power supply to critical loads.A primary chal-lenge is the lack of standards and guidelines for the protection and safety of DC microgrids,including fault detection,location,and clear-ing procedures for both grid-connected and islanded modes.In response,this study presents a brief overview of various approaches for protecting DC microgrids.
基金supported by the National Natural Science Foundation of China(72271213)the Shenzhen Science and Technology Program(JCYJ20220530143800001 and RCYX20221008092927070)+1 种基金the Guangdong Basic and Applied Basic Research Foundation(2024A1515240024)the National Key Research and Development Program of China(2022YFB2403500).
文摘Interconnection planning involving bi-directional converters(BdCs)is crucial for enhancing the reliability and robustness of hybrid alternating current(AC)/direct current(DC)microgrid clusters with high penetrations of renewable energy resources(RESs).However,challenges such as the non-convex nature of BdC efficiency and renewable energy uncertainty complicate the planning process.To address these issues,this paper proposes a tri-level BdC-based planning framework that incorporates dynamic BdC efficiency and a data-correlated uncertainty set(DcUS)derived from historical data patterns.The proposed framework employs a least-squares approximation to linearize BdC efficiency and constructs the DcUS to balance computational efficiency and solution robustness.Additionally,a fully parallel column and constraint generation algorithm is developed to solve the model efficiently.Numerical simulations on a practical hybrid AC/DC microgrid system demonstrate that the proposed method reduces interconnection costs by up to 21.8%compared to conventional uncertainty sets while ensuring robust operation under all considered scenarios.These results highlight the computational efficiency,robustness,and practicality of the proposed approach,making it a promising solution for modern power systems.
文摘This paper presents a novel active disturbance rejection control(ADRC)scheme based on a cascade connection of generalized proportional integral observers(GPIOs)with internal models designed to estimate both polynomial and resonant disturbances.In this estimator structure,referred to as Cascade GPIO(CGPIO),the total disturbance sensitivity is the product of the sensitivities at each cascade level.This approach improves system performance against both periodic and non-periodic disturbances and enhances robustness under frequency variations in harmonic components.Additionally,the decoupled nature of the estimator reduces the order of the GPIOs,thereby simplifying tuning and limiting observer gains.The proposed control scheme is supported by a frequency-domain analysis and is experimentally validated in the current control of a grid-connected converter subject to control gain uncertainties,harmonic distortion,frequency deviations,and measurement noise.Experimental results demonstrate that the CGPIO-based ADRC outperforms benchmark solutions,including proportional-integral(PI)and proportional-resonant(PR)controllers.
文摘The growing interest in energy conservation has inspired companies to seek alternatives to highly polluting fuel electricity generation. This study designed an optimised solar wind power generation system to fulfil the energy requirement of a cold chain logistics centre. This study first conducted a thorough analysis of the clarity indicators and daily temperature positions of the cold chain logistics centre, determined the average daily electricity demand, and proposed an effective design scheme. The energy simulation software, RETScreen 8.0, was used to determine the scale of solar photovoltaic and wind power projects that meet the expected energy needs of the cold chain logistics centre. The results indicated that the estimated annual total energy demand was 833689.2 kWh. The annual power generation of 6 kW from solar photovoltaic projects and 150 kW from wind power projects was found to be enough to meet the expected electricity demand. Solar photovoltaic power generation and wind power generation account for 2.44% and 97.56%, respectively. The hybrid energy system achieved a 96.6% reduction in carbon emissions and provides a reasonable payback period of 6.1 years and an electricity generation of 904368.674 kWh per year. The feasibility of the project and the calculated period of investment return are very reasonable. Therefore, this hybrid renewable energy system provides reliable power by combining energy sources.
基金This paper is supported by Science and Technology Project of State Grid(The construction of provincial energy big data ecosystem and the application practice research of data value-added service for the park,5400-202012224A-0-0-00).
文摘As the proportion of renewable energy power generation continues to increase,the number of grid-connected microgrids is gradually increasing,and geographically adjacent microgrids can be interconnected to form a Micro-Grid Community(MGC).In order to reduce the operation and maintenance costs of a single micro grid and reduce the adverse effects caused by unnecessary energy interaction between the micro grid and the main grid while improving the overall economic benefits of the micro grid community,this paper proposes a bi-level energy management model with the optimization goal of maximizing the social welfare of the micro grid community and minimizing the total electricity cost of a single micro grid.The lower-level model optimizes the output of each equipment unit in the system and the exchange power between the system and the external grid with the goal of minimizing the operating cost of each microgrid.The upper-level model optimizes the goal ofmaximizing the socialwelfare of themicrogrid.Taking amicrogrid community with four microgrids as an example,the simulation analysis shows that the proposed optimization model is beneficial to reduce the operating cost of a single microgrid,improve the overall revenue of the microgrid community,and reduce the power interaction pressure on the main grid.
文摘Recently, the smart grid has been considered as a next-generation power system to modernize the traditional grid to improve its security, connectivity, efficiency and sustainability.Unfortunately, the smart grid is susceptible to malicious cyber attacks, which can create serious technical, economical, social and control problems in power network operations. In contrast to the traditional cyber attack minimization techniques, this paper proposes a recursive systematic convolutional(RSC) code and Kalman filter(KF) based method in the context of smart grids.Specifically, the proposed RSC code is used to add redundancy in the microgrid states, and the log maximum a-posterior is used to recover the state information, which is affected by random noises and cyber attacks. Once the estimated states are obtained by KF algorithm, a semidefinite programming based optimal feedback controller is proposed to regulate the system states, so that the power system can operate properly. Test results show that the proposed approach can accurately mitigate the cyber attacks and properly estimate and control the system states.
