Hybrid Petri nets(HPNs) are widely used to describe and analyze various industrial hybrid systems that have both discrete-event and continuous discrete-time behaviors. Recently,many researchers attempt to utilize them...Hybrid Petri nets(HPNs) are widely used to describe and analyze various industrial hybrid systems that have both discrete-event and continuous discrete-time behaviors. Recently,many researchers attempt to utilize them to characterize power and energy systems. This work proposes to adopt an HPN to model and analyze a microgrid that consists of green energy sources. A reachability graph for such a model is generated and used to analyze the system properties.展开更多
Microgrids are a type of restricted power distribution systems in which electricity is generated,transmitted,and distributed within a small geographic region.They are used to ensure that renewable energy sources are u...Microgrids are a type of restricted power distribution systems in which electricity is generated,transmitted,and distributed within a small geographic region.They are used to ensure that renewable energy sources are used to their full potential.Microgrids provide further benefits,such as lowering transmission losses and the expenses associated with them.This research compares and contrasts the aims of economic dispatch,emission dispatch,fractional programing based combined economic emission dispatch,and environmental restricted economic dispatch(ECED).A low-voltage microgrid system is investigated for three different scenarios.As a study optimization tool,an innovative,resilient,and strong hybrid swarm-intelligence optimization algorithm is utilised,which is based on combining the properties of the traditional grey-wolf optimiser,sine-cosine algorithm,and crow search algorithm.The employment of a time-of-use energy mar-ket pricing approach instead of a fixed pricing plan resulted in a 15%decrease in gen-eration costs throughout the course of the research.When ECED was assessed with a 15%-20%demand side management based restructured load demand model for the microgrid system,the generation costs were reduced even further.展开更多
This paper describes the characteristics and optimal methods for the planning of stand-alone microgrid system, in order to improve the power supply reliability, increase the coefficient of utilization of renewable ene...This paper describes the characteristics and optimal methods for the planning of stand-alone microgrid system, in order to improve the power supply reliability, increase the coefficient of utilization of renewable energy and reduce the cost of investment and operation. Next, the problems in the optimal planning for a stand-alone microgrid system are summarized, including the unique operational control targets, the flexible combination approaches and the operation strategies of distributed generation energy supply system, and the special requirements of the reliability of power supply quality factor from the different users. And then, centering on the operational control and the advanced energy management strategy, the optimal mathematical models and the solving methods, the reliability assessment approaches and the improvement measures of a stand-alone microgrid system, an overview of the general situation of the recent research at home and abroad and the limitations of the study are summarized. Finally, several problems, existing in the optimal planning of stand-alone microgrid system, to be urgently solved, are put forward.展开更多
Present-day power conversion and conditioning systems focus on transferring energy from a single type of power source into a single type of load or energy storage system (ESS). While these systems can be optimized wit...Present-day power conversion and conditioning systems focus on transferring energy from a single type of power source into a single type of load or energy storage system (ESS). While these systems can be optimized within their specific topology (e.g. MPPT for solar applications and BMS for batteries), the topologies are not easily adapted to accept a wide range of power flow operating conditions. With a hybrid approach to energy storage and power flow, a system can be designed to operate at its most advantageous point, given the operating conditions. Based on the load demand, the system can select the optimal power source and ESS. This paper will investigate the feasibility of combining two types of power sources (main utility grid and photovoltaics (PV)) along with two types of ESS (ultra-capacitors and batteries). The simulation results will show the impact of a hybrid ESS on a grid-tied residential microgrid system performance under various operating scenarios.展开更多
The Phase Locked Loop controller parameters are the key-point that affects the dynamic performance of the autonomous microgrid. They have to be optimally tuned to guarantee enhanced overall system stability. In this p...The Phase Locked Loop controller parameters are the key-point that affects the dynamic performance of the autonomous microgrid. They have to be optimally tuned to guarantee enhanced overall system stability. In this paper, two-microgrid plant with their associate PWM inverter connected to the ac main grid and the load is used as an example to demonstrate the capabilities of the proposed system. The Phase Locked Loop controller is designed and tuned using the Simulating Annealing algorithm. This algorithm is used to select the Phase Locked Loop PI controller gains with optimal percentage overshoot, rise time and settling time. The controller is tested during the transition between grid-connected and autonomous operation and in reverse order. The controller is compared with Ziegler and Nichols P and PI controllers. It shows the effectiveness and the extraordinary control response of the proposed control technique with respect to percentage overshoot, rise time and settling time control parameters compared to the conventional one.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
Due to the inherent nature of high fluctuation and randomness,it is hard for renewable energy sources to meet full-time power quality requirements,and are thus difficult to be directly consumed by loads.In this study ...Due to the inherent nature of high fluctuation and randomness,it is hard for renewable energy sources to meet full-time power quality requirements,and are thus difficult to be directly consumed by loads.In this study we propose efficient flexible load microgrid system(EFLM),which breaks through point of common coupling(PCC)connection widely adapted by traditional microgrid;with slice-based multi-source energy distribution methodology,EFLM distribute power through flexible source-load connection,to loads with classified types of consumption,achieving the goal of directly allocating otherwise wasted renewable energy,to suitable loads through principles of loads classification,dynamic source-load coupling,time-based power slicing,flow-free power control,and transparent aggregation of multi-source energy.From maximising renewable energy utilisation during its entire output period,EFLM enhances direct energy utilisation,meanwhile reduces impact due to local fluctuation to the main grid.This research also provides a new pathway to microgrids accommodating high proportion of renewable energy,grid-forming and off-grid microgrid configurations,high-capacity energy storage charge-discharge management,and medium-to-low-voltage flexible grid construction.展开更多
The advent of microgrids in modern energy systems heralds a promising era of resilience,sustainability,and efficiency.Within the realm of grid-tied microgrids,the selection of an optimal optimization algorithm is crit...The advent of microgrids in modern energy systems heralds a promising era of resilience,sustainability,and efficiency.Within the realm of grid-tied microgrids,the selection of an optimal optimization algorithm is critical for effective energy management,particularly in economic dispatching.This study compares the performance of Particle Swarm Optimization(PSO)and Genetic Algorithms(GA)in microgrid energy management systems,implemented using MATLAB tools.Through a comprehensive review of the literature and sim-ulations conducted in MATLAB,the study analyzes performance metrics,convergence speed,and the overall efficacy of GA and PSO,with a focus on economic dispatching tasks.Notably,a significant distinction emerges between the cost curves generated by the two algo-rithms for microgrid operation,with the PSO algorithm consistently resulting in lower costs due to its effective economic dispatching capabilities.Specifically,the utilization of the PSO approach could potentially lead to substantial savings on the power bill,amounting to approximately$15.30 in this evaluation.Thefindings provide insights into the strengths and limitations of each algorithm within the complex dynamics of grid-tied microgrids,thereby assisting stakeholders and researchers in arriving at informed decisions.This study contributes to the discourse on sustainable energy management by offering actionable guidance for the advancement of grid-tied micro-grid technologies through MATLAB-implemented optimization algorithms.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 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
Considering the uncertainty of wind power generation(WPG)and the specific operation behaviors of trading microgrids,this paper presents a blockchain-enabled robust-game electricity transaction model in a multi-microgr...Considering the uncertainty of wind power generation(WPG)and the specific operation behaviors of trading microgrids,this paper presents a blockchain-enabled robust-game electricity transaction model in a multi-microgrid system(MMS)to obtain optimal bidding-dispatching strategies,and achieve a transparent and decentralized electricity transaction.Combining blockchain technology and a non-cooperative game model,the established MMS electricity transaction architecture provides a complete information game environment for all game microgrids and facilitates the transparent,efficient,orderly,spontaneous management of MMS electricity transactions without the intervention of a third trusted party.Based on the distributed transaction architecture,an MMS robust-game model is presented to achieve the optimal day-ahead bidding-dispatching(DA-BD)strategies,in which the individual microgrid two-stage adjustable robust-game bidding-dispatching(ARG-BD)model characterizes the WPG uncertainty by employing uncertain interval and adjustable robust parameters.The binary expansion method,duality theory,big M method,and column-and-constrain generation algorithm(C&CG)are employed to solve the individual microgrid two-stage ARG-BD model.An alternating robust-game procedure integrating the C&CG algorithm and non-cooperative game model is developed to solve the MMS robust-game model.Case studies demonstrate the transparent and decentralized transaction,economic mutual benefits,and solution robustness of the presented method.展开更多
This paper presents a holistic pricing and distributed scheduling framework for multi-microgrid system(MMGS)that considers the supply‒demand relationships of the coupled electricity‒carbon market to promote collaborat...This paper presents a holistic pricing and distributed scheduling framework for multi-microgrid system(MMGS)that considers the supply‒demand relationships of the coupled electricity‒carbon market to promote collaborative market trading within the MMGS for economic and environmental benefit improvement.Initially,an operation model of each microgrid is developed by synthetically considering electricity-carbon operational constraints related to generation units and energy storage units.Then,a collaborative optimization strategy of the MMGS is established according to the Nash bargaining game(NBG)model with the objective of maximizing overall operational revenue.To determine the trading schedule,an accelerated prediction-correction-based alternating direction method of multipliers(PCB-ADMM)algorithm is employed to derive the optimal scheduling strategy of MMGS in a distributed manner,ensuring the privacy preservation of individual microgrids.For electricity-carbon pricing,a supply-demand ratio(SDR)based pricing strategy is proposed to dynamically update electricity and carbon allowance prices,which fundamentally guides and incentivizes each microgrid to trade within the MMGS preferentially rather than with an upstream distribution network.Finally,a study case verifies the effectiveness of the proposed framework in enhancing the operation economy and environmental friendliness of the entire MMGS.展开更多
The main objective of this paper is to select the optimal model of a hybrid renewable-energy microgrid(MG)system for a village in India.The MG comprises solar photovoltaic(PV)modules,a wind turbine generator,a biomass...The main objective of this paper is to select the optimal model of a hybrid renewable-energy microgrid(MG)system for a village in India.The MG comprises solar photovoltaic(PV)modules,a wind turbine generator,a biomass generator,a battery bank,a diesel generator and an electric vehicle.The optimal model selection is based on technical,economic,environmental,social and reliability parameters.A novel spoonbill swarm optimization algorithm is proposed to select the best hybrid MG system.The optimization results are compared with particle swarm optimization,the genetic algorithm and the grasshopper optimization algorithm.The number or size of components of the optimized MG system is 215 PV modules,92 kW of wind turbine generation,25 kW of biomass generation,267 batteries,22 kW of electric vehicles and 30 kW of diesel generation.The optimized system was selected based on technical factors such as renewable dispersion(93.5%),the duty factor(5.85)and excess energy(15975 kWh/year)as well as eco-nomic considerations including the net present cost(Rs.34686622)and the cost of energy(9.3 Rs./kWh).Furthermore,environ-mental factors such as carbon emissions(396348 kg/year)and atmospheric particulate matter(22.686 kg/year);social factors such as the human progress index(0.68411),the employment generation factor(0.0389)and local employment generation(15.64643);and reliability parameters including loss of power supply probability(0.01%)and availability index(99.99%)were considered during the selection process.The spoonbill swarm optimization algorithm has reduced the convergence time by 1.2 times and decreased the number of iterations by 0.83 times compared with other algorithms.The performance of the MG system is validated in the MATLAB®environment.The results show that the MG system is the optimal system considering technical,economic,environmental,social and reliability parameters.Additionally,the spoonbill swarm optimization algorithm is found to be more efficient than the other algo-rithms in terms of iteration time and convergence time.展开更多
To meet the greenhouse gas reduction targets and address the uncertainty introduced by the surging penetration of stochastic renewable energy sources,energy storage systems are being deployed in microgrids.Relying sol...To meet the greenhouse gas reduction targets and address the uncertainty introduced by the surging penetration of stochastic renewable energy sources,energy storage systems are being deployed in microgrids.Relying solely on short-term uncertainty forecasts can result in substantial costs when making dispatch decisions for a storage system over an entire day.To mitigate this challenge,an adaptive robust optimization approach tailored for a hybrid hydrogen battery energy storage system(HBESS)operating within a microgrid is proposed,with a focus on efficient state-of-charge(SoC)planning to minimize microgrid expenses.The SoC ranges of the battery energy storage(BES)are determined in the day-ahead stage.Concurrently,the power generated by fuel cells and consumed by electrolysis device are optimized.This is followed by the intraday stage,where BES dispatch decisions are made within a predetermined SoC range to accommodate the uncertainties realized.To address this uncertainty and solve the adaptive optimization problem with integer recourse variables in the intraday stage,we proposed an outer-inner column-and-constraint generation algorithm(outer-inner-CCG).Numerical analyses underscored the high effectiveness and efficiency of the proposed adaptive robust operation model in making decisions for HBESS dispatch.展开更多
Microgrids are networked control systems with multiple distributed generators(DGs).Microgrids are associated with many problems,such as communication delays,high sampling rates,and frequent controller updates,which ma...Microgrids are networked control systems with multiple distributed generators(DGs).Microgrids are associated with many problems,such as communication delays,high sampling rates,and frequent controller updates,which make it challenging to realize coordination control among the DGs.Therefore,finite-time consensus algorithms and event-triggered control methods are combined to propose a distributed coordination control method for microgrid systems.The DG in the microgrid system serves as an agent node in the control network,and a distributed secondary controller is designed using finite-time consensus algorithm,such that the frequency and voltage restoration control has a faster convergence time and better anti-interference performance.The event-triggered function was designed based on the state information of the agents.The controller exchanges the state information at the trigger instants.System stability is analyzed using the Lyapunov stability theory,and it is verified that the controller cannot exhibit the Zeno phenomenon in the event-triggered process.A simulation platform was developed in Matlab/Simulink to verify that the proposed control method can effectively reduce the frequency of controller updates during communication delays and the burden on the communication network.展开更多
This paper proposes a feedback-optimization-based control method for linear time-invariant systems,which is aimed to exponentially stabilize the system and,meanwhile,drive the system output to an approximate solution ...This paper proposes a feedback-optimization-based control method for linear time-invariant systems,which is aimed to exponentially stabilize the system and,meanwhile,drive the system output to an approximate solution of an optimization problem with convex set constraints and affine inequality constraints.To ensure the exponential stability of the closed-loop system,the original optimization problem is first reformulated into a counterpart that has only convex set constraints.It is shown that the optimal solution of the new optimization problem is an approximate optimal solution of the original problem.Then,based on this new optimization problem,the projected primal–dual gradient dynamics algorithm is used to design the controller.By using the singular perturbation method,sufficient conditions are provided to ensure the exponential stability of the closed-loop system.The proposed method is also applied to microgrid control.展开更多
With the direct rise of the social demand for renewable energy,as a new type of energy supply model in the new era,the operation control and optimization of microgrid play an important role in solving the problem of r...With the direct rise of the social demand for renewable energy,as a new type of energy supply model in the new era,the operation control and optimization of microgrid play an important role in solving the problem of resource sharing.Microgrid can realize the flexibility of distributed power supply and the application of high efficiency,solving the problem of a large number and variety of forms of the power grid.Based on this,this paper will discuss the operation control strategy of microgrid based on a new energy grid connection,and provide constructive ideas for high-quality operation of microgrid.展开更多
This paper deeply introduces a brand-new research method for the synchronous characteristics of DC microgrid bus voltage and an improved synchronous control strategy.This method mainly targets the problem of bus volta...This paper deeply introduces a brand-new research method for the synchronous characteristics of DC microgrid bus voltage and an improved synchronous control strategy.This method mainly targets the problem of bus voltage oscillation caused by the bifurcation behavior of DC microgrid converters.Firstly,the article elaborately establishes a mathematical model of a single distributed power source with hierarchical control.On this basis,a smallworld network model that can better adapt to the topology structure of DC microgrids is further constructed.Then,a voltage synchronization analysis method based on the main stability function is proposed,and the synchronous characteristics of DC bus voltage are deeply studied by analyzing the size of the minimum non-zero eigenvalue.In view of the situation that the line coupling strength between distributed power sources is insufficient to achieve bus voltage synchronization,this paper innovatively proposes a new improved adaptive controller to effectively control voltage synchronization.And the convergence of the designed controller is strictly proved by using Lyapunov’s stability theorem.Finally,the effectiveness and feasibility of the designed controller in this paper are fully verified through detailed simulation experiments.After comparative analysis with the traditional adaptive controller,it is found that the newly designed controller can make the bus voltages of each distributed power source achieve synchronization more quickly,and is significantly superior to the traditional adaptive controller in terms of anti-interference performance.展开更多
With the rapid development of renewable energy,the Microgrid Coalition(MGC)has become an important approach to improving energy utilization efficiency and economic performance.To address the operational optimization p...With the rapid development of renewable energy,the Microgrid Coalition(MGC)has become an important approach to improving energy utilization efficiency and economic performance.To address the operational optimization problem inmulti-microgrid cooperation,a cooperative game strategy based on the Nash bargainingmodel is proposed,aiming to enable collaboration among microgrids to maximize overall benefits while considering energy trading and cost optimization.First,each microgrid is regarded as a game participant,and a multi-microgrid cooperative game model based on Nash bargaining theory is constructed,targeting the minimization of total operational cost under constraints such as power balance and energy storage limits.Second,the Nash bargaining solution is introduced as the benefit allocation scheme to ensure individual rationality and coalition stability.Finally,theAlternating Direction Method of Multipliers(ADMM)is employed to decompose the centralized optimization problem into distributed subproblems for iterative solution,thereby reducing communication burden and protecting privacy.Case studies reveal that the operational costs of the threemicrogrids are reduced by 26.28%,19.00%,and 17.19%,respectively,and the overall renewable energy consumption rate is improved by approximately 66.11%.展开更多
基金supported by the Deanship of Scientific Research(DSR)King Abdulaziz University,Jeddah(23-135-35-HiCi)
文摘Hybrid Petri nets(HPNs) are widely used to describe and analyze various industrial hybrid systems that have both discrete-event and continuous discrete-time behaviors. Recently,many researchers attempt to utilize them to characterize power and energy systems. This work proposes to adopt an HPN to model and analyze a microgrid that consists of green energy sources. A reachability graph for such a model is generated and used to analyze the system properties.
文摘Microgrids are a type of restricted power distribution systems in which electricity is generated,transmitted,and distributed within a small geographic region.They are used to ensure that renewable energy sources are used to their full potential.Microgrids provide further benefits,such as lowering transmission losses and the expenses associated with them.This research compares and contrasts the aims of economic dispatch,emission dispatch,fractional programing based combined economic emission dispatch,and environmental restricted economic dispatch(ECED).A low-voltage microgrid system is investigated for three different scenarios.As a study optimization tool,an innovative,resilient,and strong hybrid swarm-intelligence optimization algorithm is utilised,which is based on combining the properties of the traditional grey-wolf optimiser,sine-cosine algorithm,and crow search algorithm.The employment of a time-of-use energy mar-ket pricing approach instead of a fixed pricing plan resulted in a 15%decrease in gen-eration costs throughout the course of the research.When ECED was assessed with a 15%-20%demand side management based restructured load demand model for the microgrid system,the generation costs were reduced even further.
基金supported by National Natural Science Foundation of China(61100159,61233007,61503371)National High Technology Research and Development Program of China(863 Program)(2011AA040103)+2 种基金Foundation of Chinese Academy of Sciences(KGCX2-EW-104)the Strategic Priority Research Program of the Chinese Academy of Sciences(XDA06021100)the Cross-disciplinary Collaborative Teams Program for Science,Technology,and Innovation of Chinese Academy of Sciences-Network and System Technologies for Security Monitoring and Information Interaction in Smart Grid,Energy Management System for Micro-smart Grid
文摘This paper describes the characteristics and optimal methods for the planning of stand-alone microgrid system, in order to improve the power supply reliability, increase the coefficient of utilization of renewable energy and reduce the cost of investment and operation. Next, the problems in the optimal planning for a stand-alone microgrid system are summarized, including the unique operational control targets, the flexible combination approaches and the operation strategies of distributed generation energy supply system, and the special requirements of the reliability of power supply quality factor from the different users. And then, centering on the operational control and the advanced energy management strategy, the optimal mathematical models and the solving methods, the reliability assessment approaches and the improvement measures of a stand-alone microgrid system, an overview of the general situation of the recent research at home and abroad and the limitations of the study are summarized. Finally, several problems, existing in the optimal planning of stand-alone microgrid system, to be urgently solved, are put forward.
文摘Present-day power conversion and conditioning systems focus on transferring energy from a single type of power source into a single type of load or energy storage system (ESS). While these systems can be optimized within their specific topology (e.g. MPPT for solar applications and BMS for batteries), the topologies are not easily adapted to accept a wide range of power flow operating conditions. With a hybrid approach to energy storage and power flow, a system can be designed to operate at its most advantageous point, given the operating conditions. Based on the load demand, the system can select the optimal power source and ESS. This paper will investigate the feasibility of combining two types of power sources (main utility grid and photovoltaics (PV)) along with two types of ESS (ultra-capacitors and batteries). The simulation results will show the impact of a hybrid ESS on a grid-tied residential microgrid system performance under various operating scenarios.
文摘The Phase Locked Loop controller parameters are the key-point that affects the dynamic performance of the autonomous microgrid. They have to be optimally tuned to guarantee enhanced overall system stability. In this paper, two-microgrid plant with their associate PWM inverter connected to the ac main grid and the load is used as an example to demonstrate the capabilities of the proposed system. The Phase Locked Loop controller is designed and tuned using the Simulating Annealing algorithm. This algorithm is used to select the Phase Locked Loop PI controller gains with optimal percentage overshoot, rise time and settling time. The controller is tested during the transition between grid-connected and autonomous operation and in reverse order. The controller is compared with Ziegler and Nichols P and PI controllers. It shows the effectiveness and the extraordinary control response of the proposed control technique with respect to percentage overshoot, rise time and settling time control parameters compared to the conventional one.
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.
文摘Due to the inherent nature of high fluctuation and randomness,it is hard for renewable energy sources to meet full-time power quality requirements,and are thus difficult to be directly consumed by loads.In this study we propose efficient flexible load microgrid system(EFLM),which breaks through point of common coupling(PCC)connection widely adapted by traditional microgrid;with slice-based multi-source energy distribution methodology,EFLM distribute power through flexible source-load connection,to loads with classified types of consumption,achieving the goal of directly allocating otherwise wasted renewable energy,to suitable loads through principles of loads classification,dynamic source-load coupling,time-based power slicing,flow-free power control,and transparent aggregation of multi-source energy.From maximising renewable energy utilisation during its entire output period,EFLM enhances direct energy utilisation,meanwhile reduces impact due to local fluctuation to the main grid.This research also provides a new pathway to microgrids accommodating high proportion of renewable energy,grid-forming and off-grid microgrid configurations,high-capacity energy storage charge-discharge management,and medium-to-low-voltage flexible grid construction.
文摘The advent of microgrids in modern energy systems heralds a promising era of resilience,sustainability,and efficiency.Within the realm of grid-tied microgrids,the selection of an optimal optimization algorithm is critical for effective energy management,particularly in economic dispatching.This study compares the performance of Particle Swarm Optimization(PSO)and Genetic Algorithms(GA)in microgrid energy management systems,implemented using MATLAB tools.Through a comprehensive review of the literature and sim-ulations conducted in MATLAB,the study analyzes performance metrics,convergence speed,and the overall efficacy of GA and PSO,with a focus on economic dispatching tasks.Notably,a significant distinction emerges between the cost curves generated by the two algo-rithms for microgrid operation,with the PSO algorithm consistently resulting in lower costs due to its effective economic dispatching capabilities.Specifically,the utilization of the PSO approach could potentially lead to substantial savings on the power bill,amounting to approximately$15.30 in this evaluation.Thefindings provide insights into the strengths and limitations of each algorithm within the complex dynamics of grid-tied microgrids,thereby assisting stakeholders and researchers in arriving at informed decisions.This study contributes to the discourse on sustainable energy management by offering actionable guidance for the advancement of grid-tied micro-grid technologies through MATLAB-implemented optimization algorithms.
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.
文摘Considering the uncertainty of wind power generation(WPG)and the specific operation behaviors of trading microgrids,this paper presents a blockchain-enabled robust-game electricity transaction model in a multi-microgrid system(MMS)to obtain optimal bidding-dispatching strategies,and achieve a transparent and decentralized electricity transaction.Combining blockchain technology and a non-cooperative game model,the established MMS electricity transaction architecture provides a complete information game environment for all game microgrids and facilitates the transparent,efficient,orderly,spontaneous management of MMS electricity transactions without the intervention of a third trusted party.Based on the distributed transaction architecture,an MMS robust-game model is presented to achieve the optimal day-ahead bidding-dispatching(DA-BD)strategies,in which the individual microgrid two-stage adjustable robust-game bidding-dispatching(ARG-BD)model characterizes the WPG uncertainty by employing uncertain interval and adjustable robust parameters.The binary expansion method,duality theory,big M method,and column-and-constrain generation algorithm(C&CG)are employed to solve the individual microgrid two-stage ARG-BD model.An alternating robust-game procedure integrating the C&CG algorithm and non-cooperative game model is developed to solve the MMS robust-game model.Case studies demonstrate the transparent and decentralized transaction,economic mutual benefits,and solution robustness of the presented method.
基金supported in part by the National Natural Science Foundation of China(No.52377075)Fundamental Research Funds for the Central Universities(No.2024CDJXY006).
文摘This paper presents a holistic pricing and distributed scheduling framework for multi-microgrid system(MMGS)that considers the supply‒demand relationships of the coupled electricity‒carbon market to promote collaborative market trading within the MMGS for economic and environmental benefit improvement.Initially,an operation model of each microgrid is developed by synthetically considering electricity-carbon operational constraints related to generation units and energy storage units.Then,a collaborative optimization strategy of the MMGS is established according to the Nash bargaining game(NBG)model with the objective of maximizing overall operational revenue.To determine the trading schedule,an accelerated prediction-correction-based alternating direction method of multipliers(PCB-ADMM)algorithm is employed to derive the optimal scheduling strategy of MMGS in a distributed manner,ensuring the privacy preservation of individual microgrids.For electricity-carbon pricing,a supply-demand ratio(SDR)based pricing strategy is proposed to dynamically update electricity and carbon allowance prices,which fundamentally guides and incentivizes each microgrid to trade within the MMGS preferentially rather than with an upstream distribution network.Finally,a study case verifies the effectiveness of the proposed framework in enhancing the operation economy and environmental friendliness of the entire MMGS.
文摘The main objective of this paper is to select the optimal model of a hybrid renewable-energy microgrid(MG)system for a village in India.The MG comprises solar photovoltaic(PV)modules,a wind turbine generator,a biomass generator,a battery bank,a diesel generator and an electric vehicle.The optimal model selection is based on technical,economic,environmental,social and reliability parameters.A novel spoonbill swarm optimization algorithm is proposed to select the best hybrid MG system.The optimization results are compared with particle swarm optimization,the genetic algorithm and the grasshopper optimization algorithm.The number or size of components of the optimized MG system is 215 PV modules,92 kW of wind turbine generation,25 kW of biomass generation,267 batteries,22 kW of electric vehicles and 30 kW of diesel generation.The optimized system was selected based on technical factors such as renewable dispersion(93.5%),the duty factor(5.85)and excess energy(15975 kWh/year)as well as eco-nomic considerations including the net present cost(Rs.34686622)and the cost of energy(9.3 Rs./kWh).Furthermore,environ-mental factors such as carbon emissions(396348 kg/year)and atmospheric particulate matter(22.686 kg/year);social factors such as the human progress index(0.68411),the employment generation factor(0.0389)and local employment generation(15.64643);and reliability parameters including loss of power supply probability(0.01%)and availability index(99.99%)were considered during the selection process.The spoonbill swarm optimization algorithm has reduced the convergence time by 1.2 times and decreased the number of iterations by 0.83 times compared with other algorithms.The performance of the MG system is validated in the MATLAB®environment.The results show that the MG system is the optimal system considering technical,economic,environmental,social and reliability parameters.Additionally,the spoonbill swarm optimization algorithm is found to be more efficient than the other algo-rithms in terms of iteration time and convergence time.
基金supported by the National Natural Science Foundation of China under Grant No.72331008,and No.72271211,and PolyU research project 1-YXBL.
文摘To meet the greenhouse gas reduction targets and address the uncertainty introduced by the surging penetration of stochastic renewable energy sources,energy storage systems are being deployed in microgrids.Relying solely on short-term uncertainty forecasts can result in substantial costs when making dispatch decisions for a storage system over an entire day.To mitigate this challenge,an adaptive robust optimization approach tailored for a hybrid hydrogen battery energy storage system(HBESS)operating within a microgrid is proposed,with a focus on efficient state-of-charge(SoC)planning to minimize microgrid expenses.The SoC ranges of the battery energy storage(BES)are determined in the day-ahead stage.Concurrently,the power generated by fuel cells and consumed by electrolysis device are optimized.This is followed by the intraday stage,where BES dispatch decisions are made within a predetermined SoC range to accommodate the uncertainties realized.To address this uncertainty and solve the adaptive optimization problem with integer recourse variables in the intraday stage,we proposed an outer-inner column-and-constraint generation algorithm(outer-inner-CCG).Numerical analyses underscored the high effectiveness and efficiency of the proposed adaptive robust operation model in making decisions for HBESS dispatch.
基金National Natural Science Foundation of China(62063016).
文摘Microgrids are networked control systems with multiple distributed generators(DGs).Microgrids are associated with many problems,such as communication delays,high sampling rates,and frequent controller updates,which make it challenging to realize coordination control among the DGs.Therefore,finite-time consensus algorithms and event-triggered control methods are combined to propose a distributed coordination control method for microgrid systems.The DG in the microgrid system serves as an agent node in the control network,and a distributed secondary controller is designed using finite-time consensus algorithm,such that the frequency and voltage restoration control has a faster convergence time and better anti-interference performance.The event-triggered function was designed based on the state information of the agents.The controller exchanges the state information at the trigger instants.System stability is analyzed using the Lyapunov stability theory,and it is verified that the controller cannot exhibit the Zeno phenomenon in the event-triggered process.A simulation platform was developed in Matlab/Simulink to verify that the proposed control method can effectively reduce the frequency of controller updates during communication delays and the burden on the communication network.
文摘This paper proposes a feedback-optimization-based control method for linear time-invariant systems,which is aimed to exponentially stabilize the system and,meanwhile,drive the system output to an approximate solution of an optimization problem with convex set constraints and affine inequality constraints.To ensure the exponential stability of the closed-loop system,the original optimization problem is first reformulated into a counterpart that has only convex set constraints.It is shown that the optimal solution of the new optimization problem is an approximate optimal solution of the original problem.Then,based on this new optimization problem,the projected primal–dual gradient dynamics algorithm is used to design the controller.By using the singular perturbation method,sufficient conditions are provided to ensure the exponential stability of the closed-loop system.The proposed method is also applied to microgrid control.
文摘With the direct rise of the social demand for renewable energy,as a new type of energy supply model in the new era,the operation control and optimization of microgrid play an important role in solving the problem of resource sharing.Microgrid can realize the flexibility of distributed power supply and the application of high efficiency,solving the problem of a large number and variety of forms of the power grid.Based on this,this paper will discuss the operation control strategy of microgrid based on a new energy grid connection,and provide constructive ideas for high-quality operation of microgrid.
基金supported by the National Natural Science Foundation of China(Nos.51767017 and 51867015)the Basic Research and Innovation Group Project of Gansu(No.18JR3RA13)the Major Science and Technology Project of Gansu(No.19ZD2GA003).
文摘This paper deeply introduces a brand-new research method for the synchronous characteristics of DC microgrid bus voltage and an improved synchronous control strategy.This method mainly targets the problem of bus voltage oscillation caused by the bifurcation behavior of DC microgrid converters.Firstly,the article elaborately establishes a mathematical model of a single distributed power source with hierarchical control.On this basis,a smallworld network model that can better adapt to the topology structure of DC microgrids is further constructed.Then,a voltage synchronization analysis method based on the main stability function is proposed,and the synchronous characteristics of DC bus voltage are deeply studied by analyzing the size of the minimum non-zero eigenvalue.In view of the situation that the line coupling strength between distributed power sources is insufficient to achieve bus voltage synchronization,this paper innovatively proposes a new improved adaptive controller to effectively control voltage synchronization.And the convergence of the designed controller is strictly proved by using Lyapunov’s stability theorem.Finally,the effectiveness and feasibility of the designed controller in this paper are fully verified through detailed simulation experiments.After comparative analysis with the traditional adaptive controller,it is found that the newly designed controller can make the bus voltages of each distributed power source achieve synchronization more quickly,and is significantly superior to the traditional adaptive controller in terms of anti-interference performance.
基金funded by StateGrid Beijing Electric PowerCompany Technology Project,grant number 520210230004.
文摘With the rapid development of renewable energy,the Microgrid Coalition(MGC)has become an important approach to improving energy utilization efficiency and economic performance.To address the operational optimization problem inmulti-microgrid cooperation,a cooperative game strategy based on the Nash bargainingmodel is proposed,aiming to enable collaboration among microgrids to maximize overall benefits while considering energy trading and cost optimization.First,each microgrid is regarded as a game participant,and a multi-microgrid cooperative game model based on Nash bargaining theory is constructed,targeting the minimization of total operational cost under constraints such as power balance and energy storage limits.Second,the Nash bargaining solution is introduced as the benefit allocation scheme to ensure individual rationality and coalition stability.Finally,theAlternating Direction Method of Multipliers(ADMM)is employed to decompose the centralized optimization problem into distributed subproblems for iterative solution,thereby reducing communication burden and protecting privacy.Case studies reveal that the operational costs of the threemicrogrids are reduced by 26.28%,19.00%,and 17.19%,respectively,and the overall renewable energy consumption rate is improved by approximately 66.11%.
