The performances of a hybrid energy system for decentralized heating are investigated.The proposed energy system consists of a solar collector,an air-source heat pump,a gas-fired boiler and a hot water tank.A mathemat...The performances of a hybrid energy system for decentralized heating are investigated.The proposed energy system consists of a solar collector,an air-source heat pump,a gas-fired boiler and a hot water tank.A mathematical model is developed to predict the operating characteristics of the system.The simulation results are compared with experimental data.Such a comparison indicates that the model accuracy is sufficient.The influence of the flat plate solar collector area on the economic and energy efficiency of such system is also evaluated through numerical simulations.Finally,this system is optimized using the method of orthogonal design.The results clearly demonstrate that the solar-heat pump-gas combined system is more convenient and efficient than the simple gas system and the heat pump-gas combined system,whereas it is less convenient but more efficient than the solarassisted gas system.展开更多
The transition of the global economy to a low-carbon development path has led to dramatic changes in the organization and functioning of energy markets around the world,where hybrid energy systems(HESs)are one of the ...The transition of the global economy to a low-carbon development path has led to dramatic changes in the organization and functioning of energy markets around the world,where hybrid energy systems(HESs)are one of the decisive active agents.At the same time,a number of problems facing the modern HESs are primarily due to the stochastic nature of the renewable energy they use,require further profound changes not only in the technologies they use and how they manage them,necessary to meet the needs of end consumers and interact with the unified energy system,but also to preserve the ability of the environment to self-heal.In order to make the process of changes more efficient and eco-deep,the article proposes to use and discusses the approach based on service dominant(SD)logic,which opens up new opportunities for solving the problems of HESs.First of all through:the implementation of closer service interaction with other participants in the energy markets,as well as with the environment;a systemically organized process of transforming the“product”economic activity of HESs into a service-dominant one;developing the generalized and engineering models for solving the problems of optimizing the technical and economic indicators of HESs,operation in steady-state and transient modes.The calculations confirm the effectiveness of the proposed approach and its ability to reduce the average daily costs for the system as a whole by 14.7%compared to the costs with a uniform distribution of power between the modules.展开更多
This paper applies new maximum-power-point tracking （MPPT） algorithm to a hybrid renewable energy system that combines both Wind-Turbine Generator （WTG） and Solar Photovoltaic （PV） Module （SPVM）. In this paper...This paper applies new maximum-power-point tracking （MPPT） algorithm to a hybrid renewable energy system that combines both Wind-Turbine Generator （WTG） and Solar Photovoltaic （PV） Module （SPVM）. In this paper, the WTG is a direct-drive system and includes wind turbine, three-phase permanent magnet synchronous generator, three-phase full bridge rectifier, and buck-bust converter, while the SPVM consist of solar PV modules, buck converter, maximum power tracking system for both systems, and load. Several methods are applied to obtain maximum performances, the appropriate and most effective method is called gradient-approximation method for WTG approach, because it enables the generator to operate at variable wind speeds. Furthermore MPPT also is used to optimized the achieved energy generated by solar PV modules.Matlab / Simulink approach is used to simulate, discuss, and optimized the generated power by varying the duty cycle of the converters, and tip speed ratio of the WTG system.展开更多
The new energy power generation is becoming increasingly important in the power system.Such as photovoltaic power generation has become a research hotspot,however,due to the characteristics of light radiation changes,...The new energy power generation is becoming increasingly important in the power system.Such as photovoltaic power generation has become a research hotspot,however,due to the characteristics of light radiation changes,photovoltaic power generation is unstable and random,resulting in a low utilization rate and directly affecting the stability of the power grid.To solve this problem,this paper proposes a coordinated control strategy for a newenergy power generation system with a hybrid energy storage unit based on the lithium iron phosphate-supercapacitor hybrid energy storage unit.Firstly,the variational mode decomposition algorithm is used to separate the high and low frequencies of the power signal,which is conducive to the rapid and accurate suppression of the power fluctuation of the energy storage system.Secondly,the fuzzy control algorithm is introduced to balance the power between energy storage.In this paper,the actual data is used for simulation,and the simulation results show that the strategy realizes the effective suppression of the bus voltage fluctuation and the accurate control of the internal state of the energy storage unit,effectively avoiding problems such as overshoot and over-discharge,and can significantly improve the stability of the photovoltaic power generation systemand the stability of the Direct Current bus.It is of great significance to promote the development of collaborative control technology for photovoltaic hybrid energy storage units.展开更多
In the independent electro-hydrogen system(IEHS)with hybrid energy storage(HESS),achieving optimal scheduling is crucial.Still,it presents a challenge due to the significant deviations in values ofmultiple optimizatio...In the independent electro-hydrogen system(IEHS)with hybrid energy storage(HESS),achieving optimal scheduling is crucial.Still,it presents a challenge due to the significant deviations in values ofmultiple optimization objective functions caused by their physical dimensions.These deviations seriously affect the scheduling process.A novel standardization fusion method has been established to address this issue by analyzing the variation process of each objective function’s values.The optimal scheduling results of IEHS with HESS indicate that the economy and overall energy loss can be improved 2–3 times under different optimization methods.The proposed method better balances all optimization objective functions and reduces the impact of their dimensionality.When the cost of BESS decreases by approximately 30%,its participation deepens by about 1 time.Moreover,if the price of the electrolyzer is less than 15¥/kWh or if the cost of the fuel cell drops below 4¥/kWh,their participation will increase substantially.This study aims to provide a more reasonable approach to solving multi-objective optimization problems.展开更多
Power quality is a crucial area of research in contemporary power systems,particularly given the rapid proliferation of intermittent renewable energy sources such as wind power.This study investigated the relationship...Power quality is a crucial area of research in contemporary power systems,particularly given the rapid proliferation of intermittent renewable energy sources such as wind power.This study investigated the relationships between power quality indices of system output and PSD by utilizing theories related to spectra,PSD,and random signal power spectra.The relationship was derived,validated through experiments and simulations,and subsequently applied to multi-objective optimization.Various optimization algorithms were compared to achieve optimal system power quality.The findings revealed that the relationships between power quality indices and PSD were influenced by variations in the order of the power spectral estimation model.An increase in the order of the AR model resulted in a 36%improvement in the number of optimal solutions.Regarding optimal solution distribution,NSGA-II demonstrated superior diversity,while MOEA/D exhibited better convergence.However,practical applications showed that while MOEA/D had higher convergence,NSGA-II produced superior optimal solutions,achieving the best power quality indices(THDi at 4.62%,d%at 3.51%,and cosφat 96%).These results suggest that the proposed method holds significant potential for optimizing power quality in practical applications.展开更多
To address the issue of coordinated control of multiple hydrogen and battery storage units to suppress the grid-injected power deviation of wind farms,an online optimization strategy for Battery-hydrogen hybrid energy...To address the issue of coordinated control of multiple hydrogen and battery storage units to suppress the grid-injected power deviation of wind farms,an online optimization strategy for Battery-hydrogen hybrid energy storage systems based on measurement feedback is proposed.First,considering the high charge/discharge losses of hydrogen storage and the low energy density of battery storage,an operational optimization objective is established to enable adaptive energy adjustment in the Battery-hydrogen hybrid energy storage system.Next,an online optimization model minimizing the operational cost of the hybrid system is constructed to suppress grid-injected power deviations with satisfying the operational constraints of hydrogen storage and batteries.Finally,utilizing the online measurement of the energy states of hydrogen storage and batteries,an online optimization strategy based on measurement feedback is designed.Case study results show:before and after smoothing the fluctuations in wind power,the time when the power exceeded the upper and lower limits of the grid-injected power accounted for 24.1%and 1.45%of the total time,respectively,the proposed strategy can effectively keep the grid-injected power deviations of wind farms within the allowable range.Hydrogen storage and batteries respectively undertake long-term and short-term charge/discharge tasks,effectively reducing charge/discharge losses of the Battery-hydrogen hybrid energy storage systems and improving its operational efficiency.展开更多
The economic operation of integrated energy system(IES)faces new challenges such as multi-timescale characteristics of heterogeneous energy sources,and cooperative operation of hybrid energy storage system(HESS).To th...The economic operation of integrated energy system(IES)faces new challenges such as multi-timescale characteristics of heterogeneous energy sources,and cooperative operation of hybrid energy storage system(HESS).To this end,this paper investigates the multi-timescale rolling opti-mization problem for IES integrated with HESS.Firstly,the architecture of IES with HESS is established,a comparative analysis is conducted to evaluate the advantages of the HESS over a single energy storage system(SESS)in stabilizing power fluctuations.Secondly,the dayahead and real-time scheduling cost functions of IES are established,the day-ahead scheduling mainly depends on operation costs of the components in IES,the real-time optimal scheduling adopts the Lya-punov optimization method to schedule the battery and hydrogen energy storage in each time slot,so as to minimize the real-time average scheduling operation cost,and the problem of day-ahead and real-time scheduling error,which caused by the uncertainty of the energy storage is solved by online optimization.Finally,the proposed model is verified to reduce the scheduling operation cost and the dispatching error by performing an arithmetic example analysis of the IES in Shanghai,which provides a reference for the safe and stable operation of the IES.展开更多
In order to cope with the challenges brought by multiple uncertainties to integrated hydrogen hybrid energy systems,a stability-constrained two-stage robust optimization method considering small disturbance stability ...In order to cope with the challenges brought by multiple uncertainties to integrated hydrogen hybrid energy systems,a stability-constrained two-stage robust optimization method considering small disturbance stability and characteristics of dynamic response is proposed in this paper.In the first operating stage,the charging/discharging state of the battery and the startstop state of the electrolyzer and fuel cell are determined.Then,power constraints for stabilizing ESSs power output is considered between the first and second stage optimization to improve the small disturbance stability of the robust operation plan.Then,the goal of minimizing the operation cost and determine a robust operation operating plan under the worst case is conducting in the second stage optimization.Through the small-signal model with time-delay effect,the eigenvalue analysis method is used to find the ESSs power range,and the small-signal stability of obtained robust operation plan can be enhanced.Finally,the effectiveness and superiority of the proposed method are proved by comparing with the traditional static robust optimization method.Impacts of uncertain parameters on economy and stability are also investigated in a typical example.展开更多
Due to the uncertainty of renewable energy power generation and the non-linearity of load demand,it becomes complicated to determine the capacity of each device in hybrid renewable energy power generation systems.This...Due to the uncertainty of renewable energy power generation and the non-linearity of load demand,it becomes complicated to determine the capacity of each device in hybrid renewable energy power generation systems.This work aims to optimize the capacity of two types of the off-grid hybrid wind-hydrogen energy system.We considered the maximum profit of the system and the minimum loss of power supply probability as optimization goals.Firstly,we established steady-state models of the wind turbine,alkaline electrolyzer,lead-acid battery,and proton exchange membrane fuel cell in matrix laboratory software to optimize the capacity.Secondly,we analyzed the operating mode of the system and determined two system structures(system contains batteries whether or not).Finally,according to the wind speed and load in the sample area,we compared the economics of the two systems and selected the optimal configuration for the area.In the same calculation example data,the non-dominated sorting genetic algorithm-II(NSGA-II)is used to optimize the capacity of each device in the two systems.The results showed that the profit of the without battery-equipped system is 32.38%higher than another system.But the power supply reliability is the opposite.To avoid the contingency of the calculation results,we used the traditional genetic algorithm(GA)and ant colony optimization(ACO)to calculate the same example.The results showed that NSGA-II is significantly better than GA and ACO in terms of iteration steps and calculation results.The required architecture for the System-I composes of 3 numbers of 10 kW wind turbines,61 sets of 12 V·240 Ah leadacid batteries,8 kW electrolytic cell,and 6 kW PEMFC.The net profit and LPSP are ¥44,315 and 0.01254 respectively.The required architecture for the System-II composes of 2 numbers of 10 kW wind turbines,24 kW electrolytic cells,and 18 kW PEMFC.Net profit and LPSP are ¥58,663 and 0.03244,respectively.This paper provided two schemes for the optimal configuration of the hybrid wind-hydrogen energy system in islanding mode,which provided a theoretical basis for practical engineering applications.展开更多
In this research,a modified fractional order proportional integral derivate(FOPID)control method is proposed for the photovoltaic(PV)and thermoelectric generator(TEG)combined hybrid renewable energy system.The faster ...In this research,a modified fractional order proportional integral derivate(FOPID)control method is proposed for the photovoltaic(PV)and thermoelectric generator(TEG)combined hybrid renewable energy system.The faster tracking and steady-state output are aimed at the suggested maximum power point tracking(MPPT)control technique.The derivative order number(μ)value in the improved FOPID(also known as PIλDμ)control structure will be dynamically updated utilizing the value of change in PV array voltage output.During the transient,the value ofμis changeable;it’s one at the start and after reaching the maximum power point(MPP),allowing for strong tracking characteristics.TEG will use the freely available waste thermal energy created surrounding the PVarray for additional power generation,increasing the system’s energy conversion efficiency.A high-gain DC-DC converter circuit is included in the system to maintain a high amplitude DC input voltage to the inverter circuit.The proposed approach’s performance was investigated using an extensive MATLAB software simulation and validated by comparing findings with the perturbation and observation(P&O)type MPPT control method.The study results demonstrate that the FOPID controller-based MPPT control outperforms the P&O method in harvesting the maximum power achievable from the PV-TEG hybrid source.There is also a better control action and a faster response.展开更多
This study proposes a combined hybrid energy storage system(HESS) and transmission grid(TG) model, and a corresponding time series operation simulation(TSOS) model is established to relieve the peak-shaving pressure o...This study proposes a combined hybrid energy storage system(HESS) and transmission grid(TG) model, and a corresponding time series operation simulation(TSOS) model is established to relieve the peak-shaving pressure of power systems under the integration of renewable energy. First, a linear model for the optimal operation of the HESS is established, which considers the different power-efficiency characteristics of the pumped storage system, electrochemical storage system, and a new type of liquid compressed air energy storage. Second, a TSOS simulation model for peak shaving is built to maximize the power entering the grid from the wind farms and HESS. Based on the proposed model, this study considers the transmission capacity of a TG. By adding the power-flow constraints of the TG, a TSOS-based HESS and TG combination model for peak shaving is established. Finally, the improved IEEE-39 and IEEE-118 bus systems were considered as examples to verify the effectiveness and feasibility of the proposed model.展开更多
Regarding the problem of the short driving distance of pure electric vehicles,a battery,super-capacitor,and DC/DC converter are combined to form a hybrid energy storage system(HESS).A fuzzy adaptive filtering-based en...Regarding the problem of the short driving distance of pure electric vehicles,a battery,super-capacitor,and DC/DC converter are combined to form a hybrid energy storage system(HESS).A fuzzy adaptive filtering-based energy management strategy(FAFBEMS)is proposed to allocate the required power of the vehicle.Firstly,the state of charge(SOC)of the super-capacitor is limited according to the driving/braking mode of the vehicle to ensure that it is in a suitable working state,and fuzzy rules are designed to adaptively adjust the filtering time constant,to realize reasonable power allocation.Then,the positive and negative power are determined,and the average power of driving/braking is calculated so as to limit the power amplitude to protect the battery.To verify the proposed FAFBEMS strategy for HESS,simulations are performed under the UDDS(Urban Dynamometer Driving Schedule)driving cycle.The results show that the FAFBEMS strategy can effectively reduce the current amplitude of the battery,and the final SOC of the battery and super-capacitor is optimized to varying degrees.The energy consumption is 7.8%less than that of the rule-based energy management strategy,10.9%less than that of the fuzzy control energy management strategy,and 13.1%less than that of the filtering-based energy management strategy,which verifies the effectiveness of the FAFBEMS strategy.展开更多
Hybrid energy harvesters under external excitation have complex dynamical behavior and the superiority of promoting energy harvesting efficiency.Sometimes,it is difficult to model the governing equations of the hybrid...Hybrid energy harvesters under external excitation have complex dynamical behavior and the superiority of promoting energy harvesting efficiency.Sometimes,it is difficult to model the governing equations of the hybrid energy harvesting system precisely,especially under external excitation.Accompanied with machine learning,data-driven methods play an important role in discovering the governing equations from massive datasets.Recently,there are many studies of datadriven models done in aspect of ordinary differential equations and stochastic differential equations(SDEs).However,few studies discover the governing equations for the hybrid energy harvesting system under harmonic excitation and Gaussian white noise(GWN).Thus,in this paper,a data-driven approach,with least square and sparse constraint,is devised to discover the governing equations of the systems from observed data.Firstly,the algorithm processing and pseudo code are given.Then,the effectiveness and accuracy of the method are verified by taking two examples with harmonic excitation and GWN,respectively.For harmonic excitation,all coefficients of the system can be simultaneously learned.For GWN,we approximate the drift term and diffusion term by using the Kramers-Moyal formulas,and separately learn the coefficients of the drift term and diffusion term.Cross-validation(CV)and mean-square error(MSE)are utilized to obtain the optimal number of iterations.Finally,the comparisons between true values and learned values are depicted to demonstrate that the approach is well utilized to obtain the governing equations for the hybrid energy harvester under harmonic excitation and GWN.展开更多
In this paper, an optimized model is proposed to find the best values for decision variables to optimize the grid connected hybrid renewable energy system which consists of photovoltaic panels, wind turbines and batte...In this paper, an optimized model is proposed to find the best values for decision variables to optimize the grid connected hybrid renewable energy system which consists of photovoltaic panels, wind turbines and battery bank for electrification to North-east region of Afghanistan to meet winter power shortages of the area. In the proposed model, there are three decision variables namely, the total area occupied by the set of PV panels, total swept area by the rotating turbines＇ blades, and the number of batteries. GA （genetic algorithm） is defined to find the optimal values of the decision variables. The objective of this research is to minimize the LCC （life cycle cost） of the hybrid renewable energy system, and ensuring at the same time systems reliability level which is measured in terms of LPSP （loss of power supply probability）.展开更多
In this paper, we conduct research on the hybrid energy storage based photovoltaic piconets and the isolated net running comprehensive control system in the campus environment. Piconets flexible operation mode and the...In this paper, we conduct research on the hybrid energy storage based photovoltaic piconets and the isolated net running comprehensive control system in the campus environment. Piconets flexible operation mode and the efficient power supply without perfect stable control. Micro the early stage of network development related to micro network operation concepts are modeled on the control of large power system. Our proposed approach is proven to be effective and feasible through the numerical simulation and theoretical analysis which will be meaningful.展开更多
To solve the problem energy deficit encountered in developing countries,Hybrid Renewable Energy System(HRES)appears to be a very good solution.The paper presents the optimal design of a hybrid renewable energy system ...To solve the problem energy deficit encountered in developing countries,Hybrid Renewable Energy System(HRES)appears to be a very good solution.The paper presents the optimal design of a hybrid renewable energy system considering the technical i.e Loss of Power Supply Probability(LPSP),economic i.e Cost of Electricity(COE)and Net Present Cost(NPC)and environmental i.e Total Greenhouse gases emission(TGE)aspects using Particle Swarm Optimization(PSO),hybrid Particle Swarm Optimization-Grey Wolf Optimization(PSOGWO),hybrid Grey-Wolf Optimization-Cuckoo Search(GWOCS)and Sine-Cosine Algorithm(SCA)for a Community multimedia center in MAKENENE,Cameroon;where inhabitants have to spend at times 3 to 4 days of blackout.Seven configurations(Scenarios)of hybrid energy systems including PV,WT,Battery and Diesel generator are analyzed considering an average daily energy load of 50.22 kWh with a peak load of 5.6 kW.Four values of the derating factor i.e 0.6,0.7,0.8 and 0.9 are used in this analysis and the best value is 0.9.Scenario 3 with LPSP,COE,NPC,TGE and RF of 0.003%,0.15913$/kWh,46953.0485$,2.3406 kg/year and 99.8%respectively when using GWOCS is found to be the most appropriate for the Community multimedia center.The optimal Scenario is obtained for a system comprising of 18 kW of P_(pv-rated)corresponding to 69 solar panels,3 days of AD corresponding to a total battery capacity of 241 kWh and 1 of N_(dg).展开更多
Some types of renewable energy have been experiencing rapid evolution in recent decades, notably among the energies associated with the oceans, such as wave and current energies. The development of new energy conversi...Some types of renewable energy have been experiencing rapid evolution in recent decades, notably among the energies associated with the oceans, such as wave and current energies. The development of new energy conversion technologies for these two forms of energy has been offering a large number of equipment configurations and plant geometries for energy conversion. This process can be implemented aiming at the result of feasibility studies in places with energy potentials, establishing minimum feasibility limits to be reached. This work aims to contribute in this sense with a feasibility study of a system with ocean wave power plants and with socio-current power plants to be operated on the southern coast of Brazil. This study evaluates a hybrid system with contributions from energy supplies obtained from wave plants and current plants, connected to the grid and supplying the demand of the municipalities in the North Coast region of the State of Rio Grande do Sul, the southernmost state of Brazil. The study was carried out with simulations with the Homer Legacy software, with some adaptations for the simulation of ocean wave plants and ocean current plants. The results indicate that the ocean wave power plants were viable in the vast majority of simulated scenarios, while the ocean current power plants were viable in the scenarios with more intense average ocean current speeds and with more expensive energy acquired from the interconnected system.展开更多
The differential pricing for peak hours encourages industrial consumers to look for independent power supplies for the period from 19 to 22 hours. This paper presents a study to identify the optimal solution for a rec...The differential pricing for peak hours encourages industrial consumers to look for independent power supplies for the period from 19 to 22 hours. This paper presents a study to identify the optimal solution for a recycled paper mill that also intends to work in that period. The factory is located in Rio Grande do Sul, in southern Brazil, and considers the use of a diesel gen set, a micro hydro power plant and possibly PV modules. Two micro hydro power plants were considered in the study, an old plant to be renewed and another to be fully implemented. The software Homer was used as a tool to determine the most feasible combination of components considered in the study. The sale of surplus power to the energy system appears as a key to viability of alternatives that are not based solely on diesel generators. The optimal solution consists of a combination of diesel generators and micro hydro power plant, in one case, and only on hydroelectric power plant in another, with a significant penetration of PV modules if its cost is reduced to 12% of the current price, selling an amount of energy equal to that which is bought. The annual water availability in one of the sites requires diesel supplement, while the other, more abundant, this supplement is not necessary.展开更多
文摘The performances of a hybrid energy system for decentralized heating are investigated.The proposed energy system consists of a solar collector,an air-source heat pump,a gas-fired boiler and a hot water tank.A mathematical model is developed to predict the operating characteristics of the system.The simulation results are compared with experimental data.Such a comparison indicates that the model accuracy is sufficient.The influence of the flat plate solar collector area on the economic and energy efficiency of such system is also evaluated through numerical simulations.Finally,this system is optimized using the method of orthogonal design.The results clearly demonstrate that the solar-heat pump-gas combined system is more convenient and efficient than the simple gas system and the heat pump-gas combined system,whereas it is less convenient but more efficient than the solarassisted gas system.
文摘The transition of the global economy to a low-carbon development path has led to dramatic changes in the organization and functioning of energy markets around the world,where hybrid energy systems(HESs)are one of the decisive active agents.At the same time,a number of problems facing the modern HESs are primarily due to the stochastic nature of the renewable energy they use,require further profound changes not only in the technologies they use and how they manage them,necessary to meet the needs of end consumers and interact with the unified energy system,but also to preserve the ability of the environment to self-heal.In order to make the process of changes more efficient and eco-deep,the article proposes to use and discusses the approach based on service dominant(SD)logic,which opens up new opportunities for solving the problems of HESs.First of all through:the implementation of closer service interaction with other participants in the energy markets,as well as with the environment;a systemically organized process of transforming the“product”economic activity of HESs into a service-dominant one;developing the generalized and engineering models for solving the problems of optimizing the technical and economic indicators of HESs,operation in steady-state and transient modes.The calculations confirm the effectiveness of the proposed approach and its ability to reduce the average daily costs for the system as a whole by 14.7%compared to the costs with a uniform distribution of power between the modules.
文摘This paper applies new maximum-power-point tracking （MPPT） algorithm to a hybrid renewable energy system that combines both Wind-Turbine Generator （WTG） and Solar Photovoltaic （PV） Module （SPVM）. In this paper, the WTG is a direct-drive system and includes wind turbine, three-phase permanent magnet synchronous generator, three-phase full bridge rectifier, and buck-bust converter, while the SPVM consist of solar PV modules, buck converter, maximum power tracking system for both systems, and load. Several methods are applied to obtain maximum performances, the appropriate and most effective method is called gradient-approximation method for WTG approach, because it enables the generator to operate at variable wind speeds. Furthermore MPPT also is used to optimized the achieved energy generated by solar PV modules.Matlab / Simulink approach is used to simulate, discuss, and optimized the generated power by varying the duty cycle of the converters, and tip speed ratio of the WTG system.
基金supported by the State Grid Corporation of China Science and Technology Project,grant number 52270723000900K.
文摘The new energy power generation is becoming increasingly important in the power system.Such as photovoltaic power generation has become a research hotspot,however,due to the characteristics of light radiation changes,photovoltaic power generation is unstable and random,resulting in a low utilization rate and directly affecting the stability of the power grid.To solve this problem,this paper proposes a coordinated control strategy for a newenergy power generation system with a hybrid energy storage unit based on the lithium iron phosphate-supercapacitor hybrid energy storage unit.Firstly,the variational mode decomposition algorithm is used to separate the high and low frequencies of the power signal,which is conducive to the rapid and accurate suppression of the power fluctuation of the energy storage system.Secondly,the fuzzy control algorithm is introduced to balance the power between energy storage.In this paper,the actual data is used for simulation,and the simulation results show that the strategy realizes the effective suppression of the bus voltage fluctuation and the accurate control of the internal state of the energy storage unit,effectively avoiding problems such as overshoot and over-discharge,and can significantly improve the stability of the photovoltaic power generation systemand the stability of the Direct Current bus.It is of great significance to promote the development of collaborative control technology for photovoltaic hybrid energy storage units.
基金sponsored by R&D Program of Beijing Municipal Education Commission(KM202410009013).
文摘In the independent electro-hydrogen system(IEHS)with hybrid energy storage(HESS),achieving optimal scheduling is crucial.Still,it presents a challenge due to the significant deviations in values ofmultiple optimization objective functions caused by their physical dimensions.These deviations seriously affect the scheduling process.A novel standardization fusion method has been established to address this issue by analyzing the variation process of each objective function’s values.The optimal scheduling results of IEHS with HESS indicate that the economy and overall energy loss can be improved 2–3 times under different optimization methods.The proposed method better balances all optimization objective functions and reduces the impact of their dimensionality.When the cost of BESS decreases by approximately 30%,its participation deepens by about 1 time.Moreover,if the price of the electrolyzer is less than 15¥/kWh or if the cost of the fuel cell drops below 4¥/kWh,their participation will increase substantially.This study aims to provide a more reasonable approach to solving multi-objective optimization problems.
基金funded by the Inner Mongolia Nature Foundation Project,Project number:2023JQ04.
文摘Power quality is a crucial area of research in contemporary power systems,particularly given the rapid proliferation of intermittent renewable energy sources such as wind power.This study investigated the relationships between power quality indices of system output and PSD by utilizing theories related to spectra,PSD,and random signal power spectra.The relationship was derived,validated through experiments and simulations,and subsequently applied to multi-objective optimization.Various optimization algorithms were compared to achieve optimal system power quality.The findings revealed that the relationships between power quality indices and PSD were influenced by variations in the order of the power spectral estimation model.An increase in the order of the AR model resulted in a 36%improvement in the number of optimal solutions.Regarding optimal solution distribution,NSGA-II demonstrated superior diversity,while MOEA/D exhibited better convergence.However,practical applications showed that while MOEA/D had higher convergence,NSGA-II produced superior optimal solutions,achieving the best power quality indices(THDi at 4.62%,d%at 3.51%,and cosφat 96%).These results suggest that the proposed method holds significant potential for optimizing power quality in practical applications.
基金Supported by State Grid Zhejiang Electric Power Co.,Ltd.Science and Technology Project Funding(No.B311DS230005).
文摘To address the issue of coordinated control of multiple hydrogen and battery storage units to suppress the grid-injected power deviation of wind farms,an online optimization strategy for Battery-hydrogen hybrid energy storage systems based on measurement feedback is proposed.First,considering the high charge/discharge losses of hydrogen storage and the low energy density of battery storage,an operational optimization objective is established to enable adaptive energy adjustment in the Battery-hydrogen hybrid energy storage system.Next,an online optimization model minimizing the operational cost of the hybrid system is constructed to suppress grid-injected power deviations with satisfying the operational constraints of hydrogen storage and batteries.Finally,utilizing the online measurement of the energy states of hydrogen storage and batteries,an online optimization strategy based on measurement feedback is designed.Case study results show:before and after smoothing the fluctuations in wind power,the time when the power exceeded the upper and lower limits of the grid-injected power accounted for 24.1%and 1.45%of the total time,respectively,the proposed strategy can effectively keep the grid-injected power deviations of wind farms within the allowable range.Hydrogen storage and batteries respectively undertake long-term and short-term charge/discharge tasks,effectively reducing charge/discharge losses of the Battery-hydrogen hybrid energy storage systems and improving its operational efficiency.
基金supported by the National Natural Science Foundation of China(No.12171145)。
文摘The economic operation of integrated energy system(IES)faces new challenges such as multi-timescale characteristics of heterogeneous energy sources,and cooperative operation of hybrid energy storage system(HESS).To this end,this paper investigates the multi-timescale rolling opti-mization problem for IES integrated with HESS.Firstly,the architecture of IES with HESS is established,a comparative analysis is conducted to evaluate the advantages of the HESS over a single energy storage system(SESS)in stabilizing power fluctuations.Secondly,the dayahead and real-time scheduling cost functions of IES are established,the day-ahead scheduling mainly depends on operation costs of the components in IES,the real-time optimal scheduling adopts the Lya-punov optimization method to schedule the battery and hydrogen energy storage in each time slot,so as to minimize the real-time average scheduling operation cost,and the problem of day-ahead and real-time scheduling error,which caused by the uncertainty of the energy storage is solved by online optimization.Finally,the proposed model is verified to reduce the scheduling operation cost and the dispatching error by performing an arithmetic example analysis of the IES in Shanghai,which provides a reference for the safe and stable operation of the IES.
基金National Natural Science Foundation of China(51977181)Sichuan Science and Technology Program(19YYJC0698)+1 种基金Fok Ying-Tong Education Foundation of China(171104)the Science and Technology Project of State Grid Corporation of China(SGSW0000GHJS1900106).
文摘In order to cope with the challenges brought by multiple uncertainties to integrated hydrogen hybrid energy systems,a stability-constrained two-stage robust optimization method considering small disturbance stability and characteristics of dynamic response is proposed in this paper.In the first operating stage,the charging/discharging state of the battery and the startstop state of the electrolyzer and fuel cell are determined.Then,power constraints for stabilizing ESSs power output is considered between the first and second stage optimization to improve the small disturbance stability of the robust operation plan.Then,the goal of minimizing the operation cost and determine a robust operation operating plan under the worst case is conducting in the second stage optimization.Through the small-signal model with time-delay effect,the eigenvalue analysis method is used to find the ESSs power range,and the small-signal stability of obtained robust operation plan can be enhanced.Finally,the effectiveness and superiority of the proposed method are proved by comparing with the traditional static robust optimization method.Impacts of uncertain parameters on economy and stability are also investigated in a typical example.
基金supported by the Inner Mongolia Science and Technology Program under Grant 2021GG0336by the Open Fund of Key Laboratory of Wind Energy and Solar Energy Technology(Inner Mongolia University of Technology),Ministry of Education(No.2020ZD01)in China.
文摘Due to the uncertainty of renewable energy power generation and the non-linearity of load demand,it becomes complicated to determine the capacity of each device in hybrid renewable energy power generation systems.This work aims to optimize the capacity of two types of the off-grid hybrid wind-hydrogen energy system.We considered the maximum profit of the system and the minimum loss of power supply probability as optimization goals.Firstly,we established steady-state models of the wind turbine,alkaline electrolyzer,lead-acid battery,and proton exchange membrane fuel cell in matrix laboratory software to optimize the capacity.Secondly,we analyzed the operating mode of the system and determined two system structures(system contains batteries whether or not).Finally,according to the wind speed and load in the sample area,we compared the economics of the two systems and selected the optimal configuration for the area.In the same calculation example data,the non-dominated sorting genetic algorithm-II(NSGA-II)is used to optimize the capacity of each device in the two systems.The results showed that the profit of the without battery-equipped system is 32.38%higher than another system.But the power supply reliability is the opposite.To avoid the contingency of the calculation results,we used the traditional genetic algorithm(GA)and ant colony optimization(ACO)to calculate the same example.The results showed that NSGA-II is significantly better than GA and ACO in terms of iteration steps and calculation results.The required architecture for the System-I composes of 3 numbers of 10 kW wind turbines,61 sets of 12 V·240 Ah leadacid batteries,8 kW electrolytic cell,and 6 kW PEMFC.The net profit and LPSP are ¥44,315 and 0.01254 respectively.The required architecture for the System-II composes of 2 numbers of 10 kW wind turbines,24 kW electrolytic cells,and 18 kW PEMFC.Net profit and LPSP are ¥58,663 and 0.03244,respectively.This paper provided two schemes for the optimal configuration of the hybrid wind-hydrogen energy system in islanding mode,which provided a theoretical basis for practical engineering applications.
基金The authors extend their appreciation to the Deputyship for Research&Innovation,Ministry of Education in Saudi Arabia for funding this research work through the Project Number(IF-PSAU-2021/01/18128).
文摘In this research,a modified fractional order proportional integral derivate(FOPID)control method is proposed for the photovoltaic(PV)and thermoelectric generator(TEG)combined hybrid renewable energy system.The faster tracking and steady-state output are aimed at the suggested maximum power point tracking(MPPT)control technique.The derivative order number(μ)value in the improved FOPID(also known as PIλDμ)control structure will be dynamically updated utilizing the value of change in PV array voltage output.During the transient,the value ofμis changeable;it’s one at the start and after reaching the maximum power point(MPP),allowing for strong tracking characteristics.TEG will use the freely available waste thermal energy created surrounding the PVarray for additional power generation,increasing the system’s energy conversion efficiency.A high-gain DC-DC converter circuit is included in the system to maintain a high amplitude DC input voltage to the inverter circuit.The proposed approach’s performance was investigated using an extensive MATLAB software simulation and validated by comparing findings with the perturbation and observation(P&O)type MPPT control method.The study results demonstrate that the FOPID controller-based MPPT control outperforms the P&O method in harvesting the maximum power achievable from the PV-TEG hybrid source.There is also a better control action and a faster response.
基金supported by the State Grid Science and Technology Project (No.52999821N004)。
文摘This study proposes a combined hybrid energy storage system(HESS) and transmission grid(TG) model, and a corresponding time series operation simulation(TSOS) model is established to relieve the peak-shaving pressure of power systems under the integration of renewable energy. First, a linear model for the optimal operation of the HESS is established, which considers the different power-efficiency characteristics of the pumped storage system, electrochemical storage system, and a new type of liquid compressed air energy storage. Second, a TSOS simulation model for peak shaving is built to maximize the power entering the grid from the wind farms and HESS. Based on the proposed model, this study considers the transmission capacity of a TG. By adding the power-flow constraints of the TG, a TSOS-based HESS and TG combination model for peak shaving is established. Finally, the improved IEEE-39 and IEEE-118 bus systems were considered as examples to verify the effectiveness and feasibility of the proposed model.
基金supported by the National Natural Science Foundation of China(61673164)the Natural Science Foundation of Hunan Province(2020JJ6024)the Scientific Research Fund of Hunan Provincal Education Department(19K025).
文摘Regarding the problem of the short driving distance of pure electric vehicles,a battery,super-capacitor,and DC/DC converter are combined to form a hybrid energy storage system(HESS).A fuzzy adaptive filtering-based energy management strategy(FAFBEMS)is proposed to allocate the required power of the vehicle.Firstly,the state of charge(SOC)of the super-capacitor is limited according to the driving/braking mode of the vehicle to ensure that it is in a suitable working state,and fuzzy rules are designed to adaptively adjust the filtering time constant,to realize reasonable power allocation.Then,the positive and negative power are determined,and the average power of driving/braking is calculated so as to limit the power amplitude to protect the battery.To verify the proposed FAFBEMS strategy for HESS,simulations are performed under the UDDS(Urban Dynamometer Driving Schedule)driving cycle.The results show that the FAFBEMS strategy can effectively reduce the current amplitude of the battery,and the final SOC of the battery and super-capacitor is optimized to varying degrees.The energy consumption is 7.8%less than that of the rule-based energy management strategy,10.9%less than that of the fuzzy control energy management strategy,and 13.1%less than that of the filtering-based energy management strategy,which verifies the effectiveness of the FAFBEMS strategy.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.12002089 and 11902081)roject of Science and Technology of Guangzhou(Grant No.202201010326)
文摘Hybrid energy harvesters under external excitation have complex dynamical behavior and the superiority of promoting energy harvesting efficiency.Sometimes,it is difficult to model the governing equations of the hybrid energy harvesting system precisely,especially under external excitation.Accompanied with machine learning,data-driven methods play an important role in discovering the governing equations from massive datasets.Recently,there are many studies of datadriven models done in aspect of ordinary differential equations and stochastic differential equations(SDEs).However,few studies discover the governing equations for the hybrid energy harvesting system under harmonic excitation and Gaussian white noise(GWN).Thus,in this paper,a data-driven approach,with least square and sparse constraint,is devised to discover the governing equations of the systems from observed data.Firstly,the algorithm processing and pseudo code are given.Then,the effectiveness and accuracy of the method are verified by taking two examples with harmonic excitation and GWN,respectively.For harmonic excitation,all coefficients of the system can be simultaneously learned.For GWN,we approximate the drift term and diffusion term by using the Kramers-Moyal formulas,and separately learn the coefficients of the drift term and diffusion term.Cross-validation(CV)and mean-square error(MSE)are utilized to obtain the optimal number of iterations.Finally,the comparisons between true values and learned values are depicted to demonstrate that the approach is well utilized to obtain the governing equations for the hybrid energy harvester under harmonic excitation and GWN.
文摘In this paper, an optimized model is proposed to find the best values for decision variables to optimize the grid connected hybrid renewable energy system which consists of photovoltaic panels, wind turbines and battery bank for electrification to North-east region of Afghanistan to meet winter power shortages of the area. In the proposed model, there are three decision variables namely, the total area occupied by the set of PV panels, total swept area by the rotating turbines＇ blades, and the number of batteries. GA （genetic algorithm） is defined to find the optimal values of the decision variables. The objective of this research is to minimize the LCC （life cycle cost） of the hybrid renewable energy system, and ensuring at the same time systems reliability level which is measured in terms of LPSP （loss of power supply probability）.
文摘In this paper, we conduct research on the hybrid energy storage based photovoltaic piconets and the isolated net running comprehensive control system in the campus environment. Piconets flexible operation mode and the efficient power supply without perfect stable control. Micro the early stage of network development related to micro network operation concepts are modeled on the control of large power system. Our proposed approach is proven to be effective and feasible through the numerical simulation and theoretical analysis which will be meaningful.
文摘To solve the problem energy deficit encountered in developing countries,Hybrid Renewable Energy System(HRES)appears to be a very good solution.The paper presents the optimal design of a hybrid renewable energy system considering the technical i.e Loss of Power Supply Probability(LPSP),economic i.e Cost of Electricity(COE)and Net Present Cost(NPC)and environmental i.e Total Greenhouse gases emission(TGE)aspects using Particle Swarm Optimization(PSO),hybrid Particle Swarm Optimization-Grey Wolf Optimization(PSOGWO),hybrid Grey-Wolf Optimization-Cuckoo Search(GWOCS)and Sine-Cosine Algorithm(SCA)for a Community multimedia center in MAKENENE,Cameroon;where inhabitants have to spend at times 3 to 4 days of blackout.Seven configurations(Scenarios)of hybrid energy systems including PV,WT,Battery and Diesel generator are analyzed considering an average daily energy load of 50.22 kWh with a peak load of 5.6 kW.Four values of the derating factor i.e 0.6,0.7,0.8 and 0.9 are used in this analysis and the best value is 0.9.Scenario 3 with LPSP,COE,NPC,TGE and RF of 0.003%,0.15913$/kWh,46953.0485$,2.3406 kg/year and 99.8%respectively when using GWOCS is found to be the most appropriate for the Community multimedia center.The optimal Scenario is obtained for a system comprising of 18 kW of P_(pv-rated)corresponding to 69 solar panels,3 days of AD corresponding to a total battery capacity of 241 kWh and 1 of N_(dg).
文摘Some types of renewable energy have been experiencing rapid evolution in recent decades, notably among the energies associated with the oceans, such as wave and current energies. The development of new energy conversion technologies for these two forms of energy has been offering a large number of equipment configurations and plant geometries for energy conversion. This process can be implemented aiming at the result of feasibility studies in places with energy potentials, establishing minimum feasibility limits to be reached. This work aims to contribute in this sense with a feasibility study of a system with ocean wave power plants and with socio-current power plants to be operated on the southern coast of Brazil. This study evaluates a hybrid system with contributions from energy supplies obtained from wave plants and current plants, connected to the grid and supplying the demand of the municipalities in the North Coast region of the State of Rio Grande do Sul, the southernmost state of Brazil. The study was carried out with simulations with the Homer Legacy software, with some adaptations for the simulation of ocean wave plants and ocean current plants. The results indicate that the ocean wave power plants were viable in the vast majority of simulated scenarios, while the ocean current power plants were viable in the scenarios with more intense average ocean current speeds and with more expensive energy acquired from the interconnected system.
文摘The differential pricing for peak hours encourages industrial consumers to look for independent power supplies for the period from 19 to 22 hours. This paper presents a study to identify the optimal solution for a recycled paper mill that also intends to work in that period. The factory is located in Rio Grande do Sul, in southern Brazil, and considers the use of a diesel gen set, a micro hydro power plant and possibly PV modules. Two micro hydro power plants were considered in the study, an old plant to be renewed and another to be fully implemented. The software Homer was used as a tool to determine the most feasible combination of components considered in the study. The sale of surplus power to the energy system appears as a key to viability of alternatives that are not based solely on diesel generators. The optimal solution consists of a combination of diesel generators and micro hydro power plant, in one case, and only on hydroelectric power plant in another, with a significant penetration of PV modules if its cost is reduced to 12% of the current price, selling an amount of energy equal to that which is bought. The annual water availability in one of the sites requires diesel supplement, while the other, more abundant, this supplement is not necessary.
