The increasing penetration of second-life battery energy storage systems(SLBESS)in power grids presents substantial challenges to system operation and control due to the heterogeneous characteristics and uncertain deg...The increasing penetration of second-life battery energy storage systems(SLBESS)in power grids presents substantial challenges to system operation and control due to the heterogeneous characteristics and uncertain degradation patterns of repurposed batteries.This paper presents a novel model-free adaptive voltage controlembedded dung beetle-inspired heuristic optimization algorithmfor optimal SLBESS capacity configuration and power dispatch.To simultaneously address the computational complexity and ensure system stability,this paper develops a comprehensive bilevel optimization framework.At the upper level,a dung beetle optimization algorithmdetermines the optimal SLBESS capacity configuration byminimizing total lifecycle costswhile incorporating the charging/discharging power trajectories derived from the model-free adaptive voltage control strategy.At the lower level,a health-priority power dispatch optimization model intelligently allocates power demands among heterogeneous battery groups based on their real-time operational states,state-of-health variations,and degradation constraints.The proposed model-free approach circumvents the need for complex battery charging/discharging power controlmodels and extensive historical data requirements whilemaintaining system stability through adaptive controlmechanisms.A novel cycle life degradation model is developed to quantify the relationship between remaining useful life,depth of discharge,and operational patterns.The integrated framework enables simultaneous strategic planning and operational control,ensuring both economic efficiency and extended battery lifespan.The effectiveness of the proposed method is validated through comprehensive case studies on hybrid energy storage systems,demonstrating superior computational efficiency,robust performance across different network configurations,and significant improvements in battery utilization compared to conventional approaches.展开更多
In high-renewable-energy power systems,the demand for fast-responding capabilities is growing.To address the limitations of conventional closed-loop frequency control,where the integral coefficient cannot dynamically ...In high-renewable-energy power systems,the demand for fast-responding capabilities is growing.To address the limitations of conventional closed-loop frequency control,where the integral coefficient cannot dynamically adjust the frequency regulation command based on the state of charge(SoC)of energy storage units,this paper proposes a secondary frequency regulation control strategy based on variable integral coefficients for multiple energy storage units.First,a power-uniform controller is designed to ensure that thermal power units gradually take on more regulation power during the frequency regulation process.Next,a control framework based on variable integral coefficients is proposed within the secondary frequency regulation model,along with an objective function that simultaneously considers both Automatic Generation Control(AGC)command tracking performance and SoC recovery requirements of energy storage units.Finally,a gradient descent optimization method is used to dynamically adjust the gain of the energy storage integral controller,allowingmultiple energy storage units to respond in real-time to AGC instructions and SoC variations.Simulation results confirmthe effectiveness of the proposedmethod.Compared to traditional strategies,the proposed approach takes into account the SoCdiscrepancies amongmultiple energy storage units and the duration of system net power imbalances.It successfully implements secondary frequency regulation while achieving dynamic power allocation among the units.展开更多
The increasing penetration of renewable energy into power grids is reducing the regulation capacity of automatic generation control(AGC).Thus,there is an urgent demand to coordinate AGC units with active equipment suc...The increasing penetration of renewable energy into power grids is reducing the regulation capacity of automatic generation control(AGC).Thus,there is an urgent demand to coordinate AGC units with active equipment such as energy storage.Current dispatch decision-making methods often ignore the intermittent effects of renewable energy.This paper proposes a two-stage robust optimization model in which energy storage is used to compensate for the intermittency of renewable energy for the dispatch of AGC units.This model exploits the rapid adjustment capability of energy storage to compensate for the slow response speed of AGC units,improve the adjustment potential,and respond to the problems of intermittent power generation from renewable energy.A column and constraint generation algorithm is used to solve the model.In an example analysis,the proposed model was more robust than a model that did not consider energy storage at eliminating the effects of intermittency while offering clear improvements in economy and efficiency.展开更多
Building emission reduction is an important way to achieve China’s carbon peaking and carbon neutrality goals.Aiming at the problem of low carbon economic operation of a photovoltaic energy storage building system,a ...Building emission reduction is an important way to achieve China’s carbon peaking and carbon neutrality goals.Aiming at the problem of low carbon economic operation of a photovoltaic energy storage building system,a multi-time scale optimal scheduling strategy based on model predictive control(MPC)is proposed under the consideration of load optimization.First,load optimization is achieved by controlling the charging time of electric vehicles as well as adjusting the air conditioning operation temperature,and the photovoltaic energy storage building system model is constructed to propose a day-ahead scheduling strategy with the lowest daily operation cost.Second,considering inter-day to intra-day source-load prediction error,an intraday rolling optimal scheduling strategy based on MPC is proposed that dynamically corrects the day-ahead dispatch results to stabilize system power fluctuations and promote photovoltaic consumption.Finally,taking an office building on a summer work day as an example,the effectiveness of the proposed scheduling strategy is verified.The results of the example show that the strategy reduces the total operating cost of the photovoltaic energy storage building system by 17.11%,improves the carbon emission reduction by 7.99%,and the photovoltaic consumption rate reaches 98.57%,improving the system’s low-carbon and economic performance.展开更多
Due to the characteristics of intermittent photovoltaic power generation and power fluctuations in distributed photovoltaic power generation,photovoltaic grid-connected systems are usually equipped with energy storage...Due to the characteristics of intermittent photovoltaic power generation and power fluctuations in distributed photovoltaic power generation,photovoltaic grid-connected systems are usually equipped with energy storage units.Most of the structures combined with energy storage are used as the DC side.At the same time,virtual synchronous generators have been widely used in distributed power generation due to their inertial damping and frequency and voltage regulation.For the PV-storage grid-connected system based on virtual synchronous generators,the existing control strategy has unclear function allocation,fluctuations in photovoltaic inverter output power,and high requirements for coordinated control of PV arrays,energy storage units,and photovoltaic inverters,which make the control strategy more complicated.In order to solve the above problems,a control strategy for PV-storage grid-connected system based on a virtual synchronous generator is proposed.In this strategy,the energy storage unit implements maximum power point tracking,and the photovoltaic inverter implements a virtual synchronous generator algorithm,so that the functions implemented by each part of the system are clear,which reduces the requirements for coordinated control.At the same time,the smooth power command is used to suppress the fluctuation of the output power of the photovoltaic inverter.The simulation validates the effectiveness of the proposed method from three aspects:grid-connected operating conditions,frequency-modulated operating conditions,and illumination sudden-drop operating condition.Compared with the existing control strategies,the proposed method simplifies the control strategies and stabilizes the photovoltaic inverter fluctuation in the output power of the inverter.展开更多
Facing the economic challenges of significant frequency regulation wear and tear on thermal power units and short energy storage lifespan in thermal-energy storage combined systems participating in grid primary freque...Facing the economic challenges of significant frequency regulation wear and tear on thermal power units and short energy storage lifespan in thermal-energy storage combined systems participating in grid primary frequency regulation(PFR),this paper proposes a novel hybrid energy storage system(HESS)control strategy based on Newton-Raphson optimization algorithm(NRBO)-VMD and a fuzzy neural network(FNN)for PFR.In the primary power allocation stage,the high inertia and slow response of thermal power units prevent them from promptly responding to the high-frequency components of PFR signals,leading to increased mechanical stress.To address the distinct response characteristics of thermal units and HESS,an NRBO-VMD based decomposition method for PFR signals is proposed,enabling a flexible system response to grid frequency deviations.Within the HESS,an adaptive coordinated control strategy and a State of Charge(SOC)self-recovery strategy are introduced.These strategies autonomously adjust the virtual inertia and droop coefficients based on the depth of frequency regulation and the real-time SOC.Furthermore,a FNN is constructed to perform secondary refinement of the internal power distribution within the HESS.Finally,simulations under various operational conditions demonstrate that the proposed strategy effectively mitigates frequent power adjustments of the thermal unit during PFR,adaptively achieves optimal power decomposition and distribution,maintains the flywheel energy storage’s SOC within an optimal range,and ensures the long-term stable operation of the HESS.展开更多
Building energy analyses using forecasting optimization strategies are commonly used for predicting TES （thermal energy storage） system performance. These strategies produce perfect optimized cost savings and are no...Building energy analyses using forecasting optimization strategies are commonly used for predicting TES （thermal energy storage） system performance. These strategies produce perfect optimized cost savings and are not typically realized in the real world, unless a safety factor is applied. Rather than show how to improve the industry＇s ability to accurately model and simulate a true TES system design, this paper will show advanced building information strategies and energy management simulation techniques required to truly achieve the ideal optimized cost savings, determined from the TES energy simulation analysis. This paper uses the hospitality industry as a case study, showing the application of simulation and analytical modeling for an optimized partial TES system. As a result building energy managers can make better decisions through the entire building life cycle from the earliest concept model through operation and maintenance.展开更多
Increasing renewable energy penetration into integrated community energy systems(ICESs)requires more efficient methods to prevent power fluctuations of the tie–line(connection of the ICESs to the main grid).In this p...Increasing renewable energy penetration into integrated community energy systems(ICESs)requires more efficient methods to prevent power fluctuations of the tie–line(connection of the ICESs to the main grid).In this paper,centrally-controlled air conditioners are considered as a virtual energy storage system(VESS).The optimal thermostat regulation is used to manage the charging/discharging power of the VESS within the customer comfort level range and the virtual state of charge(VSOC)is used to describe the charging/discharging power of the VESS.On this basis,the model of the hybrid energy storage system is built with a VESS and a battery storage system(BSS).Then,an optimal coordination control strategy(OCCS)for a hybrid energy storage system is developed considering the state-space equation to describe the OCCS,the constraints of the OCCS,and the objective function to express the optimal coordination control performance.Finally,the influence of the outdoor temperature and the deadband of air conditioners on the results of the OCCS is analyzed.Results show that the OCCS can realize optimal allocation of the storage response amount to trace the reference target accurately and guarantee both the state of charge(SOC)of the batteries in a reasonable range to prolong the battery life and ensure the level of comfort experienced by users.展开更多
Mobilized energy storage(MES)can provide a variety of services for power systems,including peak shaving,frequency regulation,and congestion alleviation.In this paper,we develop an MES sharing approach based on tempora...Mobilized energy storage(MES)can provide a variety of services for power systems,including peak shaving,frequency regulation,and congestion alleviation.In this paper,we develop an MES sharing approach based on temporal-spatial network(TSN)toward systemwide temporal-spatial flexibility enhancement,specifically in which the heavy-duty vehicles can exchange batteries at the energy storage stations connected with power grids.To achieve the temporal-spatial coordination of transportation and power systems,we propose a coordinated scheduling model.A decentralized algorithm based on the improved optimality condition decomposition(OCD)algorithm is proposed to address the information asymmetry between transportation and power systems while enhancing computational efficiency.Case studies based on IEEE 30-/118-bus and transportation systems demonstrate that MESs using the proposed approach can significantly improve the utilization of batteries while reducing operating costs by over 40%compared with stationary energy storages(SESs).展开更多
Centralized delivery has become the main operation mode under the scaled development of wind power.Transmission channels are usually the guarantee of out-delivered wind power for large-scale wind base.The configuratio...Centralized delivery has become the main operation mode under the scaled development of wind power.Transmission channels are usually the guarantee of out-delivered wind power for large-scale wind base.The configuration of transmission capacity,which has the features of low utilization and poor economy,is hardly matching correctly due to the volatility and low energy density of wind.The usage of energy storage can mitigate wind power fluctuations and reduce the requirement of out-delivery transmission capacity,but facing the issue of energy storage cost recovery.Therefore,it is necessary to optimize the allocation of energy storage while considering the problem of wind power transmission.This paper studies the joint optimization of large-scale wind power transmission capacity and energy storage,reveals the mechanism of energy storage in order to reduce the power fluctuation of wind power base and slow down the demand of transmission.Then,analyze the multi-functional cost-sharing mode of energy storage,improve the efficiency of energy storage cost recovery.Constructs the coordination optimization configuration model to deal with the problem of large-scale wind power transmission capacity and energy storage,and realizes the transmission capacity optimization coordination and optimization with energy storage.The proposed method is verified by a wind base located in Northeast China.展开更多
An autonomous microgrid that runs on renewable energy sources is presented in this article.It has a supercon-ducting magnetic energy storage(SMES)device,wind energy-producing devices,and an energy storage battery.Howe...An autonomous microgrid that runs on renewable energy sources is presented in this article.It has a supercon-ducting magnetic energy storage(SMES)device,wind energy-producing devices,and an energy storage battery.However,because such microgrids are nonlinear and the energy they create varies with time,controlling and managing the energy inside them is a difficult issue.Fractional-order proportional integral(FOPI)controller is recommended for the current research to enhance a standalone microgrid’s energy management and performance.The suggested dedicated control for the SMES comprises two loops:the outer loop,which uses the FOPI to regulate the DC-link voltage,and the inner loop,responsible for regulating the SMES current,is constructed using the intelligent FOPI(iFOPI).The FOPI+iFOPI parameters are best developed using the dandelion optimizer(DO)approach to achieve the optimum performance.The suggested FOPI+iFOPI controller’s performance is contrasted with a conventional PI controller for variations in wind speed and microgrid load.The optimal FOPI+iFOPI controller manages the voltage and frequency of the load.The behavior of the microgrid as a reaction to step changes in load and wind speed was measured using the proposed controller.MATLAB simulations were used to evaluate the recommended system’s performance.The results of the simulations showed that throughout all interruptions,the recommended microgrid provided the load with AC power with a constant amplitude and frequency.In addition,the required load demand was accurately reduced.Furthermore,the microgrid functioned incredibly well despite SMES and varying wind speeds.Results obtained under identical conditions were compared with and without the best FOPI+iFOPI controller.When utilizing the optimal FOPI+iFOPI controller with SMES,it was found that the microgrid performed better than the microgrid without SMES.展开更多
Energy storage with virtual inertia and virtual droop control has attracted wide attention due to its improved frequency stability with high penetration of renewable energy sources.However,there are significant spatia...Energy storage with virtual inertia and virtual droop control has attracted wide attention due to its improved frequency stability with high penetration of renewable energy sources.However,there are significant spatial differences in frequency response.The location and capacity of energy storage are urgent issues to be resolved to support frequency.This study addresses the minimum investment of hybrid energy storage systems for providing sufficient frequency support,including the power capacity,energy capacity,and location of energy storage.A frequency response model is developed taking into account the network structure and frequency spatial distribution characteristics.In addition,a numerical computation method is provided for determining the frequency dynamic indices and calculating the output power of energy storage.Based on a simplified frequency response model,an optimal hybrid energy storage configuration method is proposed to optimize the control parameters,location,and capacity to satisfy the frequency dynamic constraints.This configuration method can exploit the potential of energy storage with different rates in different frequency support stages.To address the nonconvex drawback of this configuration,a numerical calculation method is provided based on the explicit gradient of the frequency and energy storage indices to enhance the computational efficiency.Simulations of a two-area system and the south-east Australian system verify the effectiveness of the proposed hybrid energy storage configuration method.展开更多
More and more attention has been paid to the high penetration of renewable energy in recent years.The randomness and intermittency of solar and wind energy make it an inevitable trend that renewables are coupled with ...More and more attention has been paid to the high penetration of renewable energy in recent years.The randomness and intermittency of solar and wind energy make it an inevitable trend that renewables are coupled with energy storage technologies.Pumped hydro storage(PHS)is the most widelyused storage form in the power grid but the capacity is limited by geographic conditions.The concentrated solar power(CSP)plant with a thermal energy storage(TES)system can realize easier grid connections and effective peak shaving.Therefore,this paper proposes a solar-wind-hydro hybrid power system with PHS-TES double energy storages,and investigates the optimal coordinated operational strategy and multi-objective sizing.The optimal sizing problem which considers the minimum levelized cost of energy(LCOE)and loss of power supply probability(LPSP)as objectives is solved by multi-objective particle swarm optimization.Moreover,the seasonal uncertainties of renewables are considered by applying a scenario-based analysis using Kmeans clustering.Finally,a case study reveals the effectiveness of the coordinated operational strategy and double energy storages from the perspectives of economy and reliability.The comparisons of optimal sizing results show that the PV-WindCSP-PHS system decreases the LCOE by 19.1%compared to a PV-Wind-CSP system under the same LPSP,and reduces the LPSP compared to PV-Wind-PHS systems with limited reservoir capacity,which indicates that the proposed system with double energy storages has better economy and reliability performance compared to single storage.展开更多
This study proposes a novel fully distributed coordination control(DCC) strategy to coordinate charging efficiencies of energy storage systems(ESSs). To realize this fully DCC strategy in an active distribution system...This study proposes a novel fully distributed coordination control(DCC) strategy to coordinate charging efficiencies of energy storage systems(ESSs). To realize this fully DCC strategy in an active distribution system(ADS) with high penetration of intermittent renewable generation, a two-layer consensus algorithm is proposed and applied. It collects global information in the first layer and achieves pinning-based DCC in the second layer. Basic objectives of the proposed DCC for ESSs are: à to coordinate the ESSs and improve efficiency using associated marginal charging costs(MCCs) in a fully distributed manner; ` to reduce local power mismatch and power transmission losses; ′ to adapt to unintentional communication topology changes. The effectiveness and adaptability of the proposed DCC approach are both validated by simulation results.展开更多
With more and more distributed photovoltaic(PV)plants access to the distribution system,whose structure is changing and becoming an active network.The traditional methods of voltage regulation may hardly adapt to this...With more and more distributed photovoltaic(PV)plants access to the distribution system,whose structure is changing and becoming an active network.The traditional methods of voltage regulation may hardly adapt to this new situation.To address this problem,this paper presents a coordinated control method of distributed energy storage systems(DESSs)for voltage regulation in a distribution network.The influence of the voltage caused by the PV plant is analyzed in a simple distribution feeder at first.The voltage regulation areas corresponding to DESSs are divided by calculating and comparing the voltage sensitivity matrix.Then,a coordinated voltage control strategy is proposed for the DESSs.Finally,the simulation results of the IEEE 33-bus radial distribution network verify the effectiveness of the proposed coordinated control method.展开更多
5G基站、分布式光伏(distributed photovoltaic,DPV)等分布式资源大规模参与配电网经济与电能质量等多目标优化调度,致使配电网调控模型决策变量复杂、求解时间慢等问题凸显。为此,提出一种考虑5G基站调控潜力和多资源协同的配电网分层...5G基站、分布式光伏(distributed photovoltaic,DPV)等分布式资源大规模参与配电网经济与电能质量等多目标优化调度,致使配电网调控模型决策变量复杂、求解时间慢等问题凸显。为此,提出一种考虑5G基站调控潜力和多资源协同的配电网分层分区优化方法。首先,考虑5G基站通信流量波动特性,建立计及闲置荷电状态(state of charge,SOC)约束的5G基站调控潜力模型。基于此,再建立配电网分层分区优化模型。上层以配电网综合效益最优为目标进行集中式调度,从而确定配电网分组投切电容器组、静止无功发生器等自身资源的动作方案。下层为分区调度,结合电压-功率灵敏度和考虑5G基站通信负荷的源荷不匹配度指标进行配电网物理分区,建立面向5G基站闲置SOC和DPV剩余容量的配电网分区协调优化模型,并采用二阶锥规划和同步型交替方向乘子法相结合的混合算法进行求解。最后,以改进的IEEE33节点配电网为算例,分析验证了所提方法的有效性。结果表明,所提方法能够提高配电网调控模型的求解能力,并提升配电网经济性和电压质量。展开更多
基金Financial support was provided by the State Grid Sichuan Electric Power Company Science and Technology Project“Key Research on Development Path Planning and Key Operation Technologies of New Rural Electrification Construction”under Grant No.52199623000G.
文摘The increasing penetration of second-life battery energy storage systems(SLBESS)in power grids presents substantial challenges to system operation and control due to the heterogeneous characteristics and uncertain degradation patterns of repurposed batteries.This paper presents a novel model-free adaptive voltage controlembedded dung beetle-inspired heuristic optimization algorithmfor optimal SLBESS capacity configuration and power dispatch.To simultaneously address the computational complexity and ensure system stability,this paper develops a comprehensive bilevel optimization framework.At the upper level,a dung beetle optimization algorithmdetermines the optimal SLBESS capacity configuration byminimizing total lifecycle costswhile incorporating the charging/discharging power trajectories derived from the model-free adaptive voltage control strategy.At the lower level,a health-priority power dispatch optimization model intelligently allocates power demands among heterogeneous battery groups based on their real-time operational states,state-of-health variations,and degradation constraints.The proposed model-free approach circumvents the need for complex battery charging/discharging power controlmodels and extensive historical data requirements whilemaintaining system stability through adaptive controlmechanisms.A novel cycle life degradation model is developed to quantify the relationship between remaining useful life,depth of discharge,and operational patterns.The integrated framework enables simultaneous strategic planning and operational control,ensuring both economic efficiency and extended battery lifespan.The effectiveness of the proposed method is validated through comprehensive case studies on hybrid energy storage systems,demonstrating superior computational efficiency,robust performance across different network configurations,and significant improvements in battery utilization compared to conventional approaches.
文摘In high-renewable-energy power systems,the demand for fast-responding capabilities is growing.To address the limitations of conventional closed-loop frequency control,where the integral coefficient cannot dynamically adjust the frequency regulation command based on the state of charge(SoC)of energy storage units,this paper proposes a secondary frequency regulation control strategy based on variable integral coefficients for multiple energy storage units.First,a power-uniform controller is designed to ensure that thermal power units gradually take on more regulation power during the frequency regulation process.Next,a control framework based on variable integral coefficients is proposed within the secondary frequency regulation model,along with an objective function that simultaneously considers both Automatic Generation Control(AGC)command tracking performance and SoC recovery requirements of energy storage units.Finally,a gradient descent optimization method is used to dynamically adjust the gain of the energy storage integral controller,allowingmultiple energy storage units to respond in real-time to AGC instructions and SoC variations.Simulation results confirmthe effectiveness of the proposedmethod.Compared to traditional strategies,the proposed approach takes into account the SoCdiscrepancies amongmultiple energy storage units and the duration of system net power imbalances.It successfully implements secondary frequency regulation while achieving dynamic power allocation among the units.
基金supported by Theoretical study of power system synergistic dispatch National Science Foundation of China(51477091).
文摘The increasing penetration of renewable energy into power grids is reducing the regulation capacity of automatic generation control(AGC).Thus,there is an urgent demand to coordinate AGC units with active equipment such as energy storage.Current dispatch decision-making methods often ignore the intermittent effects of renewable energy.This paper proposes a two-stage robust optimization model in which energy storage is used to compensate for the intermittency of renewable energy for the dispatch of AGC units.This model exploits the rapid adjustment capability of energy storage to compensate for the slow response speed of AGC units,improve the adjustment potential,and respond to the problems of intermittent power generation from renewable energy.A column and constraint generation algorithm is used to solve the model.In an example analysis,the proposed model was more robust than a model that did not consider energy storage at eliminating the effects of intermittency while offering clear improvements in economy and efficiency.
文摘Building emission reduction is an important way to achieve China’s carbon peaking and carbon neutrality goals.Aiming at the problem of low carbon economic operation of a photovoltaic energy storage building system,a multi-time scale optimal scheduling strategy based on model predictive control(MPC)is proposed under the consideration of load optimization.First,load optimization is achieved by controlling the charging time of electric vehicles as well as adjusting the air conditioning operation temperature,and the photovoltaic energy storage building system model is constructed to propose a day-ahead scheduling strategy with the lowest daily operation cost.Second,considering inter-day to intra-day source-load prediction error,an intraday rolling optimal scheduling strategy based on MPC is proposed that dynamically corrects the day-ahead dispatch results to stabilize system power fluctuations and promote photovoltaic consumption.Finally,taking an office building on a summer work day as an example,the effectiveness of the proposed scheduling strategy is verified.The results of the example show that the strategy reduces the total operating cost of the photovoltaic energy storage building system by 17.11%,improves the carbon emission reduction by 7.99%,and the photovoltaic consumption rate reaches 98.57%,improving the system’s low-carbon and economic performance.
基金supported by National Natural Science Foundation of China Key program(51937003)。
文摘Due to the characteristics of intermittent photovoltaic power generation and power fluctuations in distributed photovoltaic power generation,photovoltaic grid-connected systems are usually equipped with energy storage units.Most of the structures combined with energy storage are used as the DC side.At the same time,virtual synchronous generators have been widely used in distributed power generation due to their inertial damping and frequency and voltage regulation.For the PV-storage grid-connected system based on virtual synchronous generators,the existing control strategy has unclear function allocation,fluctuations in photovoltaic inverter output power,and high requirements for coordinated control of PV arrays,energy storage units,and photovoltaic inverters,which make the control strategy more complicated.In order to solve the above problems,a control strategy for PV-storage grid-connected system based on a virtual synchronous generator is proposed.In this strategy,the energy storage unit implements maximum power point tracking,and the photovoltaic inverter implements a virtual synchronous generator algorithm,so that the functions implemented by each part of the system are clear,which reduces the requirements for coordinated control.At the same time,the smooth power command is used to suppress the fluctuation of the output power of the photovoltaic inverter.The simulation validates the effectiveness of the proposed method from three aspects:grid-connected operating conditions,frequency-modulated operating conditions,and illumination sudden-drop operating condition.Compared with the existing control strategies,the proposed method simplifies the control strategies and stabilizes the photovoltaic inverter fluctuation in the output power of the inverter.
基金supported by the Lanzhou Science and Technology Plan Project(XM1753694781389).
文摘Facing the economic challenges of significant frequency regulation wear and tear on thermal power units and short energy storage lifespan in thermal-energy storage combined systems participating in grid primary frequency regulation(PFR),this paper proposes a novel hybrid energy storage system(HESS)control strategy based on Newton-Raphson optimization algorithm(NRBO)-VMD and a fuzzy neural network(FNN)for PFR.In the primary power allocation stage,the high inertia and slow response of thermal power units prevent them from promptly responding to the high-frequency components of PFR signals,leading to increased mechanical stress.To address the distinct response characteristics of thermal units and HESS,an NRBO-VMD based decomposition method for PFR signals is proposed,enabling a flexible system response to grid frequency deviations.Within the HESS,an adaptive coordinated control strategy and a State of Charge(SOC)self-recovery strategy are introduced.These strategies autonomously adjust the virtual inertia and droop coefficients based on the depth of frequency regulation and the real-time SOC.Furthermore,a FNN is constructed to perform secondary refinement of the internal power distribution within the HESS.Finally,simulations under various operational conditions demonstrate that the proposed strategy effectively mitigates frequent power adjustments of the thermal unit during PFR,adaptively achieves optimal power decomposition and distribution,maintains the flywheel energy storage’s SOC within an optimal range,and ensures the long-term stable operation of the HESS.
文摘Building energy analyses using forecasting optimization strategies are commonly used for predicting TES （thermal energy storage） system performance. These strategies produce perfect optimized cost savings and are not typically realized in the real world, unless a safety factor is applied. Rather than show how to improve the industry＇s ability to accurately model and simulate a true TES system design, this paper will show advanced building information strategies and energy management simulation techniques required to truly achieve the ideal optimized cost savings, determined from the TES energy simulation analysis. This paper uses the hospitality industry as a case study, showing the application of simulation and analytical modeling for an optimized partial TES system. As a result building energy managers can make better decisions through the entire building life cycle from the earliest concept model through operation and maintenance.
基金This work was supported by a project of State Grid Corporation of China(No.SGTJDK00KJJS1600035).
文摘Increasing renewable energy penetration into integrated community energy systems(ICESs)requires more efficient methods to prevent power fluctuations of the tie–line(connection of the ICESs to the main grid).In this paper,centrally-controlled air conditioners are considered as a virtual energy storage system(VESS).The optimal thermostat regulation is used to manage the charging/discharging power of the VESS within the customer comfort level range and the virtual state of charge(VSOC)is used to describe the charging/discharging power of the VESS.On this basis,the model of the hybrid energy storage system is built with a VESS and a battery storage system(BSS).Then,an optimal coordination control strategy(OCCS)for a hybrid energy storage system is developed considering the state-space equation to describe the OCCS,the constraints of the OCCS,and the objective function to express the optimal coordination control performance.Finally,the influence of the outdoor temperature and the deadband of air conditioners on the results of the OCCS is analyzed.Results show that the OCCS can realize optimal allocation of the storage response amount to trace the reference target accurately and guarantee both the state of charge(SOC)of the batteries in a reasonable range to prolong the battery life and ensure the level of comfort experienced by users.
基金supported by National Natural Science Foundation of China(No.52277092)Chinese Association of Science and Technology Young Elite Scientists Sponsorship Program(No.YESS20210227).
文摘Mobilized energy storage(MES)can provide a variety of services for power systems,including peak shaving,frequency regulation,and congestion alleviation.In this paper,we develop an MES sharing approach based on temporal-spatial network(TSN)toward systemwide temporal-spatial flexibility enhancement,specifically in which the heavy-duty vehicles can exchange batteries at the energy storage stations connected with power grids.To achieve the temporal-spatial coordination of transportation and power systems,we propose a coordinated scheduling model.A decentralized algorithm based on the improved optimality condition decomposition(OCD)algorithm is proposed to address the information asymmetry between transportation and power systems while enhancing computational efficiency.Case studies based on IEEE 30-/118-bus and transportation systems demonstrate that MESs using the proposed approach can significantly improve the utilization of batteries while reducing operating costs by over 40%compared with stationary energy storages(SESs).
基金supported by the National Key Research and Development Program(2016YFB0900100)。
文摘Centralized delivery has become the main operation mode under the scaled development of wind power.Transmission channels are usually the guarantee of out-delivered wind power for large-scale wind base.The configuration of transmission capacity,which has the features of low utilization and poor economy,is hardly matching correctly due to the volatility and low energy density of wind.The usage of energy storage can mitigate wind power fluctuations and reduce the requirement of out-delivery transmission capacity,but facing the issue of energy storage cost recovery.Therefore,it is necessary to optimize the allocation of energy storage while considering the problem of wind power transmission.This paper studies the joint optimization of large-scale wind power transmission capacity and energy storage,reveals the mechanism of energy storage in order to reduce the power fluctuation of wind power base and slow down the demand of transmission.Then,analyze the multi-functional cost-sharing mode of energy storage,improve the efficiency of energy storage cost recovery.Constructs the coordination optimization configuration model to deal with the problem of large-scale wind power transmission capacity and energy storage,and realizes the transmission capacity optimization coordination and optimization with energy storage.The proposed method is verified by a wind base located in Northeast China.
基金This research was funded by the Deputyship for Research and Innovation,Ministry of Education,Saudi Arabia,through the University of Tabuk,Grant Number S-1443-0123.
文摘An autonomous microgrid that runs on renewable energy sources is presented in this article.It has a supercon-ducting magnetic energy storage(SMES)device,wind energy-producing devices,and an energy storage battery.However,because such microgrids are nonlinear and the energy they create varies with time,controlling and managing the energy inside them is a difficult issue.Fractional-order proportional integral(FOPI)controller is recommended for the current research to enhance a standalone microgrid’s energy management and performance.The suggested dedicated control for the SMES comprises two loops:the outer loop,which uses the FOPI to regulate the DC-link voltage,and the inner loop,responsible for regulating the SMES current,is constructed using the intelligent FOPI(iFOPI).The FOPI+iFOPI parameters are best developed using the dandelion optimizer(DO)approach to achieve the optimum performance.The suggested FOPI+iFOPI controller’s performance is contrasted with a conventional PI controller for variations in wind speed and microgrid load.The optimal FOPI+iFOPI controller manages the voltage and frequency of the load.The behavior of the microgrid as a reaction to step changes in load and wind speed was measured using the proposed controller.MATLAB simulations were used to evaluate the recommended system’s performance.The results of the simulations showed that throughout all interruptions,the recommended microgrid provided the load with AC power with a constant amplitude and frequency.In addition,the required load demand was accurately reduced.Furthermore,the microgrid functioned incredibly well despite SMES and varying wind speeds.Results obtained under identical conditions were compared with and without the best FOPI+iFOPI controller.When utilizing the optimal FOPI+iFOPI controller with SMES,it was found that the microgrid performed better than the microgrid without SMES.
基金supported by the National Key Research and Development Program(No.2023YFB2406600)the National Natural Science Foundation of China(No.U22A6007 and No.52222703).
文摘Energy storage with virtual inertia and virtual droop control has attracted wide attention due to its improved frequency stability with high penetration of renewable energy sources.However,there are significant spatial differences in frequency response.The location and capacity of energy storage are urgent issues to be resolved to support frequency.This study addresses the minimum investment of hybrid energy storage systems for providing sufficient frequency support,including the power capacity,energy capacity,and location of energy storage.A frequency response model is developed taking into account the network structure and frequency spatial distribution characteristics.In addition,a numerical computation method is provided for determining the frequency dynamic indices and calculating the output power of energy storage.Based on a simplified frequency response model,an optimal hybrid energy storage configuration method is proposed to optimize the control parameters,location,and capacity to satisfy the frequency dynamic constraints.This configuration method can exploit the potential of energy storage with different rates in different frequency support stages.To address the nonconvex drawback of this configuration,a numerical calculation method is provided based on the explicit gradient of the frequency and energy storage indices to enhance the computational efficiency.Simulations of a two-area system and the south-east Australian system verify the effectiveness of the proposed hybrid energy storage configuration method.
基金the National Key Research and Development Program of China 2018YFE0128500the Fundamental Research Funds for the Central Universities of China under Grant B210202069.
文摘More and more attention has been paid to the high penetration of renewable energy in recent years.The randomness and intermittency of solar and wind energy make it an inevitable trend that renewables are coupled with energy storage technologies.Pumped hydro storage(PHS)is the most widelyused storage form in the power grid but the capacity is limited by geographic conditions.The concentrated solar power(CSP)plant with a thermal energy storage(TES)system can realize easier grid connections and effective peak shaving.Therefore,this paper proposes a solar-wind-hydro hybrid power system with PHS-TES double energy storages,and investigates the optimal coordinated operational strategy and multi-objective sizing.The optimal sizing problem which considers the minimum levelized cost of energy(LCOE)and loss of power supply probability(LPSP)as objectives is solved by multi-objective particle swarm optimization.Moreover,the seasonal uncertainties of renewables are considered by applying a scenario-based analysis using Kmeans clustering.Finally,a case study reveals the effectiveness of the coordinated operational strategy and double energy storages from the perspectives of economy and reliability.The comparisons of optimal sizing results show that the PV-WindCSP-PHS system decreases the LCOE by 19.1%compared to a PV-Wind-CSP system under the same LPSP,and reduces the LPSP compared to PV-Wind-PHS systems with limited reservoir capacity,which indicates that the proposed system with double energy storages has better economy and reliability performance compared to single storage.
基金supported by National Key R&D Program of China(No.2017YFB0902803)National Natural Science Foundation of China(No.51477029)+1 种基金Natural Science Foundation of Jiangsu Province(No.BK20160674)State Grid Corporation of China(No.SGTYHT/14-JS-188)
文摘This study proposes a novel fully distributed coordination control(DCC) strategy to coordinate charging efficiencies of energy storage systems(ESSs). To realize this fully DCC strategy in an active distribution system(ADS) with high penetration of intermittent renewable generation, a two-layer consensus algorithm is proposed and applied. It collects global information in the first layer and achieves pinning-based DCC in the second layer. Basic objectives of the proposed DCC for ESSs are: à to coordinate the ESSs and improve efficiency using associated marginal charging costs(MCCs) in a fully distributed manner; ` to reduce local power mismatch and power transmission losses; ′ to adapt to unintentional communication topology changes. The effectiveness and adaptability of the proposed DCC approach are both validated by simulation results.
基金This paper is supported by The National Key Research and Development Plan,Energy Storage Technology of 10MW Level Redox Battery,2017YFB0903504。
文摘With more and more distributed photovoltaic(PV)plants access to the distribution system,whose structure is changing and becoming an active network.The traditional methods of voltage regulation may hardly adapt to this new situation.To address this problem,this paper presents a coordinated control method of distributed energy storage systems(DESSs)for voltage regulation in a distribution network.The influence of the voltage caused by the PV plant is analyzed in a simple distribution feeder at first.The voltage regulation areas corresponding to DESSs are divided by calculating and comparing the voltage sensitivity matrix.Then,a coordinated voltage control strategy is proposed for the DESSs.Finally,the simulation results of the IEEE 33-bus radial distribution network verify the effectiveness of the proposed coordinated control method.
文摘5G基站、分布式光伏(distributed photovoltaic,DPV)等分布式资源大规模参与配电网经济与电能质量等多目标优化调度,致使配电网调控模型决策变量复杂、求解时间慢等问题凸显。为此,提出一种考虑5G基站调控潜力和多资源协同的配电网分层分区优化方法。首先,考虑5G基站通信流量波动特性,建立计及闲置荷电状态(state of charge,SOC)约束的5G基站调控潜力模型。基于此,再建立配电网分层分区优化模型。上层以配电网综合效益最优为目标进行集中式调度,从而确定配电网分组投切电容器组、静止无功发生器等自身资源的动作方案。下层为分区调度,结合电压-功率灵敏度和考虑5G基站通信负荷的源荷不匹配度指标进行配电网物理分区,建立面向5G基站闲置SOC和DPV剩余容量的配电网分区协调优化模型,并采用二阶锥规划和同步型交替方向乘子法相结合的混合算法进行求解。最后,以改进的IEEE33节点配电网为算例,分析验证了所提方法的有效性。结果表明,所提方法能够提高配电网调控模型的求解能力,并提升配电网经济性和电压质量。
