Theauthor proposes a dual layer source grid load storage collaborative planning model based on Benders decomposition to optimize the low-carbon and economic performance of the distribution network.The model plans the ...Theauthor proposes a dual layer source grid load storage collaborative planning model based on Benders decomposition to optimize the low-carbon and economic performance of the distribution network.The model plans the configuration of photovoltaic(3.8 MW),wind power(2.5 MW),energy storage(2.2 MWh),and SVC(1.2 Mvar)through interaction between upper and lower layers,and modifies lines 2–3,8–9,etc.to improve transmission capacity and voltage stability.The author uses normal distribution and Monte Carlo method to model load uncertainty,and combines Weibull distribution to describe wind speed characteristics.Compared to the traditional three-layer model(TLM),Benders decomposition-based two-layer model(BLBD)has a 58.1%reduction in convergence time(5.36 vs.12.78 h),a 51.1%reduction in iteration times(23 vs.47 times),a 8.07%reduction in total cost(12.436 vs.13.528 million yuan),and a 9.62%reduction in carbon emissions(12,456 vs.13,782 t).After optimization,the peak valley difference decreased from4.1 to 2.9MW,the renewable energy consumption rate reached 93.4%,and the energy storage efficiency was 87.6%.Themodel has been validated in the IEEE 33 node system,demonstrating its superiority in terms of economy,low-carbon,and reliability.展开更多
Traditional seawater desalination requires high amounts of energy, with correspondingly high costs and limited benefits, hindering wider applications of the process. To further improve the comprehensive economic benef...Traditional seawater desalination requires high amounts of energy, with correspondingly high costs and limited benefits, hindering wider applications of the process. To further improve the comprehensive economic benefits of seawater desalination, the desalination load can be combined with renewable energy sources such as solar energy, wind energy, and ocean energy or with the power grid to ensure its effective regulation. Utilizing energy internet(EI) technology, energy balance demand of the regional power grid, and coordinated control between coastal multi-source multi-load and regional distribution network with desalination load is reviewed herein. Several key technologies, including coordinated control of coastal multi-source multi-load system with seawater desalination load, flexible interaction between seawater desalination and regional distribution network, and combined control of coastal multi-source multi-load storage system with seawater desalination load, are discussed in detail. Adoption of the flexible interaction between seawater desalination and regional distribution networks is beneficial for solving water resource problems, improving the ability to dissipate distributed renewable energy, balancing and increasing grid loads, improving the safety and economy of coastal power grids, and achieving coordinated and comprehensive application of power grids, renewable energy sources, and coastal loads.展开更多
Recent economic growth and development have considerably raised energy consumption over the globe.Electric load prediction approaches become essential for effective planning,decision-making,and contract evaluation of ...Recent economic growth and development have considerably raised energy consumption over the globe.Electric load prediction approaches become essential for effective planning,decision-making,and contract evaluation of the power systems.In order to achieve effective forecasting outcomes with minimumcomputation time,this study develops an improved whale optimization with deep learning enabled load prediction(IWO-DLELP)scheme for energy storage systems(ESS)in smart grid platform.The major intention of the IWO-DLELP technique is to effectually forecast the electric load in SG environment for designing proficient ESS.The proposed IWO-DLELP model initially undergoes pre-processing in two stages namely min-max normalization and feature selection.Besides,partition clustering approach is applied for the decomposition of data into distinct clusters with respect to distance and objective functions.Moreover,IWO with bidirectional gated recurrent unit(BiGRU)model is applied for the prediction of load and the hyperparameters are tuned by the use of IWO algorithm.The experiment analysis reported the enhanced results of the IWO-DLELP model over the recent methods interms of distinct evaluation measures.展开更多
In this paper,the installation of energy storage systems(EES)and their role in grid peak load shaving in two echelons,their distribution and generation are investigated.First,the optimal placement and capacity of the ...In this paper,the installation of energy storage systems(EES)and their role in grid peak load shaving in two echelons,their distribution and generation are investigated.First,the optimal placement and capacity of the energy storage is taken into consideration,then,the charge-discharge strategy for this equipment is determined.Here,Genetic Algorithm(GA)and Particle Swarm Optimization(PSO)are used to calculate the minimum and maximum load in the network with the presence of energy storage systems.The energy storage systems were utilized in a distribution system with the aid of a peak load shaving approach.Ultimately,the battery charge-discharge is managed at any time during the day,considering the load consumption at each hour.The results depict that the load curve reached a constant state by managing charge-discharge with no significant changes.This shows the significance of such matters in terms of economy and technicality.展开更多
Microgrids are local power systems that may or may not be connected to the distribution system and are typically controlled by the local operator.Interest in microgrids is rising and it is likely that the number of mi...Microgrids are local power systems that may or may not be connected to the distribution system and are typically controlled by the local operator.Interest in microgrids is rising and it is likely that the number of microgrids connected to distribution networks will increase.Currently,there is no consensus on how microgrids will interact with the distribution system―they have the potential to threaten stability,or to assist.However microgrids,with their emphasis on sophisticated control in order to manage their particular challenges,address many of the problems that will be required to overcome in realizing the smart grid.This paper examines some of the issues involved in connecting microgrids to the distribution networks,and illustrates how microgrids have a key role to play in the development of the smart grid.展开更多
With the rapid development of electrical power systems in recent years,microgrids(MGs)have become increasingly prevalent.MGs improve network efficiency and reduce operating costs and emissions because of the integrati...With the rapid development of electrical power systems in recent years,microgrids(MGs)have become increasingly prevalent.MGs improve network efficiency and reduce operating costs and emissions because of the integration of distributed renewable energy sources(RESs),energy storage,and source-load management systems.Despite these advances,the decentralized architecture of MGs impacts the functioning patterns of the entire system,including control strategy,energy management philosophy,and protection scheme.In this context,developing a convenient protection strategy for MGs is challenging because of various obstacles,such as the significant variance in short-circuit values under different operating modes,two-way power flow,asynchronous reclosing,protection blinding,sympathetic tripping,and loss of coordination.In light of these challenges,this paper reviews prior research on proposed protection schemes for AC-MGs to thoroughly evaluate network protection’s potential issues.The paper also provides a comprehensive overview of the MG structure and the associated protection challenges,solutions,real applications,and future trends.展开更多
https://www.sciencedirect.com/journal/energy-and-buildings/vol/354/suppl/C Volume 354,1 March 2026[OA](1)Rule-based peak shaving strategy with battery storage:Evaluating socio-economic impacts in regional grids by Md ...https://www.sciencedirect.com/journal/energy-and-buildings/vol/354/suppl/C Volume 354,1 March 2026[OA](1)Rule-based peak shaving strategy with battery storage:Evaluating socio-economic impacts in regional grids by Md Masud Rana,Huadong Mo,Mohd Fakhizan Romlie,et al,Article 116983 Abstract:The Australian electricity framework includes several demand tariff structures,with peak demand charges constituting a significant cost component for consumers.Efficient peak load shaving techniques can mitigate these charges,leading to substantial economic benefits to the power suppliers,consumers,and society.展开更多
With high penetration of renewable energy sources(RESs)in modern power systems,system frequency becomes more prone to fluctuation as RESs do not naturally have inertial properties.A conventional energy storage system(...With high penetration of renewable energy sources(RESs)in modern power systems,system frequency becomes more prone to fluctuation as RESs do not naturally have inertial properties.A conventional energy storage system(ESS)based on a battery has been used to tackle the shortage in system inertia but has low and short-term power support during the disturbance.To address the issues,this paper proposes a new synthetic inertia control(SIC)design with a superconducting magnetic energy storage(SMES)system to mimic the necessary inertia power and damping properties in a short time and thereby regulate the microgrid(µG)frequency during disturbances.In addition,system frequency deviation is reduced by employing the proportional-integral(PI)controller with the proposed SIC system.The efficacy of the proposed SIC system is validated by comparison with the conventional ESS and SMES systems without using the PI controller,under various load/renewable perturbations,nonlinearities,and uncertainties.The simulation results highlight that the proposed system with SMES can efficiently manage several disturbances and high system uncertainty compared to the conventional ESS and SMES systems,without using the PI controller.展开更多
With rapidly growing of Renewable Energy Sources(RESs)in renewable power systems,several disturbances influence on the power systems such as;lack of system inertia that results from replacing the synchronous generator...With rapidly growing of Renewable Energy Sources(RESs)in renewable power systems,several disturbances influence on the power systems such as;lack of system inertia that results from replacing the synchronous generators with RESs and frequency/voltage fluctuations that resulting from the intermittent nature of the RESs.Hence,the modern power systems become more susceptible to the system instability than conventional power systems.Therefore,in this study,a new application of Superconducting Magnetic Energy Storage(SMES)(i.e.,auxiliary Load Frequency Control(LFC))has been integrated with the secondary frequency control(i.e.,LFC)for frequency stability enhancement of the Egyptian Power System(EPS)due to high RESs penetration.Where,the coordinated control strategy is based on the PI controller that is optimally designed by the Particle Swarm Optimization(PSO)algorithm to minimize the frequency deviations of the EPS.The EPS includes both conventional generation units(i.e.,non-reheat,reheat and hydraulic power plants)with inherent nonlinearities,and RESs(i.e.,wind and solar energy).System modelling and simulation results are carried out using Matlab/Simulink^(■)software.The simulation results reveal the robustness of the proposed coordinated control strategy to preserve the system stability of the EPS with high penetration of RESs for different contingencies.展开更多
This paper presents the concept of controlling distributed electric loads with thermal energy storage as a passive electric energy storage system(PEESS).Examples of such loads include different types of thermostatical...This paper presents the concept of controlling distributed electric loads with thermal energy storage as a passive electric energy storage system(PEESS).Examples of such loads include different types of thermostatically controlled appliances(TCAs)such as hot water heaters,air conditioners,and refrigerators.Each TCA can be viewed as a thermal cell that stores electricity as thermal energy.A centralized control mechanism can be used to control the timing of each thermal cell to consume electric energy so that the aggregated electricity consumption of the thermal cells will vary against a baseline consumption.Thus,when the aggregated consumption is higher than the baseline,the PEESS is charging;otherwise,the PEESS is discharging.The overall performance of a PEESS will be equivalent to that of a battery energy storage device.This paper presents the configuration and formulates the control of a PEESS.The modeling results demonstrate the feasibility of implementing the PEESS.展开更多
加快建设沙戈荒源网荷储一体化基地有力推动了电力系统低碳转型,但基地内缺乏常规电源,呈现出电网弱、低惯量、弱阻尼等特征。高压大功率变流器是主力电源型新能源场站的关键电气装备,起到自主构建电压/频率,提供阻尼和惯量支撑等作用...加快建设沙戈荒源网荷储一体化基地有力推动了电力系统低碳转型,但基地内缺乏常规电源,呈现出电网弱、低惯量、弱阻尼等特征。高压大功率变流器是主力电源型新能源场站的关键电气装备,起到自主构建电压/频率,提供阻尼和惯量支撑等作用。在此背景下,首先介绍了源网荷储一体化基地变流拓扑及汇集方式,对“多机并联-多级升压”汇集拓扑所引发的宽频振荡、协同构网控制困难以及过载能力弱等问题进行了分析。其次,分别对光伏发电系统、蓄电池储能系统(battery energy storage system,BESS)以及光储一体化系统的高压大功率变流拓扑特点进行了梳理和分析。最后,探索了高压大功率变流器亟待解决的关键问题。展开更多
新型电力系统建设背景下,新能源渗透率不断提高造成电力系统灵活性需求剧增。针对电力系统灵活性供需失衡问题,提出含碳捕集电厂的源荷储资源数据驱动鲁棒优化调度模型。首先,基于碳捕集电厂、抽水蓄能等源荷储灵活性资源运行特性,刻画...新型电力系统建设背景下,新能源渗透率不断提高造成电力系统灵活性需求剧增。针对电力系统灵活性供需失衡问题,提出含碳捕集电厂的源荷储资源数据驱动鲁棒优化调度模型。首先,基于碳捕集电厂、抽水蓄能等源荷储灵活性资源运行特性,刻画电力系统灵活性供给能力;其次,采用数据驱动方法构建椭球不确定性集以刻画风电、光伏波动区间,根据各时刻边界值量化灵活性需求;进而,结合灵活性供需关系,提出源荷储资源数据驱动鲁棒优化模型,并采用改进列与约束生成算法(column and constraint generation,C&CG)进行求解。算例仿真表明,通过协同调度源荷储灵活性资源有助于支撑电力系统功率平衡,提高灵活性裕度,数据驱动鲁棒优化方法能够剔除传统盒式不确定集中的不实际恶劣场景,进而改善传统鲁棒优化模型过于保守的问题,并显著提升计算效率。展开更多
文摘Theauthor proposes a dual layer source grid load storage collaborative planning model based on Benders decomposition to optimize the low-carbon and economic performance of the distribution network.The model plans the configuration of photovoltaic(3.8 MW),wind power(2.5 MW),energy storage(2.2 MWh),and SVC(1.2 Mvar)through interaction between upper and lower layers,and modifies lines 2–3,8–9,etc.to improve transmission capacity and voltage stability.The author uses normal distribution and Monte Carlo method to model load uncertainty,and combines Weibull distribution to describe wind speed characteristics.Compared to the traditional three-layer model(TLM),Benders decomposition-based two-layer model(BLBD)has a 58.1%reduction in convergence time(5.36 vs.12.78 h),a 51.1%reduction in iteration times(23 vs.47 times),a 8.07%reduction in total cost(12.436 vs.13.528 million yuan),and a 9.62%reduction in carbon emissions(12,456 vs.13,782 t).After optimization,the peak valley difference decreased from4.1 to 2.9MW,the renewable energy consumption rate reached 93.4%,and the energy storage efficiency was 87.6%.Themodel has been validated in the IEEE 33 node system,demonstrating its superiority in terms of economy,low-carbon,and reliability.
基金supported by the State Grid Science and Technology Project, “Study on Multi-source and Multiload Coordination and Optimization Technology Considering Desalination of Sea Water” (No. SGTJDK00DWJS1800011)
文摘Traditional seawater desalination requires high amounts of energy, with correspondingly high costs and limited benefits, hindering wider applications of the process. To further improve the comprehensive economic benefits of seawater desalination, the desalination load can be combined with renewable energy sources such as solar energy, wind energy, and ocean energy or with the power grid to ensure its effective regulation. Utilizing energy internet(EI) technology, energy balance demand of the regional power grid, and coordinated control between coastal multi-source multi-load and regional distribution network with desalination load is reviewed herein. Several key technologies, including coordinated control of coastal multi-source multi-load system with seawater desalination load, flexible interaction between seawater desalination and regional distribution network, and combined control of coastal multi-source multi-load storage system with seawater desalination load, are discussed in detail. Adoption of the flexible interaction between seawater desalination and regional distribution networks is beneficial for solving water resource problems, improving the ability to dissipate distributed renewable energy, balancing and increasing grid loads, improving the safety and economy of coastal power grids, and achieving coordinated and comprehensive application of power grids, renewable energy sources, and coastal loads.
文摘Recent economic growth and development have considerably raised energy consumption over the globe.Electric load prediction approaches become essential for effective planning,decision-making,and contract evaluation of the power systems.In order to achieve effective forecasting outcomes with minimumcomputation time,this study develops an improved whale optimization with deep learning enabled load prediction(IWO-DLELP)scheme for energy storage systems(ESS)in smart grid platform.The major intention of the IWO-DLELP technique is to effectually forecast the electric load in SG environment for designing proficient ESS.The proposed IWO-DLELP model initially undergoes pre-processing in two stages namely min-max normalization and feature selection.Besides,partition clustering approach is applied for the decomposition of data into distinct clusters with respect to distance and objective functions.Moreover,IWO with bidirectional gated recurrent unit(BiGRU)model is applied for the prediction of load and the hyperparameters are tuned by the use of IWO algorithm.The experiment analysis reported the enhanced results of the IWO-DLELP model over the recent methods interms of distinct evaluation measures.
基金supported in part by an International Research Partnership“Electrical Engineering-Thai French Research Center(EE-TFRC)”under the project framework of the Lorraine Universitéd’Excellence(LUE)in cooperation between Universitéde Lorraine and King Mongkut’s University of Technology North Bangkok and in part by the National Research Council of Thailand(NRCT)under Senior Research Scholar Program under Grant No.N42A640328.
文摘In this paper,the installation of energy storage systems(EES)and their role in grid peak load shaving in two echelons,their distribution and generation are investigated.First,the optimal placement and capacity of the energy storage is taken into consideration,then,the charge-discharge strategy for this equipment is determined.Here,Genetic Algorithm(GA)and Particle Swarm Optimization(PSO)are used to calculate the minimum and maximum load in the network with the presence of energy storage systems.The energy storage systems were utilized in a distribution system with the aid of a peak load shaving approach.Ultimately,the battery charge-discharge is managed at any time during the day,considering the load consumption at each hour.The results depict that the load curve reached a constant state by managing charge-discharge with no significant changes.This shows the significance of such matters in terms of economy and technicality.
基金supported by the Australian Department of Environment,Water, Heritage and the Arts under Grant No. RDG 08-29
文摘Microgrids are local power systems that may or may not be connected to the distribution system and are typically controlled by the local operator.Interest in microgrids is rising and it is likely that the number of microgrids connected to distribution networks will increase.Currently,there is no consensus on how microgrids will interact with the distribution system―they have the potential to threaten stability,or to assist.However microgrids,with their emphasis on sophisticated control in order to manage their particular challenges,address many of the problems that will be required to overcome in realizing the smart grid.This paper examines some of the issues involved in connecting microgrids to the distribution networks,and illustrates how microgrids have a key role to play in the development of the smart grid.
文摘With the rapid development of electrical power systems in recent years,microgrids(MGs)have become increasingly prevalent.MGs improve network efficiency and reduce operating costs and emissions because of the integration of distributed renewable energy sources(RESs),energy storage,and source-load management systems.Despite these advances,the decentralized architecture of MGs impacts the functioning patterns of the entire system,including control strategy,energy management philosophy,and protection scheme.In this context,developing a convenient protection strategy for MGs is challenging because of various obstacles,such as the significant variance in short-circuit values under different operating modes,two-way power flow,asynchronous reclosing,protection blinding,sympathetic tripping,and loss of coordination.In light of these challenges,this paper reviews prior research on proposed protection schemes for AC-MGs to thoroughly evaluate network protection’s potential issues.The paper also provides a comprehensive overview of the MG structure and the associated protection challenges,solutions,real applications,and future trends.
文摘https://www.sciencedirect.com/journal/energy-and-buildings/vol/354/suppl/C Volume 354,1 March 2026[OA](1)Rule-based peak shaving strategy with battery storage:Evaluating socio-economic impacts in regional grids by Md Masud Rana,Huadong Mo,Mohd Fakhizan Romlie,et al,Article 116983 Abstract:The Australian electricity framework includes several demand tariff structures,with peak demand charges constituting a significant cost component for consumers.Efficient peak load shaving techniques can mitigate these charges,leading to substantial economic benefits to the power suppliers,consumers,and society.
文摘With high penetration of renewable energy sources(RESs)in modern power systems,system frequency becomes more prone to fluctuation as RESs do not naturally have inertial properties.A conventional energy storage system(ESS)based on a battery has been used to tackle the shortage in system inertia but has low and short-term power support during the disturbance.To address the issues,this paper proposes a new synthetic inertia control(SIC)design with a superconducting magnetic energy storage(SMES)system to mimic the necessary inertia power and damping properties in a short time and thereby regulate the microgrid(µG)frequency during disturbances.In addition,system frequency deviation is reduced by employing the proportional-integral(PI)controller with the proposed SIC system.The efficacy of the proposed SIC system is validated by comparison with the conventional ESS and SMES systems without using the PI controller,under various load/renewable perturbations,nonlinearities,and uncertainties.The simulation results highlight that the proposed system with SMES can efficiently manage several disturbances and high system uncertainty compared to the conventional ESS and SMES systems,without using the PI controller.
基金This paper was funded by the Cultural Affairs and Missions Sector of the Egyptian Ministry of Higher Education.
文摘With rapidly growing of Renewable Energy Sources(RESs)in renewable power systems,several disturbances influence on the power systems such as;lack of system inertia that results from replacing the synchronous generators with RESs and frequency/voltage fluctuations that resulting from the intermittent nature of the RESs.Hence,the modern power systems become more susceptible to the system instability than conventional power systems.Therefore,in this study,a new application of Superconducting Magnetic Energy Storage(SMES)(i.e.,auxiliary Load Frequency Control(LFC))has been integrated with the secondary frequency control(i.e.,LFC)for frequency stability enhancement of the Egyptian Power System(EPS)due to high RESs penetration.Where,the coordinated control strategy is based on the PI controller that is optimally designed by the Particle Swarm Optimization(PSO)algorithm to minimize the frequency deviations of the EPS.The EPS includes both conventional generation units(i.e.,non-reheat,reheat and hydraulic power plants)with inherent nonlinearities,and RESs(i.e.,wind and solar energy).System modelling and simulation results are carried out using Matlab/Simulink^(■)software.The simulation results reveal the robustness of the proposed coordinated control strategy to preserve the system stability of the EPS with high penetration of RESs for different contingencies.
文摘This paper presents the concept of controlling distributed electric loads with thermal energy storage as a passive electric energy storage system(PEESS).Examples of such loads include different types of thermostatically controlled appliances(TCAs)such as hot water heaters,air conditioners,and refrigerators.Each TCA can be viewed as a thermal cell that stores electricity as thermal energy.A centralized control mechanism can be used to control the timing of each thermal cell to consume electric energy so that the aggregated electricity consumption of the thermal cells will vary against a baseline consumption.Thus,when the aggregated consumption is higher than the baseline,the PEESS is charging;otherwise,the PEESS is discharging.The overall performance of a PEESS will be equivalent to that of a battery energy storage device.This paper presents the configuration and formulates the control of a PEESS.The modeling results demonstrate the feasibility of implementing the PEESS.
文摘加快建设沙戈荒源网荷储一体化基地有力推动了电力系统低碳转型,但基地内缺乏常规电源,呈现出电网弱、低惯量、弱阻尼等特征。高压大功率变流器是主力电源型新能源场站的关键电气装备,起到自主构建电压/频率,提供阻尼和惯量支撑等作用。在此背景下,首先介绍了源网荷储一体化基地变流拓扑及汇集方式,对“多机并联-多级升压”汇集拓扑所引发的宽频振荡、协同构网控制困难以及过载能力弱等问题进行了分析。其次,分别对光伏发电系统、蓄电池储能系统(battery energy storage system,BESS)以及光储一体化系统的高压大功率变流拓扑特点进行了梳理和分析。最后,探索了高压大功率变流器亟待解决的关键问题。
文摘新型电力系统建设背景下,新能源渗透率不断提高造成电力系统灵活性需求剧增。针对电力系统灵活性供需失衡问题,提出含碳捕集电厂的源荷储资源数据驱动鲁棒优化调度模型。首先,基于碳捕集电厂、抽水蓄能等源荷储灵活性资源运行特性,刻画电力系统灵活性供给能力;其次,采用数据驱动方法构建椭球不确定性集以刻画风电、光伏波动区间,根据各时刻边界值量化灵活性需求;进而,结合灵活性供需关系,提出源荷储资源数据驱动鲁棒优化模型,并采用改进列与约束生成算法(column and constraint generation,C&CG)进行求解。算例仿真表明,通过协同调度源荷储灵活性资源有助于支撑电力系统功率平衡,提高灵活性裕度,数据驱动鲁棒优化方法能够剔除传统盒式不确定集中的不实际恶劣场景,进而改善传统鲁棒优化模型过于保守的问题,并显著提升计算效率。
