Essentially, it is significant to supply the consumer with reliable and sufficient power. Since, power quality is measured by the consistency in frequency and power flow between control areas. Thus, in a power system ...Essentially, it is significant to supply the consumer with reliable and sufficient power. Since, power quality is measured by the consistency in frequency and power flow between control areas. Thus, in a power system operation and control,automatic generation control(AGC) plays a crucial role. In this paper, multi-area(Five areas: area 1, area 2, area 3, area 4 and area 5) reheat thermal power systems are considered with proportional-integral-derivative(PID) controller as a supplementary controller. Each area in the investigated power system is equipped with appropriate governor unit, turbine with reheater unit, generator and speed regulator unit. The PID controller parameters are optimized by considering nature bio-inspired firefly algorithm(FFA). The experimental results demonstrated the comparison of the proposed system performance(FFA-PID)with optimized PID controller based genetic algorithm(GAPID) and particle swarm optimization(PSO) technique(PSOPID) for the same investigated power system. The results proved the efficiency of employing the integral time absolute error(ITAE) cost function with one percent step load perturbation(1 % SLP) in area 1. The proposed system based FFA achieved the least settling time compared to using the GA or the PSO algorithms, while, it attained good results with respect to the peak overshoot/undershoot. In addition, the FFA performance is improved with the increased number of iterations which outperformed the other optimization algorithms based controller.展开更多
Present day power scenarios demand a high quality uninterrupted power supply and needs environmental issues to be addressed. Both concerns can be dealt with by the introduction of the renewable sources to the existing...Present day power scenarios demand a high quality uninterrupted power supply and needs environmental issues to be addressed. Both concerns can be dealt with by the introduction of the renewable sources to the existing power system. Thus, automatic generation control(AGC) with diverse renewable sources and a modified-cascaded controller are presented in the paper.Also, a new hybrid scheme of the improved teaching learning based optimization-differential evolution(hITLBO-DE) algorithm is applied for providing optimization of controller parameters. A study of the system with a technique such as TLBO applied to a proportional integral derivative(PID), integral double derivative(IDD) and PIDD is compared to hITLBO-DE tuned cascaded controller with dynamic load change.The suggested methodology has been extensively applied to a 2-area system with a diverse source power system with various operation time non-linearities such as dead-band of, generation rate constraint and reheat thermal units. The multi-area system with reheat thermal plants, hydel plants and a unit of a wind-diesel combination is tested with the cascaded controller scheme with a different controller setting for each area. The variation of the load is taken within 1% to 5% of the connected load and robustness analysis is shown by modifying essential factors simultaneously by± 30%. Finally, the proposed scheme of controller and optimization technique is also tested with a 5-equal area thermal system with non-linearities. The simulation results demonstrate the superiority of the proposed controller and algorithm under a dynamically changing load.展开更多
The microgrid is a typical cyber-physical microgrid system(CPMS). The physical unconventional distributed generators(DGs) are intermittent and inverter-interfaced which makes them very different to control. The cyber ...The microgrid is a typical cyber-physical microgrid system(CPMS). The physical unconventional distributed generators(DGs) are intermittent and inverter-interfaced which makes them very different to control. The cyber components,such as the embedded computer and communication network,are equipped with DGs, to process and transmit the necessary information for the controllers. In order to ensure system-wide observability, controllability and stabilization for the microgrid,the cyber and physical component need to be integrated. For the physical component of CPMS, the droop-control method is popular as it can be applied in both modes of operation to improve the grid transient performance. Traditional droop control methods have the drawback of the inherent trade-off between power sharing and voltage and frequency regulation. In this paper, the global information(such as the average voltage and the output active power of the microgrid and so on) are acquired distributedly based on multi-agent system(MAS). Based on the global information from cyber components of CPMS, automatic generation control(AGC) and automatic voltage control(AVC)are proposed to deal with the drawback of traditional droop control. Simulation studies in PSCAD demonstrate the effectiveness of the proposed control methods.展开更多
As synchronous generators(SGs)are gradually displaced by renewable energy sources(RESs),the frequency stability of power systems deteriorates because RESs,represented by utility-scale solar and wind power sources,do n...As synchronous generators(SGs)are gradually displaced by renewable energy sources(RESs),the frequency stability of power systems deteriorates because RESs,represented by utility-scale solar and wind power sources,do not provide the inertial response,primary frequency response,secondary frequency response,and tertiary frequency regulation.As a result,the remaining SGs may not be sufficient to maintain the power balance and frequency stability.The concept and control strategies of virtual synchronous generators(VSGs)enable the inverter-based wind and solar power sources to emulate the outer characteristics of traditional SGs and participate in the active power and frequency control of power systems.This paper focuses on the automatic generation control(AGC)with virtual synchronous renewables(VSRs).First,the VSR strategy that enables the RESs to participate in AGC is introduced.Second,based on the interval representation of uncertainty,the output of RES is transformed into two portions,i.e.,the dispatchable portion and the stochastic portion.In the dispatchable portion,the RESs can participate in AGC jointly with SGs.Accordingly,a security-constrained economic dispatch(SCED)model is built considering the RESs operating in VSR mode.Third,the solution strategy that employs the slack variables to acquire deterministic constraints is introduced.Finally,the proposed SCED model is solved based on the 6-bus and 39-bus systems.The results show that,compared with the maximum power point tracking(MPPT)mode,VSRs can participate in the active power and frequency control jointly with SGs,increase the maximum penetration level of RESs,and decrease the operating cost.展开更多
Communication plays a vital role in incorporating smartness into the interconnected power system.However,historical records prove that the data transfer has always been vulnerable to cyber-attacks.Unless these cyber-a...Communication plays a vital role in incorporating smartness into the interconnected power system.However,historical records prove that the data transfer has always been vulnerable to cyber-attacks.Unless these cyber-attacks are identified and cordoned off,they may lead to black-out and result in national security issues.This paper proposes an optimal two-stage Kalman filter(OTS-KF)for simultaneous state and cyber-attack estimation in automatic generation control(AGC)system.Biases/cyber-attacks are modeled as unknown inputs in the AGC dynamics.Five types of cyber-attacks,i.e.,false data injection(FDI),data replay attack,denial of service(DoS),scaling,and ramp attacks,are injected into the measurements and estimated using OTS-KF.As the load variations of each area are seldom available,OTS-KF is reformulated to estimate the states and outliers along with the load variations of the system.The proposed technique is validated on the benchmark two-area,three-area,and five-area power system models.The simulation results under various test conditions demonstrate the efficacy of the proposed filter.展开更多
Particle swarm optimization(PSO)is one of the popular stochastic optimization based on swarm intelligence algorithm.This simple and promising algorithm has applications in many research fields.In PSO,each particle can...Particle swarm optimization(PSO)is one of the popular stochastic optimization based on swarm intelligence algorithm.This simple and promising algorithm has applications in many research fields.In PSO,each particle can adjust its‘flying’according to its own flying experience and its companions’flying experience.This paper proposes a new PSO variant,called the statistically tracked PSO,which uses group statistical characteristics to update the velocity of the particle after certain iterations,thus avoiding localminima and helping particles to explore global optimum with an improved convergence.The performance of the proposed algorithm is tested on a deregulated automatic generation control problem in power systems and encouraging results are obtained.展开更多
A big step forward to improve power system monitoring and performance, continued load growth without a corresponding increase in transmission resources has resulted in reduced operational margins for many power system...A big step forward to improve power system monitoring and performance, continued load growth without a corresponding increase in transmission resources has resulted in reduced operational margins for many power systems worldwide and has led to operation of power systems closer to their stability limits and to power exchange in new patterns. These issues, as well as the on-going worldwide trend towards deregulation of the entire industry on the one hand and the increased need for accurate and better network monitoring on the other hand, force power utilities exposed to this pressure to demand new solutions for wide area monitoring, protection and control. Wide-area monitoring, protection, and control require communicating the specific-node information to a remote station but all information should be time synchronized so that to neutralize the time difference between information. It gives a complete simultaneous snap shot of the power system. The conventional system is not able to satisfy the time-synchronized requirement of power system. Phasor Measurement Unit (PMU) is enabler of time-synchronized measurement, it communicate the synchronized local information to remote station.展开更多
根据机组响应控制指令时间长短不同,提出一种多时间尺度协调的区域控制偏差(area control error,ACE)超前控制方法。首先分析了现有ACE超前控制方法的不足,给出目标时刻控制区理想总发电的预测模型;然后分析了计划机组计划与执行的关系...根据机组响应控制指令时间长短不同,提出一种多时间尺度协调的区域控制偏差(area control error,ACE)超前控制方法。首先分析了现有ACE超前控制方法的不足,给出目标时刻控制区理想总发电的预测模型;然后分析了计划机组计划与执行的关系,提出计划机组出力偏差的预估方法;进而综合考虑总发电、计划机组发电和自动发电控制(auto generation control,AGC)机组的希望运行点,计算出目标时刻协调AGC机组的希望总出力;最后,通过一个优化模型把协调AGC机组的希望总出力分配到各协调AGC机组上。文章所提方法已在四川电网投入现场试运行,结果证明了该方法的可行性。展开更多
文摘Essentially, it is significant to supply the consumer with reliable and sufficient power. Since, power quality is measured by the consistency in frequency and power flow between control areas. Thus, in a power system operation and control,automatic generation control(AGC) plays a crucial role. In this paper, multi-area(Five areas: area 1, area 2, area 3, area 4 and area 5) reheat thermal power systems are considered with proportional-integral-derivative(PID) controller as a supplementary controller. Each area in the investigated power system is equipped with appropriate governor unit, turbine with reheater unit, generator and speed regulator unit. The PID controller parameters are optimized by considering nature bio-inspired firefly algorithm(FFA). The experimental results demonstrated the comparison of the proposed system performance(FFA-PID)with optimized PID controller based genetic algorithm(GAPID) and particle swarm optimization(PSO) technique(PSOPID) for the same investigated power system. The results proved the efficiency of employing the integral time absolute error(ITAE) cost function with one percent step load perturbation(1 % SLP) in area 1. The proposed system based FFA achieved the least settling time compared to using the GA or the PSO algorithms, while, it attained good results with respect to the peak overshoot/undershoot. In addition, the FFA performance is improved with the increased number of iterations which outperformed the other optimization algorithms based controller.
文摘Present day power scenarios demand a high quality uninterrupted power supply and needs environmental issues to be addressed. Both concerns can be dealt with by the introduction of the renewable sources to the existing power system. Thus, automatic generation control(AGC) with diverse renewable sources and a modified-cascaded controller are presented in the paper.Also, a new hybrid scheme of the improved teaching learning based optimization-differential evolution(hITLBO-DE) algorithm is applied for providing optimization of controller parameters. A study of the system with a technique such as TLBO applied to a proportional integral derivative(PID), integral double derivative(IDD) and PIDD is compared to hITLBO-DE tuned cascaded controller with dynamic load change.The suggested methodology has been extensively applied to a 2-area system with a diverse source power system with various operation time non-linearities such as dead-band of, generation rate constraint and reheat thermal units. The multi-area system with reheat thermal plants, hydel plants and a unit of a wind-diesel combination is tested with the cascaded controller scheme with a different controller setting for each area. The variation of the load is taken within 1% to 5% of the connected load and robustness analysis is shown by modifying essential factors simultaneously by± 30%. Finally, the proposed scheme of controller and optimization technique is also tested with a 5-equal area thermal system with non-linearities. The simulation results demonstrate the superiority of the proposed controller and algorithm under a dynamically changing load.
基金supported by National Natural Science Foundation of China(61100159,61233007,61503371)National High Technology Research and Development Program of China(863 Program)(2011AA040103)+2 种基金Foundation of Chinese Academy of Sciences(KGCX2-EW-104)the Strategic Priority Research Program of the Chinese Academy of Sciences(XDA06021100)the Cross-disciplinary Collaborative Teams Program for Science,Technology,and Innovation of Chinese Academy of Sciences-Network and System Technologies for Security Monitoring and Information Interaction in Smart Grid,Energy Management System for Micro-smart Grid
文摘The microgrid is a typical cyber-physical microgrid system(CPMS). The physical unconventional distributed generators(DGs) are intermittent and inverter-interfaced which makes them very different to control. The cyber components,such as the embedded computer and communication network,are equipped with DGs, to process and transmit the necessary information for the controllers. In order to ensure system-wide observability, controllability and stabilization for the microgrid,the cyber and physical component need to be integrated. For the physical component of CPMS, the droop-control method is popular as it can be applied in both modes of operation to improve the grid transient performance. Traditional droop control methods have the drawback of the inherent trade-off between power sharing and voltage and frequency regulation. In this paper, the global information(such as the average voltage and the output active power of the microgrid and so on) are acquired distributedly based on multi-agent system(MAS). Based on the global information from cyber components of CPMS, automatic generation control(AGC) and automatic voltage control(AVC)are proposed to deal with the drawback of traditional droop control. Simulation studies in PSCAD demonstrate the effectiveness of the proposed control methods.
基金supported by the Research and Application of Key Technologies of Flexible Power Supply System Under Various Emergency Scenarios(No.5442PD210001)。
文摘As synchronous generators(SGs)are gradually displaced by renewable energy sources(RESs),the frequency stability of power systems deteriorates because RESs,represented by utility-scale solar and wind power sources,do not provide the inertial response,primary frequency response,secondary frequency response,and tertiary frequency regulation.As a result,the remaining SGs may not be sufficient to maintain the power balance and frequency stability.The concept and control strategies of virtual synchronous generators(VSGs)enable the inverter-based wind and solar power sources to emulate the outer characteristics of traditional SGs and participate in the active power and frequency control of power systems.This paper focuses on the automatic generation control(AGC)with virtual synchronous renewables(VSRs).First,the VSR strategy that enables the RESs to participate in AGC is introduced.Second,based on the interval representation of uncertainty,the output of RES is transformed into two portions,i.e.,the dispatchable portion and the stochastic portion.In the dispatchable portion,the RESs can participate in AGC jointly with SGs.Accordingly,a security-constrained economic dispatch(SCED)model is built considering the RESs operating in VSR mode.Third,the solution strategy that employs the slack variables to acquire deterministic constraints is introduced.Finally,the proposed SCED model is solved based on the 6-bus and 39-bus systems.The results show that,compared with the maximum power point tracking(MPPT)mode,VSRs can participate in the active power and frequency control jointly with SGs,increase the maximum penetration level of RESs,and decrease the operating cost.
文摘Communication plays a vital role in incorporating smartness into the interconnected power system.However,historical records prove that the data transfer has always been vulnerable to cyber-attacks.Unless these cyber-attacks are identified and cordoned off,they may lead to black-out and result in national security issues.This paper proposes an optimal two-stage Kalman filter(OTS-KF)for simultaneous state and cyber-attack estimation in automatic generation control(AGC)system.Biases/cyber-attacks are modeled as unknown inputs in the AGC dynamics.Five types of cyber-attacks,i.e.,false data injection(FDI),data replay attack,denial of service(DoS),scaling,and ramp attacks,are injected into the measurements and estimated using OTS-KF.As the load variations of each area are seldom available,OTS-KF is reformulated to estimate the states and outliers along with the load variations of the system.The proposed technique is validated on the benchmark two-area,three-area,and five-area power system models.The simulation results under various test conditions demonstrate the efficacy of the proposed filter.
文摘Particle swarm optimization(PSO)is one of the popular stochastic optimization based on swarm intelligence algorithm.This simple and promising algorithm has applications in many research fields.In PSO,each particle can adjust its‘flying’according to its own flying experience and its companions’flying experience.This paper proposes a new PSO variant,called the statistically tracked PSO,which uses group statistical characteristics to update the velocity of the particle after certain iterations,thus avoiding localminima and helping particles to explore global optimum with an improved convergence.The performance of the proposed algorithm is tested on a deregulated automatic generation control problem in power systems and encouraging results are obtained.
文摘A big step forward to improve power system monitoring and performance, continued load growth without a corresponding increase in transmission resources has resulted in reduced operational margins for many power systems worldwide and has led to operation of power systems closer to their stability limits and to power exchange in new patterns. These issues, as well as the on-going worldwide trend towards deregulation of the entire industry on the one hand and the increased need for accurate and better network monitoring on the other hand, force power utilities exposed to this pressure to demand new solutions for wide area monitoring, protection and control. Wide-area monitoring, protection, and control require communicating the specific-node information to a remote station but all information should be time synchronized so that to neutralize the time difference between information. It gives a complete simultaneous snap shot of the power system. The conventional system is not able to satisfy the time-synchronized requirement of power system. Phasor Measurement Unit (PMU) is enabler of time-synchronized measurement, it communicate the synchronized local information to remote station.
基金Supported by the Natural Science Foundation of Jiangsu Province ( BK2010411 ) and the National International Cooperation Project of China-Korea (2011DFA11310).
文摘根据机组响应控制指令时间长短不同,提出一种多时间尺度协调的区域控制偏差(area control error,ACE)超前控制方法。首先分析了现有ACE超前控制方法的不足,给出目标时刻控制区理想总发电的预测模型;然后分析了计划机组计划与执行的关系,提出计划机组出力偏差的预估方法;进而综合考虑总发电、计划机组发电和自动发电控制(auto generation control,AGC)机组的希望运行点,计算出目标时刻协调AGC机组的希望总出力;最后,通过一个优化模型把协调AGC机组的希望总出力分配到各协调AGC机组上。文章所提方法已在四川电网投入现场试运行,结果证明了该方法的可行性。