Effective source-load prediction and reasonable dispatching are crucial to realize the economic and reliable operations of integrated energy systems(IESs).They can overcome the challenges introduced by the uncertainti...Effective source-load prediction and reasonable dispatching are crucial to realize the economic and reliable operations of integrated energy systems(IESs).They can overcome the challenges introduced by the uncertainties of new energies and various types of loads in the IES.Accordingly,a robust optimal dispatching method for the IES based on a robust economic model predictive control(REMPC)strategy considering source-load power interval prediction is proposed.First,an operation model of the IES is established,and an interval prediction model based on the bidirectional long short-term memory network optimized by beetle antenna search and bootstrap is formulated and applied to predict the photovoltaic power and the cooling,heating,and electrical loads.Then,an optimal dispatching scheme based on REMPC is devised for the IES.The source-load interval prediction results are used to improve the robustness of the REPMC and reduce the influence of source-load uncertainties on dispatching.An actual IES case is selected to conduct simulations;the results show that compared with other prediction techniques,the proposed method has higher prediction interval coverage probability and prediction interval normalized averaged width.Moreover,the operational cost of the IES is decreased by the REMPC strategy.With the devised dispatching scheme,the ability of the IES to handle the dispatching risk caused by prediction errors is enhanced.Improved dispatching robustness and operational economy are also achieved.展开更多
This paper presents a finite-time economic model predictive control(MPC)algorithm that can be used for frequency regulation and optimal load dispatch in multi-area power systems.Economic MPC can be used in a power sys...This paper presents a finite-time economic model predictive control(MPC)algorithm that can be used for frequency regulation and optimal load dispatch in multi-area power systems.Economic MPC can be used in a power system to ensure frequency stability,real-time economic optimization,control of the system and optimal load dispatch from it.A generalized terminal penalty term was used,and the finite-time convergence of the system was guaranteed.The effectiveness of the proposed model predictive control algorithm was verified by simulating a power system,which had two areas connected by an AC tie line.The simulation results demonstrated the effectiveness of the algorithm.展开更多
The emerging virtual coupling technology aims to operate multiple train units in a Virtually Coupled Train Set(VCTS)at a minimal but safe distance.To guarantee collision avoidance,the safety distance should be calcula...The emerging virtual coupling technology aims to operate multiple train units in a Virtually Coupled Train Set(VCTS)at a minimal but safe distance.To guarantee collision avoidance,the safety distance should be calculated using the state-of-the-art space-time separation principle that separates the Emergency Braking(EB)trajectories of two successive units during the whole EB process.In this case,the minimal safety distance is usually numerically calculated without an analytic formulation.Thus,the constrained VCTS control problem is hard to address with space-time separation,which is still a gap in the existing literature.To solve this problem,we propose a Distributed Economic Model Predictive Control(DEMPC)approach with computation efficiency and theoretical guarantee.Specifically,to alleviate the computation burden,we transform implicit safety constraints into explicitly linear ones,such that the optimal control problem in DEMPC is a quadratic programming problem that can be solved efficiently.For theoretical analysis,sufficient conditions are derived to guarantee the recursive feasibility and stability of DEMPC,employing compatibility constraints,tube techniques and terminal ingredient tuning.Moreover,we extend our approach with globally optimal and distributed online EB configuration methods to shorten the minimal distance among VCTS.Finally,experimental results demonstrate the performance and advantages of the proposed approaches.展开更多
荷电状态(state of charge,SOC)和峰值功率(state of peak power,SOP)的精确估计对保障电池安全稳定运行具有重要意义。为解决传统估计算法误差高、鲁棒性差等问题,本文提出了一种基于自适应无迹卡尔曼滤波(adaptive unscented Kalman f...荷电状态(state of charge,SOC)和峰值功率(state of peak power,SOP)的精确估计对保障电池安全稳定运行具有重要意义。为解决传统估计算法误差高、鲁棒性差等问题,本文提出了一种基于自适应无迹卡尔曼滤波(adaptive unscented Kalman filtering,AUKF)和经济模型预测控制(economic model predictive control,EMPC)的全钒液流电池(all-vanadium redox batteries,VRB)SOC/SOP联合估计方法。首先,为了提高传统模型的建模精度,本文综合考虑了VRB的电化学场和流体力学场的耦合特性,建立了一个能够全面刻画VRB运行过程的综合等效电路模型,并采用人工蜂群算法(artificial bee colony algorithm,ABC)对模型参数进行离线辨识。随后,考虑到传统的UKF算法无法适应系统噪声,收敛性差,且忽略电池参数变化等缺点,本文提出了基于AUKF的在线参数辨识和SOC估计算法,通过自适应调整UKF算法的参数来提高模型的精度。结合SOC的估计结果,采用EMPC算法估计VRB的SOP,并综合考虑了电压、电流、SOC和电解液流速等约束条件。最后,设计了多种实验工况验证了本文提出的SOC/SOP联合估计算法的精度。文章研究内容能够为液流电池不同运行状态下峰值功率预测和储能电站的精准调度提供依据。展开更多
对现有电站污染物控制装置基础上进行技术改造,协同实现汞污染控制是行之有效的技术方案,汞污染控制系统的技术经济性评估是燃煤电站管理者面临的首要问题.用Integrated Environmental Control Modeling(IECM)软件模拟了温度、煤种及空...对现有电站污染物控制装置基础上进行技术改造,协同实现汞污染控制是行之有效的技术方案,汞污染控制系统的技术经济性评估是燃煤电站管理者面临的首要问题.用Integrated Environmental Control Modeling(IECM)软件模拟了温度、煤种及空气污染控制装置的配置对活性炭吸附电站燃煤烟气汞效果的影响,并对不同条件下,活性炭的喷射量进行了模拟和经济性分析.结果表明活性炭捕获汞的效果是与排烟温度成反比的.对于燃烧烟煤的电厂,加入烟气脱硫装置(FGD)后活性炭的喷射量将大大减少,再结合选择性催化还原装置(SCR)后,可以达到很高的汞脱除效果;对于无烟煤和褐煤,加入烟气脱硫装置(FGD)可减少约27%的活性炭喷射量,但再加入催化还原装置(SCR)后,对活性炭的注入量几乎没有影响.展开更多
基金supported by the National Key Research and Development Project of China(2018YFE0122200).
文摘Effective source-load prediction and reasonable dispatching are crucial to realize the economic and reliable operations of integrated energy systems(IESs).They can overcome the challenges introduced by the uncertainties of new energies and various types of loads in the IES.Accordingly,a robust optimal dispatching method for the IES based on a robust economic model predictive control(REMPC)strategy considering source-load power interval prediction is proposed.First,an operation model of the IES is established,and an interval prediction model based on the bidirectional long short-term memory network optimized by beetle antenna search and bootstrap is formulated and applied to predict the photovoltaic power and the cooling,heating,and electrical loads.Then,an optimal dispatching scheme based on REMPC is devised for the IES.The source-load interval prediction results are used to improve the robustness of the REPMC and reduce the influence of source-load uncertainties on dispatching.An actual IES case is selected to conduct simulations;the results show that compared with other prediction techniques,the proposed method has higher prediction interval coverage probability and prediction interval normalized averaged width.Moreover,the operational cost of the IES is decreased by the REMPC strategy.With the devised dispatching scheme,the ability of the IES to handle the dispatching risk caused by prediction errors is enhanced.Improved dispatching robustness and operational economy are also achieved.
基金supported by the National Natural Science Foundation of China(Grant 62103101)the Natural Science Foundation of Jiangsu Province of China(Grant BK20210217)+5 种基金the China Postdoctoral Science Foundation(Grant 2022M710680)the National Natural Science Foundation of China(Grant 62273094)the"Zhishan"Scholars Programs of Southeast Universitythe Fundamental Science(Natural Science)General Program of Jiangsu Higher Education Institutions(No.21KJB470020)the Open Research Fund of Jiangsu Collaborative Innovation Center for Smart Distribution Network,Nanjing Institute of Technology(No.XTCX202102)the Introduced Talents Scientific Research Start-up Fund Project,Nanjing Institute of Technology(No.YKJ202133).
文摘This paper presents a finite-time economic model predictive control(MPC)algorithm that can be used for frequency regulation and optimal load dispatch in multi-area power systems.Economic MPC can be used in a power system to ensure frequency stability,real-time economic optimization,control of the system and optimal load dispatch from it.A generalized terminal penalty term was used,and the finite-time convergence of the system was guaranteed.The effectiveness of the proposed model predictive control algorithm was verified by simulating a power system,which had two areas connected by an AC tie line.The simulation results demonstrated the effectiveness of the algorithm.
基金supported by the National Natural Science Foundation of China(52372310)the State Key Laboratory of Advanced Rail Autonomous Operation(RAO2023ZZ001)+1 种基金the Fundamental Research Funds for the Central Universities(2022JBQY001)Beijing Laboratory of Urban Rail Transit.
文摘The emerging virtual coupling technology aims to operate multiple train units in a Virtually Coupled Train Set(VCTS)at a minimal but safe distance.To guarantee collision avoidance,the safety distance should be calculated using the state-of-the-art space-time separation principle that separates the Emergency Braking(EB)trajectories of two successive units during the whole EB process.In this case,the minimal safety distance is usually numerically calculated without an analytic formulation.Thus,the constrained VCTS control problem is hard to address with space-time separation,which is still a gap in the existing literature.To solve this problem,we propose a Distributed Economic Model Predictive Control(DEMPC)approach with computation efficiency and theoretical guarantee.Specifically,to alleviate the computation burden,we transform implicit safety constraints into explicitly linear ones,such that the optimal control problem in DEMPC is a quadratic programming problem that can be solved efficiently.For theoretical analysis,sufficient conditions are derived to guarantee the recursive feasibility and stability of DEMPC,employing compatibility constraints,tube techniques and terminal ingredient tuning.Moreover,we extend our approach with globally optimal and distributed online EB configuration methods to shorten the minimal distance among VCTS.Finally,experimental results demonstrate the performance and advantages of the proposed approaches.
文摘对现有电站污染物控制装置基础上进行技术改造,协同实现汞污染控制是行之有效的技术方案,汞污染控制系统的技术经济性评估是燃煤电站管理者面临的首要问题.用Integrated Environmental Control Modeling(IECM)软件模拟了温度、煤种及空气污染控制装置的配置对活性炭吸附电站燃煤烟气汞效果的影响,并对不同条件下,活性炭的喷射量进行了模拟和经济性分析.结果表明活性炭捕获汞的效果是与排烟温度成反比的.对于燃烧烟煤的电厂,加入烟气脱硫装置(FGD)后活性炭的喷射量将大大减少,再结合选择性催化还原装置(SCR)后,可以达到很高的汞脱除效果;对于无烟煤和褐煤,加入烟气脱硫装置(FGD)可减少约27%的活性炭喷射量,但再加入催化还原装置(SCR)后,对活性炭的注入量几乎没有影响.
