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Autonomous Vehicle Platoons In Urban Road Networks:A Joint Distributed Reinforcement Learning and Model Predictive Control Approach
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作者 Luigi D’Alfonso Francesco Giannini +3 位作者 Giuseppe Franzè Giuseppe Fedele Francesco Pupo Giancarlo Fortino 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2024年第1期141-156,共16页
In this paper, platoons of autonomous vehicles operating in urban road networks are considered. From a methodological point of view, the problem of interest consists of formally characterizing vehicle state trajectory... In this paper, platoons of autonomous vehicles operating in urban road networks are considered. From a methodological point of view, the problem of interest consists of formally characterizing vehicle state trajectory tubes by means of routing decisions complying with traffic congestion criteria. To this end, a novel distributed control architecture is conceived by taking advantage of two methodologies: deep reinforcement learning and model predictive control. On one hand, the routing decisions are obtained by using a distributed reinforcement learning algorithm that exploits available traffic data at each road junction. On the other hand, a bank of model predictive controllers is in charge of computing the more adequate control action for each involved vehicle. Such tasks are here combined into a single framework:the deep reinforcement learning output(action) is translated into a set-point to be tracked by the model predictive controller;conversely, the current vehicle position, resulting from the application of the control move, is exploited by the deep reinforcement learning unit for improving its reliability. The main novelty of the proposed solution lies in its hybrid nature: on one hand it fully exploits deep reinforcement learning capabilities for decisionmaking purposes;on the other hand, time-varying hard constraints are always satisfied during the dynamical platoon evolution imposed by the computed routing decisions. To efficiently evaluate the performance of the proposed control architecture, a co-design procedure, involving the SUMO and MATLAB platforms, is implemented so that complex operating environments can be used, and the information coming from road maps(links,junctions, obstacles, semaphores, etc.) and vehicle state trajectories can be shared and exchanged. Finally by considering as operating scenario a real entire city block and a platoon of eleven vehicles described by double-integrator models, several simulations have been performed with the aim to put in light the main f eatures of the proposed approach. Moreover, it is important to underline that in different operating scenarios the proposed reinforcement learning scheme is capable of significantly reducing traffic congestion phenomena when compared with well-reputed competitors. 展开更多
关键词 distributed model predictive control distributed reinforcement learning routing decisions urban road networks
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Distributed Model Predictive Load Frequency Control of Multi-area Power System with DFIGs 被引量:17
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作者 Yi Zhang Xiangjie Liu Bin Qu 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2017年第1期125-135,共11页
Reliable load frequency control LFC is crucial to the operation and design of modern electric power systems. Considering the LFC problem of a four-Area interconnected power system with wind turbines, this paper presen... Reliable load frequency control LFC is crucial to the operation and design of modern electric power systems. Considering the LFC problem of a four-Area interconnected power system with wind turbines, this paper presents a distributed model predictive control DMPC based on coordination scheme. The proposed algorithm solves a series of local optimization problems to minimize a performance objective for each control area. The generation rate constraints GRCs, load disturbance changes, and the wind speed constraints are considered. Furthermore, the DMPC algorithm may reduce the impact of the randomness and intermittence of wind turbine effectively. A performance comparison between the proposed controller with and without the participation of the wind turbines is carried out. Analysis and simulation results show possible improvements on closed-loop performance, and computational burden with the physical constraints. © 2014 Chinese Association of Automation. 展开更多
关键词 Asynchronous generators Electric control equipment Electric fault currents Electric frequency control Electric load management Electric power systems model predictive control Optimization Press load control WIND Wind turbines
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Resilience Against Replay Attacks:A Distributed Model Predictive Control Scheme for Networked Multi-Agent Systems 被引量:5
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作者 Giuseppe Franzè Francesco Tedesco Domenico Famularo 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2021年第3期628-640,共13页
In this paper,a resilient distributed control scheme against replay attacks for multi-agent networked systems subject to input and state constraints is proposed.The methodological starting point relies on a smart use ... In this paper,a resilient distributed control scheme against replay attacks for multi-agent networked systems subject to input and state constraints is proposed.The methodological starting point relies on a smart use of predictive arguments with a twofold aim:1)Promptly detect malicious agent behaviors affecting normal system operations;2)Apply specific control actions,based on predictive ideas,for mitigating as much as possible undesirable domino effects resulting from adversary operations.Specifically,the multi-agent system is topologically described by a leader-follower digraph characterized by a unique leader and set-theoretic receding horizon control ideas are exploited to develop a distributed algorithm capable to instantaneously recognize the attacked agent.Finally,numerical simulations are carried out to show benefits and effectiveness of the proposed approach. 展开更多
关键词 distributed model predictive control leader-follower networks multi-agent systems replay attacks resilient control
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Distributed model predictive control for multiagent systems with improved consistency 被引量:2
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作者 Shanbi WEI Yi CHAI Baocang DING 《控制理论与应用(英文版)》 EI 2010年第1期117-122,共6页
This paper addresses an improved distributed model predictive control (DMPC) scheme for multiagent systems with an attempt to improving its consistency. The deviation between what an agent is actually doing and what... This paper addresses an improved distributed model predictive control (DMPC) scheme for multiagent systems with an attempt to improving its consistency. The deviation between what an agent is actually doing and what its neighbors believe that agent is doing is penalized in the cost function of each agent. At each sampling instant the compatibility constraint of each agent is set tighter than the previous sampling instant. Like the traditional approach, the performance cost is utilized as the Lyapunov function to prove closed-looped stability. The closed-loop stability is guaranteed if the weight matrix for deviation in the cost function are sufficiently large. The proposed distributed control scheme is formulated as quadratic programming with quadratic constraints. A numerical example is given to illustrate the effectiveness of the proposed scheme. 展开更多
关键词 distributed model predictive control dmpc Multiagent systems Compatibility constraint CONSISTENCY
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Distributed Model Predictive Control for Networked Plant-wide Systems With Neighborhood Cooperation 被引量:2
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作者 Ting Bai Shaoyuan Li Yi Zheng 《IEEE/CAA Journal of Automatica Sinica》 EI CSCD 2019年第1期108-117,共10页
For large-scale networked plant-wide systems composed by physically(or geographically) divided subsystems, only limited information is available for local controllers on account of region and communication restriction... For large-scale networked plant-wide systems composed by physically(or geographically) divided subsystems, only limited information is available for local controllers on account of region and communication restrictions. Concerning the optimal control problem of such subsystems, a neighbor-based distributed model predictive control(NDMPC) strategy is presented to improve the global system performance. In this scheme, the performance index of local subsystems and that of its neighbors are minimized together in the determination of the optimal control input, which makes the local control decision also beneficial to its neighboring subsystems and further contributes to improving the convergence and control performance of overall system.The stability of the closed-loop system is proved. Moreover, the parameter designing method for distributed synthesis is provided.Finally, the simulation results illustrate the main characteristics and effectiveness of the proposed control scheme. 展开更多
关键词 distributed control model predictive control (MPC) NEIGHBORHOOD COOPERATION plant-wide SYSTEMS
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DISOPE distributed model predictive control of cascade systems with network communication 被引量:1
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作者 Yan ZHANG Shaoyuan LI 《控制理论与应用(英文版)》 EI 2005年第2期131-138,共8页
A novel distributed model predictive control scheme based on dynamic integrated system optimization and parameter estimation (DISOPE) was proposed for nonlinear cascade systems under network environment. Under the d... A novel distributed model predictive control scheme based on dynamic integrated system optimization and parameter estimation (DISOPE) was proposed for nonlinear cascade systems under network environment. Under the distributed control structure, online optimization of the cascade system was composed of several cascaded agents that can cooperate and exchange information via network communication. By iterating on modified distributed linear optimal control problems on the basis of estimating parameters at every iteration the correct optimal control action of the nonlinear model predictive control problem of the cascade system could be obtained, assuming that the algorithm was convergent. This approach avoids solving the complex nonlinear optimization problem and significantly reduces the computational burden. The simulation results of the fossil fuel power unit are illustrated to verify the effectiveness and practicability of the proposed algorithm. 展开更多
关键词 Cascade systems Dynamic integrated system optimization and parameter estimation (DISOPE) model predictive control (MPC) distributed control system (DCS) Autonomous agents Fossil fuel power unit (FFPU)
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Model-based Predictive Control for Spatially-distributed Systems Using Dimensional Reduction Models 被引量:3
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作者 Meng-Ling Wang Ning Li Shao-Yuan Li 《International Journal of Automation and computing》 EI 2011年第1期1-7,共7页
In this paper, a low-dimensional multiple-input and multiple-output (MIMO) model predictive control (MPC) configuration is presented for partial differential equation (PDE) unknown spatially-distributed systems ... In this paper, a low-dimensional multiple-input and multiple-output (MIMO) model predictive control (MPC) configuration is presented for partial differential equation (PDE) unknown spatially-distributed systems (SDSs). First, the dimension reduction with principal component analysis (PCA) is used to transform the high-dimensional spatio-temporal data into a low-dimensional time domain. The MPC strategy is proposed based on the online correction low-dimensional models, where the state of the system at a previous time is used to correct the output of low-dimensional models. Sufficient conditions for closed-loop stability are presented and proven. Simulations demonstrate the accuracy and efficiency of the proposed methodologies. 展开更多
关键词 Spatially-distributed system principal component analysis (PCA) time/space separation dimension reduction model predictive control (MPC).
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Distributed Model Predictive Control with Actuator Saturation for Markovian Jump Linear System 被引量:2
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作者 Yan Song Haifeng Lou Shuai Liu 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI 2015年第4期374-381,共8页
This paper is concerned with the distributed model predictive control (MPC) problem for a class of discrete-time Markovian jump linear systems (MJLSs) subject to actuator saturation and polytopic uncertainty in system... This paper is concerned with the distributed model predictive control (MPC) problem for a class of discrete-time Markovian jump linear systems (MJLSs) subject to actuator saturation and polytopic uncertainty in system matrices. The global system is decomposed into several subsystems which coordinate with each other. A set of distributed controllers is designed by solving a min-max optimization problem in terms of the solutions of linear matrix inequalities (LMIs). An iterative algorithm is developed to achieve the online computation. Finally, a simulation example is employed to show the effectiveness of the proposed algorithm. © 2014 Chinese Association of Automation. 展开更多
关键词 Actuators ALGORITHMS Iterative methods Linear matrix inequalities Linear systems Markov processes Matrix algebra model predictive control Optimization predictive control systems Robustness (control systems)
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The Design of Output Feedback Distributed Model Predictive Controller for a Class of Nonlinear Systems
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作者 Baili Su Yingzhi Wang 《Applied Mathematics》 2017年第12期1832-1850,共19页
For a class of nonlinear systems whose states are immeasurable, when the outputs of the system are sampled asynchronously, by introducing a state observer, an output feedback distributed model predictive control algor... For a class of nonlinear systems whose states are immeasurable, when the outputs of the system are sampled asynchronously, by introducing a state observer, an output feedback distributed model predictive control algorithm is proposed. It is proved that the errors of estimated states and the actual system's states are bounded. And it is guaranteed that the estimated states of the closed-loop system are ultimately bounded in a region containing the origin. As a result, the states of the actual system are ultimately bounded. A simulation example verifies the effectiveness of the proposed distributed control method. 展开更多
关键词 Nonlinear Systems distributed model predictive control State OBSERVER Output Feedback ASYNCHRONOUS Measurements
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Distributed model predictive control based on adaptive sampling mechanism
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作者 Zhen Wang Aimin An Qianrong Li 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2021年第11期193-204,共12页
In this work,an adaptive sampling control strategy for distributed predictive control is proposed.According to the proposed method,the sampling rate of each subsystem of the accused object is determined based on the p... In this work,an adaptive sampling control strategy for distributed predictive control is proposed.According to the proposed method,the sampling rate of each subsystem of the accused object is determined based on the periodic detection of its dynamic behavior and calculations made using a correlation function.Then,the optimal sampling interval within the period is obtained and sent to the corresponding sub-prediction controller,and the sampling interval of the controller is changed accordingly before the next sampling period begins.In the next control period,the adaptive sampling mechanism recalculates the sampling rate of each subsystem’s measurable output variable according to both the abovementioned method and the change in the dynamic behavior of the entire system,and this process is repeated.Such an adaptive sampling interval selection based on an autocorrelation function that measures dynamic behavior can dynamically optimize the selection of sampling rate according to the real-time change in the dynamic behavior of the controlled object.It can also accurately capture dynamic changes,meaning that each sub-prediction controller can more accurately calculate the optimal control quantity at the next moment,significantly improving the performance of distributed model predictive control(DMPC).A comparison demonstrates that the proposed adaptive sampling DMPC algorithm has better tracking performance than the traditional DMPC algorithm. 展开更多
关键词 Chemical process distributed model predictive control Adaptive sampling mechanism Optimal sampling interval System dynamic behavior
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Networked Cooperative Distributed Model Predictive Control Based on State Observer
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作者 Baili Su Yanan Zhao Jinming Huang 《Applied Mathematics》 2016年第10期1148-1164,共17页
Although distributed model predictive control has caused significant attention and received many good results, the results are mostly under the assumption that the system states can be observed. However, the states ar... Although distributed model predictive control has caused significant attention and received many good results, the results are mostly under the assumption that the system states can be observed. However, the states are difficult to be observed in practice. In this paper, a novel distributed model predictive control is proposed based on state observer for a kind of linear discrete-time systems where states are not measured. Firstly, an output feedback control law is designed based on Lyapunov function and state observer. And the stability domain is described. Furthermore, the stability domain as a terminal constraint is added into the constraint conditions of the algorithm to make systems stable outside the stability domain. The simulation results show the effectiveness of the proposed method. 展开更多
关键词 distributed System model predictive control Lyapunov Function State Observer Stable Domain Cooperative control
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Virtually coupled train set control subject to space-time separation:A distributed economic MPC approach with emergency braking configuration
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作者 Xiaolin Luo Tao Tang +1 位作者 Le Wang Hongjie Liu 《High-Speed Railway》 2024年第3期143-152,共10页
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
关键词 Virtually coupled train set Space-time separation Economic model predictive control distributed model predictive control Emergency braking configuration
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Distributed Mo del Predictive Control Based on Multi-agent Mo del for Electric Multiple Units 被引量:12
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作者 LI Zhong-Qi 《自动化学报》 EI CSCD 北大核心 2014年第11期2625-2631,共7页
关键词 分布式电源 电动车组 多代理 预测控制 多单元 协调控制算法 多AGENT 功率单元
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A Composite Model Predictive Control Strategy for Furnaces
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作者 臧灏 李宏光 +1 位作者 黄静雯 王佳 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2014年第7期788-794,共7页
Tube furnaces are essential and primary energy intensive facilities in petrochemical plants. Operational optimization of furnaces could not only help to improve product quality but also benefit to reduce energy consum... Tube furnaces are essential and primary energy intensive facilities in petrochemical plants. Operational optimization of furnaces could not only help to improve product quality but also benefit to reduce energy consumption and exhaust emission. Inspired by this idea, this paper presents a composite model predictive control(CMPC)strategy, which, taking advantage of distributed model predictive control architectures, combines tracking nonlinear model predictive control and economic nonlinear model predictive control metrics to keep process running smoothly and optimize operational conditions. The controllers connected with two kinds of communication networks are easy to organize and maintain, and stable to process interferences. A fast solution algorithm combining interior point solvers and Newton's method is accommodated to the CMPC realization, with reasonable CPU computing time and suitable online applications. Simulation for industrial case demonstrates that the proposed approach can ensure stable operations of furnaces, improve heat efficiency, and reduce the emission effectively. 展开更多
关键词 FURNACE Tracking nonlinear model predictive control Economic nonlinear model predictive control distributed model predictive control
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Consensus of Multi-Agent Systems with Input Constraints Based on Distributed Predictive Control Scheme
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作者 Yueqi Hou Xiaolong Liang +3 位作者 Lyulong He Jiaqiang Zhang Jie Zhu Baoxiang Ren 《Computers, Materials & Continua》 SCIE EI 2020年第3期1335-1349,共15页
Consensus control of multi-agent systems has attracted compelling attentions from various scientific communities for its promising applications.This paper presents a discrete-time consensus protocol for a class of mul... Consensus control of multi-agent systems has attracted compelling attentions from various scientific communities for its promising applications.This paper presents a discrete-time consensus protocol for a class of multi-agent systems with switching topologies and input constraints based on distributed predictive control scheme.The consensus protocol is not only distributed but also depends on the errors of states between agent and its neighbors.We focus mainly on dealing with the input constraints and a distributed model predictive control scheme is developed to achieve stable consensus under the condition that both velocity and acceleration constraints are included simultaneously.The acceleration constraint is regarded as the changing rate of velocity based on some reasonable assumptions so as to simplify the analysis.Theoretical analysis shows that the constrained system steered by the proposed protocol achieves consensus asymptotically if the switching interaction graphs always have a spanning tree.Numerical examples are also provided to illustrate the validity of the algorithm. 展开更多
关键词 Multi-agent systems CONSENSUS input constraints model predictive control distributed control switching interaction graphs
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基于DMPC的无信控交叉口智能网联车辆多车协同轨迹规划
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作者 金立生 魏青嵩 +3 位作者 谢宪毅 石业玮 雒国凤 李克强 《汽车安全与节能学报》 CAS CSCD 北大核心 2024年第2期235-241,共7页
为了解决智能网联自动驾驶环境下无信控十字交叉口多车协同通行的冲突问题,该文提出了一种基于分布式模型预测控制(DMPC)的多车协同轨迹规划方法。采用分布式模型预测框架实现多车协同轨迹规划的分布式独立计算,利用滚动时域预测周车轨... 为了解决智能网联自动驾驶环境下无信控十字交叉口多车协同通行的冲突问题,该文提出了一种基于分布式模型预测控制(DMPC)的多车协同轨迹规划方法。采用分布式模型预测框架实现多车协同轨迹规划的分布式独立计算,利用滚动时域预测周车轨迹实现车-车未来状态交互,基于智能网联环境车-车交互通信功能实现规划结果共享;引入道路边界约束、加速度约束与碰撞约束等车辆安全约束条件,通过二次规划求解可以安全通行十字路口的多车轨迹;基于MATLAB驾驶场景生成模块建立无信控十字交叉口环境,并在2种场景下验证了该方法的有效性。结果表明:在直行工况和左转工况下多车间最小距离分别为2.58 m和2.99 m,均满足避撞的安全距离约束,实现了多车之间的协同避撞并且能够保证通行效率。 展开更多
关键词 车辆工程 无信控十字交叉口 多车协同 分布式模型预测控制(dmpc) 轨迹规划
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基于视线协同和DMPC的载机-防御弹群协同主动防御制导策略
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作者 杨登峰 闫晓东 《系统工程与电子技术》 EI CSCD 北大核心 2024年第5期1724-1733,共10页
在目标-攻击弹-防御弹群(target-attacker-defenders,TADs)系统中,防御弹群通过与目标(载机)异构协同、弹群间同构协同以保护载机并降低单弹脱靶的风险。针对TADs系统在二维平面下的协同主动防御模型进行了研究,采用机/弹协同和防御弹... 在目标-攻击弹-防御弹群(target-attacker-defenders,TADs)系统中,防御弹群通过与目标(载机)异构协同、弹群间同构协同以保护载机并降低单弹脱靶的风险。针对TADs系统在二维平面下的协同主动防御模型进行了研究,采用机/弹协同和防御弹群协同的两层制导策略。在机弹协同方面,防御弹领弹与载机进行异构协同,考虑载机及防御弹领弹的机动能力限制,采用协同视线制导律(cooperative line of sight guidance,CLOSG)分别得到载机和防御弹领弹的制导指令;在防御弹群协同方面,考虑单弹计算能力约束,拦截时间约束和加速度约束,设计出基于分布式模型预测控制(distributed model predictive control,DMPC)的算法实现弹群从弹和防御弹领弹协同同时抵达并拦截攻击弹。仿真结果表明,多防御弹协同一致拦截制导算法能够实现TADs系统中载机和防御弹群的异构协同主动防御,并实现防御弹群的一致性同时拦截,以降低单弹脱靶的风险。 展开更多
关键词 协同主动防御 异构协同 目标-攻击弹-防御弹群系统 协同视线制导 分布式模型预测控制 一致性同时拦截
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Distributed Economic MPC for Synergetic Regulation of the Voltage of an Island DC Micro-Grid
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作者 Yi Zheng Yanye Wang +2 位作者 Xun Meng Shaoyuan Li Hao Chen 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2024年第3期734-745,共12页
In this paper,distributed model predictive control(DMPC) for island DC micro-grids(MG) with wind/photovoltaic(PV)/battery power is proposed,which coordinates all distributed generations(DG) to stabilize the bus voltag... In this paper,distributed model predictive control(DMPC) for island DC micro-grids(MG) with wind/photovoltaic(PV)/battery power is proposed,which coordinates all distributed generations(DG) to stabilize the bus voltage together with the insurance of having computational efficiency under a real-time requirement.Based on the feedback of the bus voltage,the deviation of the current is dispatched to each DG according to cost over the prediction horizon.Moreover,to avoid the excessive fluctuation of the battery power,both the discharge-charge switching times and costs are considered in the model predictive control(MPC) optimization problems.A Lyapunov constraint with a time-varying steady-state is designed in each local MPC to guarantee the stabilization of the entire system.The voltage stabilization of the MG is achieved by this strategy with the cooperation of DGs.The numeric results of applying the proposed method to a MG of the Shanghai Power Supply Company shows the effectiveness of the distributed economic MPC. 展开更多
关键词 distributed model predictive control(dmpc) Lyapunovbased model predictive control micro-grid(MG) voltage control
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CBF-Based Distributed Model Predictive Control for Safe Formation of Autonomous Mobile Robots
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作者 MU Jianbin YANG Haili HE Defeng 《Journal of Shanghai Jiaotong university(Science)》 EI 2024年第4期678-688,共11页
A distributed model predictive control(DMPC)method based on robust control barrier function(RCBF)is developed to achieve the safe formation target of multi-autonomous mobile robot systems in an uncertain disturbed env... A distributed model predictive control(DMPC)method based on robust control barrier function(RCBF)is developed to achieve the safe formation target of multi-autonomous mobile robot systems in an uncertain disturbed environment.The first step is to analyze the safety requirements of the system during safe formation and categorize them into collision avoidance and distance connectivity maintenance.RCBF constraints are designed based on collision avoidance and connectivity maintenance requirements,and security constraints are achieved through a combination.Then,the specified safety constraints are integrated with the objective of forming a multi-autonomous mobile robot formation.To ensure safe control,the optimization problem is integrated with the DMPC method.Finally,the RCBF-DMPC algorithm is proposed to ensure iterative feasibility and stability while meeting the constraints and expected objectives.Simulation experiments illustrate that the designed algorithm can achieve cooperative formation and ensure system security. 展开更多
关键词 distributed model predictive control(dmpc) robust control barrier function(RCBF) autonomous mobile robot formation control collision avoidance
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基于改进蜣螂算法的多区域空调系统需求响应DMPC供冷策略
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作者 王鑫洋 闫秀英 +1 位作者 吴晓雪 侯帅旗 《计算机测量与控制》 2024年第10期250-262,共13页
针对夏季电网高峰期间办公建筑空调系统的峰值负荷造成电网短缺等问题,提出一种基于需求响应的多区域空调系统分布式模型预测控制(DMPC)供冷策略;以西安市某办公建筑的5个区域为研究对象,分别建立该办公建筑的物理模型及空调系统能耗数... 针对夏季电网高峰期间办公建筑空调系统的峰值负荷造成电网短缺等问题,提出一种基于需求响应的多区域空调系统分布式模型预测控制(DMPC)供冷策略;以西安市某办公建筑的5个区域为研究对象,分别建立该办公建筑的物理模型及空调系统能耗数学模型,并验证模型的准确性;构建多区域空调系统仿真模型,优化目标为最小化空调系统运行能耗和室温与设定值的误差最小;选取蜣螂算法作为优化工具,并针对该算法存在全局搜索速度慢、易早收敛和陷入局部最优等缺点;采取混沌映射策略优化种群初始化,生成更加均匀的种群以提升种群个体质量;利用螺旋搜索策略对蜣螂的觅食和繁殖行为进行更新,进一步扩展算法的全局搜索性;同时引入随机扰动和自适应因子改进蜣螂的偷窃行为,改善算法易陷入局部最优等问题;运用改进后的蜣螂算法对DMPC的滚动优化进行优化求解,并与PID温度反馈控制进行对比,验证DMPC的控制性能;实验结果表明,在所研究的5个区域中,DMPC比PID控制方法的响应速度分别提升了8.91、8.65、12.04、5.79和1.79%;结合需求响应策略利用分时电价进行调控,提出温度与启停优化调控策略对空调系统的峰值负荷进行削峰转移;结果表明两种预冷启停优化策略的峰时负荷转移率分别为27.29%和29.16%,可以有效地将系统高峰时段的冷负荷转移到其他时段,降低电网运行压力。 展开更多
关键词 需求响应 削峰转移 分布式模型预测控制 改进的蜣螂优化算法 节能优化
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