Comparison of Centralized and Decentralized Systems in Power System Restoration

This paper proposes a multiagent approach to decentralized power system restoration for distribution system networks and presents a comparison of centralized and decentralized systems for power system restoration. Numerous studies have been conducted on power system restoration problems. From the viewpoint of system structures, this research can be divided into two categories: centralized systems and decentralized systems. In this study, we solve a power system restoration problem for a power distribution network by two different methods: mathematical programming (MIP) and the proposed multiagent‐based method (MAS). The proposed multiagent system consists of several distributing substation agents (DSAGs) and load agents (LAGs). An LAG corresponds to the customer load, and a DSAG supplies electricity to the LAG. From the simulation results, it can be seen that the proposed system can reach the right solution by making use of only local information and that the solution quality is better than that of the centralized system (MIP). This means that the proposed multiagent restoration system is a promising approach to larger scale distribution networks.     

A multi‐agent approach to unit commitment

This paper proposes a multiagent system to power system unit commitment problems. Multiagent is a new paradigm for developing software applications. Coordinating the behavior of autonomous agents is a key issue in agent‐oriented programming techniques today. Recently, agents are being used in an increasingly wide variety of applications, ranging from comparatively small systems such as E‐mail filters to large, open, complex systems such as air traffic control. Though some agent frameworks have been proposed in the power system field, the number of studies is limited. In this paper, we developed a power system unit commitment application by multiagent architecture. Our multiagent system has the following characteristics: (1) The system consists of a single facilitator agent, two mobile agents, and one or more generator agents which are elements of power system network. (2) The facilitator agent is developed to act as a manager for the process by using the singleton design pattern. The mobile agents migrate to generator‐agents to increase or decrease their power generations. The generator agents have their operational data. (3) Message object is developed to communicate between the agents using KQML‐like object. The proposed approach is applied to a simple model system, and the results show that the multiagent system is an efficient decentralized approach for solving power system unit commitment problems. © 2002 Wiley Periodicals, Inc. Electr Eng Jpn, 141(2): 41–47, 2002; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.10057     

Sampled-data bipartite consensus control of nonlinear multi-agent systems under denial-of-service attacks

This article concentrates on the sampled-data secure bipartite consensus problem for a class of nonlinear multiagent systems under intermittent denial-of-service attacks. The network communication channels are destroyed when the attacks occur, which causes all the system states to be unavailable. A novel distributed sampled-data output feedback control protocol is developed by using the discontinuous sensor data. It is proved by the Lyapunov stability analysis that the considered nonlinear multiagent systems can achieve bipartite consensus exponentially in light of the designed control protocol. Then, the control algorithm is extended to systems with both state and input delay. Finally, a simulation example is presented to verify the effectiveness of the proposed control protocol.     

Multiagent‐Based Electric Power Interchange between Microgrids

In this paper, we propose a multiagent‐based electric power interchange method between microgrids (MGs). The proposed multiagent system consists of eight types of agent: a single micro virtual power plant (MVPP) agent , several MG controller agents (MGCs), several load agents, several gas turbine (gas engine) agents, several photovoltaic generation agents, several wind turbine generation agents, several battery agents, and a single grid agent. In the proposed system, the MVPP plays an important role, facilitating electric power exchange between MGCs. Simulation results suggest that the proposed multiagent system could improve the load factor and reduce the MG operation cost.     

A Multiagent‐Based Microgrid Operation Method

In this paper, we propose an autonomous microgrid operation using a multiagent approach. The proposed multiagent system consists of seven types of agent: a single microgrid controller agent (MGC), several load agents (LAGs), several gas‐turbine (gas‐engine) agents (GAGs), several photovoltaic generation agents (PVAGs), several wind‐turbine generation agents (WTAGs), several battery agents (BAGs), and a single grid agent (GridAG). In a microgrid, LAGs act as consumers or buyers, GAGs, PVAGs, and WTAGs act as producers or sellers, and BAGs act as prosumers or sellers/buyers. In order to verify the performance of the proposed system, it is applied to a simple model system with different electrical power prices. From the simulation results, it can be seen that the proposed multiagent system can perform microgrid operations efficiently.     

A multiagent approach to power system normal operation

Recently, the electric utility industry worldwide has been facing pressure to be deregulated or restructured in order to increase its efficiency, to reduce operational cost, or to give consumers more alternatives. For this aspect, a great deal more research is needed to achieve a better, intelligent knowledge process. The present centralized system for power system control, operation, and planning must be remodeled to cope with these situations. With the promotion for the deregulation of the electric power system, the definition of the objective function for the optimization problem such as outage work operation for electric power systems is becoming critical. Currently, agents are an intense focus in many subfields of computer science and artificial intelligence. Agents are being used in an increasingly wide variety of applications. In this paper, we developed a power system normal operation application by multiagent architecture. Our multiagent system consists of several facilitator agents, equipment agents, and switch‐box agents. Facilitator agent acts as a manager for negotiation process between agents. Equipment agent corresponds to the element of the electric power system, such as bus, transformer, and transmission line, while switch‐box agent is the pseudo object which consists of neighboring current breakers and disconnecting switches. The proposed system realizes the appropriate switching operations by interacting with corresponding agents. The proposed approach is applied to a simple network, and the results show that the proposed multiagent system is an efficient decentralized approach for solving power system normal operations. © 2004 Wiley Periodicals, Inc. Electr Eng Jpn, 146(4): 26–33, 2004; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.10227     

Neural Networks for Real-Time Traffic Signal Control

Real-time traffic signal control is an integral part of the urban traffic control system, and providing effective real-time traffic signal control for a large complex traffic network is an extremely challenging distributed control problem. This paper adopts the multiagent system approach to develop distributed unsupervised traffic responsive signal control models, where each agent in the system is a local traffic signal controller for one intersection in the traffic network. The first multiagent system is developed using hybrid computational intelligent techniques. Each agent employs a multistage online learning process to update and adapt its knowledge base and decision-making mechanism. The second multiagent system is developed by integrating the simultaneous perturbation stochastic approximation theorem in fuzzy neural networks (NN). The problem of real-time traffic signal control is especially challenging if the agents are used for an infinite horizon problem, where online learning has to take place continuously once the agent-based traffic signal controllers are implemented into the traffic network. A comprehensive simulation model of a section of the Central Business District of Singapore has been developed using PARAMICS microscopic simulation program. Simulation results show that the hybrid multiagent system provides significant improvement in traffic conditions when evaluated against an existing traffic signal control algorithm as well as the SPSA-NN-based multiagent system as the complexity of the simulation scenario increases. Using the hybrid NN-based multiagent system, the mean delay of each vehicle was reduced by 78% and the mean stoppage time, by 85% compared to the existing traffic signal control algorithm. The promising results demonstrate the efficacy of the hybrid NN-based multiagent system in solving large-scale traffic signal control problems in a distributed manner.     

A multiagent‐based microgrid operation method considering charging and discharging strategies of electric vehicles

In this paper, we propose a multiagent‐based microgrid (MG) operation method considering charging and discharging electric vehicles (EVs). The proposed system consists of five types of agents: single microgrid controller agent, several load agents, several gas turbines/engine agents, several photovoltaic generation agents, and several electric vehicle agents. In the proposed method, the load balancing can be realized by suppressing sudden fluctuations in supply and demand balance due to the synchronization of charging and discharging of EVs. From the simulation results, it can be seen that the proposed multiagent system could realize the load equalization in MG.     

An adaptive and reliable system based on interdependence between agents

A multiagent system (MAS) has recently gained public attention as a technique to solve competition and cooperation in distributed systems. However, MAS's vulnerability due to the propagation of failures prevents its application to a large‐scale system. This paper proposes a general composition technique to improve its reliability easily applied to the existent MAS. The proposed system monitors messages between agents to detect undesirable behaviors (failures). Collecting related information, the system generates global information of interdependence between agents and expresses it in a graph. This interdependence graph enables us to detect or predict undesirable behaviors. This paper also shows that the system can optimize performance of MAS and improve adaptively its reliability under complicated and dynamic environment by applying the global information acquired from analysis of the interdependence graph to a replication system. © 2008 Wiley Periodicals, Inc. Electr Eng Jpn, 164(1): 62–68, 2008; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.20517     

火电厂Multiagent系统中的前馈控制代理

提出了一种火电厂multiagent系统中的前馈控制代理(FFCAs)系统。FFCAs利用模糊神经系统进行决策。FFCAs代理与反馈控制代理(FBCAs)通过通信协调合作,并向火电机组代理(FFPUAs)发送控制信号以完成各个任务。模拟结果显示,神经网络和模糊逻辑是FFCAs代理进行决策的有效工具。     

基于多Agent的变电站操作票自动生成系统

变电站操作票制度是保证变电站安全、可靠运行的重要措施,因此开具正确无误的倒闸操作票对于变电站的运行操作和维护管理具有重要的意义.本文提出将分布式人工智能之多Agent理论应用于操作票自动生成系统中,并结合RBF神经网络技术,建造了由设备操作序列生成Agent、校核Agent、解释Agent、协调控制Agent组成的具有分布式结构的变电站操作票MAS.研究表明该系统的实现过程简单、维护管理方便、具有较强的智能性.     

A Voltage Control Method for a Distributed Line Feeder by means of Multiagent Approach

This paper proposes a method for the coordinated control of power factor by means of a multiagent approach. The proposed multiagent system consists of two types of agent: single feeder agent (F_AG) and bus agent (B_AG). In the proposed system, an F_AG plays as an important role, which decides the power factors of all distributed generators by executing the load flow calculations repeatedly. The voltage control strategies are implemented as the class definition of Java into the system. In order to verify the performance of the proposed method, it has been applied to a typical distribution model system. The simulation results show that the system is able to control very violent fluctuation of the demands and the photovoltaic (PV) generations.     

Market-based multiagent system for reconfiguration of shipboard power systems

On ships, the electric shipboard power system (SPS) supplies electrical power to critical functions such as navigation, communication, emergency systems, and in the case of warships, weapon systems. During ship operation, some parts of the SPS may become unavailable due to damage, fault, or maintenance. For the survivability and reliability of ships, it is desired to make the SPS highly reconfigurable. This paper presents a market-based multiagent system (MAS) for the reconfiguration of radial SPS. Radial SPSs are found on majority of ships. In the proposed MAS, each agent only communicates with its neighbor agents to make the system work in a fully decentralized manner. The MAS is implemented using Java Agent Development Framework (JADE), which is fully implemented in Java and compliant with Foundation of Intelligent Physical Agents (FIPA). An SPS with two generators and four loads is used for testing the proposed MAS. The results show the proposed MAS can successfully reconfigure a radial SPS.     

考虑光储型电热协同系统灵活性的多代理削峰填谷策略

为解决光储型电热协同系统（electric-thermal system, ETS）协作参与电网削峰填谷问题,并减小负荷预测误差和新能源波动对调节效果的影响,提出一种多代理削峰填谷策略。该策略依托由配网代理、区域代理、ETS/光伏发电（PV）代理和执行单元构成的多代理系统实施,包含集中式能量优化和分布式能量管理环节。在集中式能量优化过程中,配网代理可通过求解以自身运行成本最小为优化目标的模型预测控制（model predictive control,MPC）优化模型,为区域代理及其内部的光伏系统提供日内有功功率上限计划。分布式能量管理过程中,区域代理和ETS/PV代理基于多智能体一致性算法获取供暖设备的有功功率修正值,从而减小实际区域代理有功功率与其计划值间的偏差。仿真结果表明：该策略可使系统协同参与削峰填谷且结果更精确。     

Adaptive cooperative tracking control of uncertain nonlinear multiagent systems with uncertain Markov switching communication graphs

This paper deals with the cooperative tracking problem of nonlinear multiagent systems. Compared with the existing works, both the uncertainties in model and switching topology are considered. Two control laws, the adaptive distributed controller based on state information and the adaptive distributed controller based on output information, are proposed using the neural networks. The advantage of the proposed controller is that we no longer require the exact knowledge of follower agents' parameters and the precise switching signal of communication topology by taking advantages of neural networks approximation and the property of transition probabilities. It is proved that all followers can track the leader with permitted bounded errors under the proposed controller. An illustration is given to testify the efficacy of the proposed approach.     

A distributed non-Lipschitz control framework for self-organizing microgrids with uncooperative and renewable generations

This paper investigates the design of robust distributed voltage and frequency control for a self-organized microgrid. A multiagent distributed secondary hierarchy is proposed using control Lyapunov function. Power resources are categorized as controllable and uncontrollable distributed generations (DG). Controllable DGs are exchanging information with neighbor DGs through agents at communication layer. The agents communicate to restore the voltage and frequency to their nominal references. Furthermore, the proposed scheme is robust against the insufficient data from uncontrollable DGs, since it provides an improved and stable operation even when there is no communication with uncontrollable DGs and loads. It can actively compensate for the random unknown demand and generation, by sharing the power mismatch in distributed droop architecture. It is shown that the suggested controller is capable of stabilizing an uncooperative microgrid in which not all DGs are cooperating. Also, the convergence speed of the system is improved using the finite-time controller. The performance and finite-time stability of a microgrid with partially-cooperative DGs is proved using Lyapunov theorem and is validated through numerical simulation. The results show improved transients, accurate steady state values for voltage and frequency control of a microgrid, and robustness against communication architecture variations. The impact of communication delays, the uncertainty in coupling gains of the communication links, and the time-interval between updating the controller and the states through communication are investigated.     

Distributed adaptive output consensus control of a class of uncertain nonlinear multiagents systems

This paper addresses the leader‐follower output consensus problem for a class of uncertain nonlinear multiagent systems in a directed communication topology. By employing the backstepping method, the dynamic surface control technique, neutral networks, and the graph theory, a distributed adaptive control scheme is developed recursively for each follower using its own and neighbors' information. The key features of this strategy are that it reduces the computational burden by introducing the dynamic surface control approach and there is no requirement for a priori knowledge about uncertain dynamics of the system. Moreover, in theory, it is proved that the designed control approach can steer the output signals of followers in a directed graph to track the desired trajectory of the leader and guarantee all signals in the closed‐loop system cooperatively semiglobally uniformly ultimately bounded. Furthermore, two examples are included, and the simulation results demonstrate the effectiveness of the proposed strategy.     

Fuzzy adaptive leader‐following consensus of second‐order multiagent systems with imprecise communication topology structure

The consensus problem of second‐order nonlinear multiagent systems (MAS) with imprecise communication topology structure is addressed in this paper. Takagi‐Sugeno fuzzy models are presented to describe the leader‐following MAS with imprecise communication topology structure. By designing the distributed adaptive controller, an efficient framework is proposed for the consensus control of the MAS with both uncertain parameters and input disturbances. Under the conditions that the communication topology is fuzzy union connected and the dynamics of the leader agent is unknown to any agent of followers, the proposed protocol can guarantee that the consensus errors asymptotically approach zeros. Furthermore, the proposed algorithm is extended to solve the formation control problem. Sufficient conditions are given for the consensus and formation problems of the MAS based on the Lyapunov stability theory. Finally, a numerical example and multiple pendulum systems are given to illustrate the effectiveness of the proposed control protocols.     

基于lEO61850变电站广域后备保护agent的信息模型研究

为了提高电力系统的安全性,使广域后备保护（wide—area backup protection,WABP）设备满足变电站自动化系统的发展要求,对基于IEC61850的分布式多主体（multiagent）WABP信息模型进行了研究。介绍了multiagentWABP的结构及功能,详细说明了WABP主体（agent）的设计方法,包括保护智能电子设备（intelligent electronic device,IED）的对象模式、WABPagent的组成模块、保护agent和常规逻辑节点间的信息流,根据信息的不同类型,可以选择传输控制协议或用户数据报协议在不同变电站之间来传递信息。最后,对广域通信模型进行了介绍。采用广域协作策略的multiagent WABP可以准确判断系统故障,具有很好的可行性和实用性。     

Optimal Energy Management for Smart Grid System Considering Battery Characteristics

This paper discusses optimal energy management considering battery characteristics for smart grid and microgrid systems. Energy storage systems are very important for energy peak shifting and peak load cutting in microgrid and smart grid systems, but optimal battery formulation and energy management in the use of expensive energy storage system and methods of taking account of battery characteristics are still in the developmental stage. First, the optimal battery placement for a smart grid system with lithium‐ion batteries is considered as a means of lifetime extension. The battery choice index for this optimal battery utilization problem of optimal energy management is discussed. Second, a smart grid system with a distributed battery system for grid frequency control with consideration of distributed control and battery characteristics is discussed. Optimal controllers for distributed battery systems to reduce the battery load and to expend the battery lifetime are designed. Simulations are used to demonstrate the effectiveness of the proposed method in comparison with conventional methods.