An Introduction to MultiAgent Systems.

The Smart Grid, regarded as the next generation power grid, uses two-way flows of electricity and information to create a widely distributed automated energy delivery network. In this article, we survey the literature till 2011 on the enabling technologies for the Smart Grid. We explore three major systems, namely the smart infrastructure system, the smart management system, and the smart protection system. We also propose possible future directions in each system. colorred{Specifically, for the smart infrastructure system, we explore the smart energy subsystem, the smart information subsystem, and the smart communication subsystem.} For the smart management system, we explore various management objectives, such as improving energy efficiency, profiling demand, maximizing utility, reducing cost, and controlling emission. We also explore various management methods to achieve these objectives. For the smart protection system, we explore various failure protection mechanisms which improve the reliability of the Smart Grid, and explore the security and privacy issues in the Smart Grid.

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Smart Grid — The New and Improved Power Grid: A Survey

The increasing interest in integrating intermittent renewable energy sources into microgrids presents major challenges from the viewpoints of reliable operation and control. In this paper, the major issues and challenges in microgrid control are discussed, and a review of state-of-the-art control strategies and trends is presented; a general overview of the main control principles (e.g., droop control, model predictive control, multi-agent systems) is also included. The paper classifies microgrid control strategies into three levels: primary, secondary, and tertiary, where primary and secondary levels are associated with the operation of the microgrid itself, and tertiary level pertains to the coordinated operation of the microgrid and the host grid. Each control level is discussed in detail in view of the relevant existing technical literature.

Trends in Microgrid Control

Smart Grid - The New and Improved Power Grid:

This book, written by two major figures in adaptive control, provides a wealth of material for researchers, practitioners, and students. While some researchers in adaptive control may note the absence of a particular topic, the book‘s scope represents a high-gain instrument. It can be used by designers of control systems to enhance their work through the information on many new theoretical developments, and can be used by mathematical control theory specialists to adapt their research to practical needs. The book is strongly recommended to anyone interested in adaptive control.

Adaptive Control

Microgrids are a new concept for future energy distribution systems that enable renewable energy integration and improved energy management capability. Microgrids consist of multiple distributed generators (DGs) that are usually integrated via power electronic inverters. In order to enhance power quality and power distribution reliability, microgrids need to operate in both grid-connected and island modes. Consequently, microgrids can suffer performance degradation as the operating conditions vary due to abrupt mode changes and variations in bus voltages and system frequency. This paper presents controller design and optimization methods to stably coordinate multiple inverter-interfaced DGs and to robustly control individual interface inverters against voltage and frequency disturbances. Droop-control concepts are used as system-level multiple DG coordination controllers, and control theory is applied to device-level inverter controllers. Optimal control parameters are obtained by particle-swarm-optimization algorithms, and the control performance is verified via simulation studies.

Control Methods of Inverter-Interfaced Distributed Generators in a Microgrid System

Smart Grid technology is recognized as a key component of the solution to challenges such as the increasing electric demand, an aging utility infrastructure and workforce, and the environmental impact of greenhouse gases produced during electric generation. This paper presents the application of a hybrid optimization algorithm for distributed energy resource (DER) management in Smart Grid operation. The approach emphasizes the advantages of using multiagent systems for profitable operation of a Smart Grid in the energy market. The trading strategy adopted for the auction process is a profit-maximizing adaptive bidding strategy based on risk and competitive equilibrium price prediction. The auctioneer manages the usage of DERs by receiving bids from buyers and asks from sellers. A hybrid-immune-system-based particle swarm optimization is used to minimize the fuel cost for generation assuming realistic market prices for power, distributed generator bids reflecting realistic operational costs, and load bids customized according to the consumers' priorities. The simulation results clearly indicate that the agent-based management is effective in coordinating the various DERs economically and profitably.

An Intelligent Auction Scheme for Smart Grid Market Using a Hybrid Immune Algorithm

Particle swarm optimization-based parameter identification applied to permanent magnet synchronous motors

The shipboard power system (SPS) supplies energy to electric equipment on ships. It is critical for the system to be reconfigurable for the purpose of survivability and reliability. In earlier work, a decentralized approach using agents for a radial SPS reconfiguration is successfully developed. Each agent in this system communicates only with its immediate neighbors, which reduces the dependency on the system topology. However, a ring structure in the system leads to the problem of redundant information accumulation among the agents, making the information flow in the system unstable. In this correspondence, the authors propose a method, based on the use of the spanning tree algorithm in the IEEE 802.1d protocol, for an agent system to detect and break the ring structure in the system. Then, an algorithm for calculating the information flow without redundant information accumulation is put forward. Finally, the proposed methodology is illustrated through a test case on a simplified SPS.

A multiagent based algorithm for ring-structured shipboard power system reconfiguration

Fault diagnosis and prognosis are important tools for the reliability, availability, and survivability of navy all-electric ships (AES). Extending the fault detection and diagnosis into predictive maintenance increases the value of this technology. The traditional diagnosis can be viewed as a single diagnostic agent having a model of the component or the whole system to be diagnosed. This becomes inadequate when the components or system become large, complex, and even distributed as on navy electric ships. For such systems, the software multiagents may offer a solution. A key benefit of software agents is their ability to automatically perform complex tasks in place of human operators. After briefly reviewing traditional fault diagnosis and software agent technologies, this paper discusses how these technologies can be used to support the drastic manning reduction requirements for future navy ships. Examples are given on the existing naval applications and research on detection, diagnostic, and prognostic software agents. Current work on a multiagent system for shipboard power systems is presented as an example of system-level application.

David A. Cartes

Papers

Control Methods of Inverter-Interfaced Distributed Generators in a Microgrid System

An Intelligent Auction Scheme for Smart Grid Market Using a Hybrid Immune Algorithm

Particle swarm optimization-based parameter identification applied to permanent magnet synchronous motors

A multiagent based algorithm for ring-structured shipboard power system reconfiguration

Fault Detection, Diagnostics, and Prognostics: Software Agent Solutions