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Shipboard electric power systems (SPS) are dynamic, complex systems that require continuous monitoring and fast controls to operate in a reliable and secure state. A self-healing system for SPS was developed using common programming languages to arm SPS to monitor and respond to threats and natural system failures. This self-healing system includes features for activating control solutions before...
A shipboard power system (SPS) supplies energy to electrical loads on a ship. It is critical for the system to be reconfigurable for the purpose of survivability and reliability. In our earlier work an agent based de-centralized approach for a radial SPS reconfiguration is successfully developed. Each agent in this system only communicates with its immediate neighbors, which reduces the dependency...
This paper presents an expert system which performs detailed diagnosis of digital relay operation by analyzing data contained in relay files and reports. Problem domain is discussed first. Then the analysis strategy is detailed: forward chaining reasoning, logic reasoning and backward chaining reasoning are employed to predict protection operation, identify unexpected protection operation and diagnose...
Multi-agent systems can be defined as a network of interacting software modules that bring together dispersed systems that collectively manage complex tasks that are beyond the capacity of any individual system on the network. In this work, the aim behind this technology is to monitor and diagnose an electric system to validate certain control actions on the system depending on changing operating...
Summary form only given. There has been a sea change in the strategy and priorities of the Department of Defense and the US Navy as a result of the desire to accelerate transformation and as a response to the global war on terrorism. A review of recent policy documents can be interpreted as a driver for an expansion of the role of intelligent systems in naval platforms and as a guide for future technology...
Reliable electricity has become an essential underpinning for national security in modern society. The fault-tolerant generic framework proposed herein can prevent potential outages from happening through intelligent agent coordination. Instead of limiting the system to manage existing devices, the developed system is adaptive to the future power grid in years to come. This paper proposes a hardware-in-the-loop...
The goal of this chapter is to give fundamental knowledge on solving multi-objective optimization problems. The focus is on the intelligent metaheuristic approaches (evolutionary algorithms or swarm-based techniques). The focus is on techniques for efficient generation of the Pareto frontier. A general formulation of MO optimization is given in this chapter, the Pareto optimality concepts introduced,...
Adequate training programs for power systems restoration tasks must take into account that this is a cooperative activity involving several entities. The proposed architecture of the intelligent tutoring system presented in this paper is based on a multi-agent system offering a simulated training environment
For a market player, in order to perform an optimal risk management, it is important to have not only suitable price forecasting tools taking into account the most significant price drivers but also methods to quantify their accuracy. This paper proposes an intelligent system for price forecasting accuracy assessment (ISPF). The core of ISPF is a fuzzy interpolator of the effects of the price drivers;...
Renewable energies such as wind power or photovoltaic energy are environmentally focused but the output power fluctuation of the renewable energies may cause excess variation of voltage or frequency of the grid (Ramirez et al., 2004; Oliva and Balda, 2003), Marei et al., 2004), Okuyama et al., 2003). Increase of the amount of renewable energies would violate the quality of the grid (McCusker et al...
On the premise of future improvement of information infrastructures, we proposed a multi-agent based protection scheme for distribution systems with high penetration of distributed generators (DGs). In the proposed protection scheme, various relays designed as relay agents cooperate to locate and isolate fault zone. Binary state signal, e.g. current direction, magnitude, etc. is determined autonomously...
As a relatively new population based optimization technique, differential evolution has been attracting increasing attention for a wide variety of engineering applications including power engineering. Unlike the conventional evolutionary algorithms which depend on predefined probability distribution function for mutation process, differential evolution uses the differences of randomly sampled pairs...
This study presents the ant colony system (ACS) algorithms for optimization of power systems planning. The developed ACS algorithms formulate complex problems as combinatorial optimization problems. They are distributed algorithms composed by a set of cooperating artificial agents, called ants, which cooperate to find an optimum solution of the combinatorial problems. A pheromone matrix that plays...
This paper solves a unit commitment (UC) problem of the interconnected power system. The UC provides an approach to decrease the cost and improve reliability of the network. The UC is a dynamic process, and the generation plan is always changing according to different load and network topology. The problem is solved by ADP which solves the dynamic problem with a two-stage neural network method. One...
Expert-system-based approaches to complex computational procedures of transients in power systems are desirable because power systems contain complex and nonlinear elements. We propose the use of symbolically-aided modeling as the basis for the design of expert transient simulators. The symbolic approaches work well when (a) the user interface is "symbolized" and (b) the underlying computational...
Artificial intelligence (AI) techniques are becoming an active area of research for real applications. Power industry is one of the best examples of this. Different problems have been solved with these techniques, for example monitoring, alarm management, diagnosis, and network planning. This paper presents an on-line diagnosis system for gas turbines in power plants. Since this application deals...
This paper proposes a scheme for online voltage stability monitoring using radial basis function network (RBFN). A single RBFN is used to predict MW margins for different contingencies. A self-organizing learning algorithm and a sequential learning strategy are used to design the hidden layer of the RBFN and the weights in the output layer are determined by using linear optimization technique. The...
On-line monitoring of power system voltage security has become a very demanding task in competitive power market operation and fast estimation of bus voltage is essential for this. In this paper, a novel parallel radial basis function neural network (PRBFN) which is a multistage network, in which stages operate in parallel rather than in series during testing, has been developed to predict bus voltage...
Different from most power systems, the requirement for reliability of the power system on board a spacecraft is much more stringent. However, the reliability of the spacecraft power system can not be solely realized by increasing system redundancies due to limitations on mass. A Ring-Bus topology has been proposed for this purpose. This paper provides an analysis to this special topology, study selected...
This paper proposes a neural network solution methodology for the problem of measuring the actual amount of harmonic current injected into a power network by a non-linear load. The determination of harmonic currents is complicated by the fact that the supply voltage waveform is distorted by other loads and is rarely a pure sinusoid. A recurrent neural network architecture based method is used to find...
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