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Document Type:Latin Dissertation
Language of Document:English
Record Number:55499
Doc. No:TL25453
Call number:‭3270923‬
Main Entry:Jianhui Wang
Title & Author:Decision support tools for restructured power systemsJianhui Wang
College:Illinois Institute of Technology
Date:2007
Degree:Ph.D.
student score:2007
Page No:108
Abstract:Restructuring has brought tremendous changes to the electricity industry throughout the world. In many electricity markets in operation today, an independent system operator (ISO) plays a very important role of ensuring the economics and security of power system operation. Decision support tools are indispensable for the ISO to fulfill its responsibility and have to be improved as markets evolve. This dissertation presents three improvements in decision support tools. A new auction algorithm is proposed to simultaneously clear the energy and ancillary service markets. The most distinct feature of the proposed algorithm is that the ancillary services requirement is not pre-specified but determined based on contingency simulations. Benders decomposition is applied to address the computational complexity due to the increase of system size and/or the number of simulated contingencies. The proposed algorithm can assist the ISO to determine the optimal amount of hourly ancillary services requirement. A robust short-term dispatch algorithm is presented to address the intermittency that is usually related to renewable and distributed generation resources, such as wind and solar energy. Monte Carlo simulations with Latin hypercube sampling technique are conducted to model the intermittent wind power output. Benders decomposition is applied to address the computational complexity due to the increase in system size and/or the number of simulated scenarios. An important application of the proposed algorithm is to help the power system dispatcher identify an appropriate level of wind power penetration for minimization the cost and maximizing the power system security. A game theory-based model is proposed to model the competitive behavior of generation companies during their decision making process for capacity expansion. A co-evolutionary algorithm combined with pattern search is used to search for the Nash equilibrium of the game. The proposed model can assist the ISO to test different market rules for the long-term generation planning thus avoiding the adverse impacts of improper market designs in a volatile electricity market.
Subject:Applied sciences; Decision support; Independent system operators; Power systems; Electrical engineering; 0544:Electrical engineering
Added Entry:M. L. Shahidehpour, Zuyi
Added Entry:Illinois Institute of Technology