Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/8085
Title: ECONOMIC ASPECTS OF ELECTRIC GENERATION IN DEREGULATED ENVIRONMENT OF POWER SYSTEM
Authors: Yadav, Madhav Singh
Keywords: ELECTRICAL ENGINEERING
ELECTRIC GENERATION
DEREGULATED ENVIRONMENT
POWER SYSTEM
Issue Date: 2011
Abstract: In a vertically integrated power system, the term `Economic Generation' implies the minimization in the cost of generation with an obligatory fulfillment of demand and reserve constraints. The deregulation has brought about the introduction of competition in the power industry. As, no centralized control persists over generation under new structure, economic electric generation involves the generating company (GENCO) to decide the generation schedule of its different units in such a manner that maximizes its profit irrespective of system social benefit means without paying heed to the demand and reserve constraints fulfillment. The profit depends upon revenue which is governed by the market spot prices of power and reserve. With the forecasted reserve, energy market prices and forecasted demand, reserve requirements given, this thesis proposes a unit commitment method that solves the problem of generation scheduling over a period of time for GENCOs so that their profit is maximized. This problem is called profit. based unit commitment or price based unit commitment (PBUC). The traditional Lagrangian relaxation (LR) method used for solving unit commitment problem opts a dual optimization technique, where dual problem is solved by dynamic programming and Lagrange multipliers are updated with sub gradient method. Though, it provides a fast solution but it may suffer with the convergence problem due to the application of Gradient method for updating Lagrange multipliers. In the work being presented, a hybrid LRGA method is used for solving the PBUC problem in which the concept of genetic algorithm (GA) is adopted along with Lagrangian relaxation (LR) method for improvising the performance of LR method. An optimal path search technique is used to solve the two stage dynamic programming sub problem associated with the dual problem. While Lagrange multipliers are updated by genetic algorithms instead of sub gradient method. A 3 unit, 12 hour data set is used and PBUC problem is solved in two modes of reserve payments. The results are compared with the traditional commitment results for verifying the increase in profit.
URI: http://hdl.handle.net/123456789/8085
Other Identifiers: M.Tech
Appears in Collections:MASTERS' DISSERTATIONS (Electrical Engg)

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