Application of hybrid evolutionary Programming based particle swarm Optimization to multi area unit Commitment in a power system

Abstract

In most interconnected power systems the power requirement is newlineprincipally met by thermal power generation Several operating strategies are newlinepossible to meet the required power demand which varies from hour to hour newlineof the day An important criterion in power system operation is to meet the newlinepower demand at minimum fuel cost using an optimal mix of different power newlineplants Moreover in order to supply high quality of electric power to the newlinecustomer in a secure and economic manner thermal Unit Commitment UC newlineis considered to be one of the best available options It is thus recognized that newlinethe optimal UC of thermal systems which is the problem of determining the newlineschedule of generating units within a power system subject to a variety of newlineoperating constraints results in a great saving of electrical utilities So the newlinegeneral objective of the UC problem is to minimize the system s total newlineoperating cost while satisfying all the constraints The Unit Commitment newlineProblem UCP is commonly formulated as a nonlinear large scale mixedinteger newlinecombinational problem The exact solution to the Unit Commitment newlineProblem can be obtained by a complete enumeration of all feasible newlinecombinations of generating units which could be a huge number Then the newlineeconomic dispatch problem is solved for each feasible combination to newlineoptimally allocate the load demand among the running units while satisfying newlinethe power balance equation and unit operating limits Basically the high newlinedimension of the possible solution space is the real difficulty in solving the newlineunit commitment problem newline newline