The following information was submitted:
Transactions: WSEAS TRANSACTIONS ON SYSTEMS AND CONTROL
Transactions ID Number: 52-663
Full Name: S. MUTHU VIJAYA PANDIAN
Position: Associate Professor
Age: ON
Sex: Male
Address: Department of EEE, VLBJCET, Coimbatore, India
Country: INDIA
Tel: +91-9865259633
Tel prefix:
Fax: +9104222607152
E-mail address: ajay_vijay@rediffmail.com
Other E-mails: mvp_78@rediffmail.com
Title of the Paper: An Evolutionary Programming based Efficient particle swarm optimization for economic dispatch problem with valve-point loading
Authors as they appear in the Paper: S.Muthu Vijaya Pandian , K.Thanushkodi
Email addresses of all the authors: ajay_vijay@rediffmail.com, dr_thanush@rediffmail.com
Number of paper pages: 23
Abstract: Economic dispatch (ED) is one of the most important optimization problems in a power system. The objective of ED is that the sharing of power demand among the online generators keeping minimum cost of generation as a constraint. It determines the optimal settings of generator units with predicted load demand over certain period of time. The aim of the thesis is to operate an electric power system most economically within its security limits. It is known that the security limit of any generator lies between its minimum and maximum power generation capacity. This thesis mainly focuses on minimizing the total fuel cost of all generators of the power system. This thesis proposes the following two new PSO algorithms to solve non convex economic dispatch problem. • A Efficient Particle swarm optimization is termed as EPSO • A Hybrid of Evolutionary Programming (EP) and Efficient particle swarm optimization (EPSO) is termed as EP-EPSO Since ED is introduced, sever!
al methods are being used to solve these problems. However, all these methods cannot provide an optimal solution because they are trapped at some local optimum. The stochastic optimization techniques such as EPSO and EP have got the advantages of good convergent property. A significant speed up can be obtained by the hybrid of this algorithm. In traditional ED, the cost function of each generator is approximately represented as a simple quadratic equation and it is solved by using mathematical programming, which is based on several optimization techniques such as dynamic programming, linear programming and lambda iteration method. However, all these methods cannot provide an optimal solution because they get trapped at any one of the local optima and hence there is a need for efficient optimization techniques. This thesis develops and applies hybrid algorithm, EP-EPSO to non-convex economic dispatch problems. In order to exploit the promising solution region, a simple local!
random search EP procedure is integrated with EPSO to form the propos
ed hybrid algorithm. The implementation of this hybrid method EP-EPSO for ED problem is explained in detail. The proposed techniques are tested on standard test systems available in the literature. The performance of proposed EPSO and EP-EPSO are compared with i) PSO ii) GA iii) SA iv) MPSO v) GA-SA vi) PSO-SQP vii) EP-SQP viii) DEC-SQP ix) PSO-LRS and x) NPSO-LRS It is observed that the EP-EPSO has higher convergence rate, advanced quality and better optimal cost when compared to the other techniques. ED problems considered have been solved including transmission losses with and without valve-point loading effects
Keywords: Economic Dispatch, Valve-point Loading, Efficient particle swarm optimization, Transmission losses
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