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A new hybrid approach for the solution of nonconvex economic dispatch problem with valve-point effects
Authors:Tahir Nadeem Malik  Azzam ul Asar  Mudasser F Wyne  Shakil Akhtar
Affiliation:1. Dept. of Electrical Engineering, University of Engineering & Technology, Taxila, Pakistan;2. Dept. of Electrical Engineering, University of Engineering & Technology, Peshawar, NWFP, Pakistan;3. School of Engineering and Technology, National University, 3678 Aero Court, San Diego, CA 92123, USA;4. Dept. of Information Technology, Clayton State University, Morrow, GA 30062, USA
Abstract:Economic dispatch (ED) generally formulated as convex problem using optimization techniques by approximating generator input/output characteristic curves of monotonically increasing nature results in an inaccurate dispatch. The genetic algorithm has previously been used for the solution of problem for economic dispatch but takes longer time to converge to near optimal results. The hybrid approach is one of the methodologies used to fine tune the near optimal results produced by GA. This paper proposes new hybrid approach to solve the ED problem by using the valve-point effect. The approach we propose combines the genetic algorithm (GA) with active power optimization (APO) based on the Newton's second order approach (NSO). The genetic algorithm acts as a global optimizer giving near optimal generation schedule, which becomes the input for generation buses in APO algorithm. This algorithm acting as local search technique dispatching the generated active power of units for minimization of cost and gives optimum generation schedule. Three machines 6-bus, IEEE 5-machines 14-bus, and IEEE 6-mchines 30-bus systems have been tested for validation of our approach. Results of the proposed scheme compared with results obtained from GA alone give significant improvements in the generation cost showing the promise of the proposed approach.
Keywords:Genetic algorithm  Economic dispatch  Nonconvex cost function  Local search  Global solution  Valve-point effect  Optimal power flow
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