Abstract

The insufficiency of energy resources, increased cost of generation and rising load demand necessitate optimized economic dispatch. The real world ED (Economic Dispatch) is highly non-convex, nonlinear and discontinuous problem with different equality and inequality constraints. In this research paper, a novel hybrid MFO-SQP (Moth Flame Optimization with Sequential Quadratic Programming) is proposed to solve the ED problem. The MFO is stochastic searching algorithm minimizes by random search and SQP is definite in nature that refines the local search in vicinity of local minima. Proposed technique has been implemented on 6, 15 and 40 units test system with different constraints like valve point loading effect, transmission loss, prohibited zones, generator capacity limits and power balance. Results, obtained from proposed technique are compared with those of the techniques reported in the literature, are proven better in terms of fuel cost and convergence.

Highlights

  • The insufficiency of energy resources, increased cost of generation and rising load demand necessitate optimized economic dispatch

  • Transmission loss in ED problem is calculated by using coefficient method which is described as follows: NN

  • MFO will optimize these flames by using its updating procedure and provide only one best flame at lowest cost which will be the solution of ED problem

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Summary

INTRODUCTION

Lectricity plays a vital role in the economy of any Ecountry and electrical power system has central importance in this regard. Ever-growing energy demand and increased fuel cost makes ED a very important problem in present power system. Some are based on simple mathematical concept and some belong to the AI (Artificial Intelligence) Among these techniques few lag due to non-qualitative results, computational burden, premature convergence, bulk memory consumption, large number of control parameters, large time consumption, non-consistent performance, complex structure, failure for large problem, global and local optimum search space limitations. SQP is used as local fine tune searcher for the search space explored by MFO. This hybrid algorithm is tested on 6, 15 and 40 units systems and results are compared with those obtained by using different algorithms reported in the literature

PROBLEM FORMULATION
Prohibited Operated Zones
Transmission Loss
MOTH FLAME OPTIMIZATION
SEQUENTIAL QUADRATIC PROGRAMMING
IMPLEMENTATION OF MFO-SQP n
CASE STUDIES AND RESULTS
Test System-1
Test System-2
Test System-3
CONCLUSION
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