اصلاح الگوريتم بهينه سازي فاخته براي حل مساله برنامه ريزي توسعه توليد

چكيده انگليسي :

An Improved Cuckoo Optimization Algorithm for Generation Expansion Planning Nooshin Soleymani n soleymani@ec iut ac ir Date of Submission September 20 2014 Department of Electrical and Computer Engineering Isfahan University of Technology Isfahan 84156 83111 IranDegree Master of Science Language FarsiSupervisor Akbar Ebrahimi ebrahimi@cc iut ac ir AbstractGeneration Expansion Planning GEP is the first crucial step in long term expansion planningissues after that the load is properly forecasted for a specified future period GEP is the problem ofdetermining when where what type and how much capacity of new power plants are required sothat the demand is adequately supplied for a foreseen future The GEP is concerned with a highlyconstrained nonlinear discrete dynamic optimization problem The main purpose of GEP is to findthe optimal generation expansion plan with minimum cost according to pre specified reliabilitycriteria In this thesis the GEP cost function is to minimize the total investment cost operation costand outage cost cost of the expected energy not served as well as salvage value of investmentcosts neglecting retirement of units Generation system reliability is provided by Expected EnergyNot Served EENS and Loss of Load Probability LOLP indices To calculate expected enegryproduced by each unit probabilistic production simulation is used by Equivalent Energy Function EEF method Some of metahueristic algorithms were applied to solve GEP problem The Cuckoo OptimizationAlogorithm COA is a new evolutionary algorithm which is suitable for continuous nonlinearoptimization problems This thesis presents a development of an improved cuckoo optimizationalgorithm ICOA and its application to solve discrete GEP problem Egg laying based on fitness anew egg laying readius ELR a new flying method a new migration operator and performing newpopulation based on genetic operators are developed to provide a more accurate search mechanismfor discrete optimization problem The ICOA approach is applied to a test system to solve the GEPproblem In order to show the effect of increasing scale on ICOA perormance the GEP is solved ina time horizon of 10 year and 20 year planning period For better comparison the PSO COA andMCOA algorithms are also applied to this test system Furtheremore the results of GA and SFLAfor this system are pursued The obtained results show that the proposed method rather than otherthree methods can provide a lower cost expansion plan for GEP Based on good application of the proposed method ICOA for solving discrete GEP problem agood application to continuous optimization problems is also expected for it so the ICOA isapplied to Economic Load Dispatch ELD problem as a nonlinear continuous problem in powersystem The aim of ELD is to find the optimal combination of generators in order to minimize thetotal fuel costs of thermal units while satisfying the load demand and operation constraints Furthermore the PSO COA and MCOA algorithms are applied to this test system for comparingresults The obtained results affirm fast convergence and efficiency of the proposed method ICOA compared to other applied algorithms It was shown that the developed ICOA improvedthe COA algorithm in solving both of discrete and continuous optimization problems Keywords Cuckoo Optimization Algorithm Generation Expansion Planning EconomicLoad Dispatch Particle Swarm Optimization Probabilistic Production Simulation

سليماني، نوشين

اصلاح الگوريتم بهينه سازي فاخته براي حل مساله برنامه ريزي توسعه توليد

الگورين بهينه سازي ازدحام ذرات , بهره برداري اقتصادي نيروگاه ها , شبيه سازي احتمالاتي توليد