5907

5522

كارشناسي ارشد

قدرت

اصفهان: دانشگاه صنعتي اصفهان، دانشكده برق و كامپيوتر

1389

نه،111ص.: مصور،جدول،نمودار

ص.ع.به فارسي و انگليسي

اكبر ابراهيمي

مسعود رشيدي نژاد

21/2/90

غلامرضا يوسفي، مريم ذكري

مهندسي برق و كامپيوتر

ID5522

به فارسي و انگليسي: قابل رويت در نسخه ديجيتالي

Generation Expansion Planning by a New Modified SFL Algorithm Morteza Jadidoleslam Zeidabadi m jadidoleslam@ec iut ac ir Date of Submission 2011 02 28 Department of Electrical and Computer Engineering Isfahan University of Technology Isfahan 84156 83111 Iran Degree M Sc Language Farsi Supervisor Akbar Ebrahimi ebrahimi@cc iut ac ir Abstract Generation Expansion Planning GEP is a part of expansion planning problem in power systems The GEP is defined as the problem of determining when where what type and how much capacity of new power plants should be constructed over a long term planning horizon to meet forecasted demand Least cost GEP is known as a highly constrained and non linear discrete dynamic optimization problem The main purpose of the problem is to minimize the total cost of generation system expansion plan within pre specified reliability criteria In order to achieve this objective in this thesis GEP is modeled as an optimization problem in which the objective function is to minimize the total investment operation and outage energy not served costs of power system as well as salvage value of investment costs Generation system reliability is assessed and provided by means of Expected Energy Not Served EENS and Loss of Load Probability LOLP indices Probabilistic Production Simulation PPS is done using the Equivalent Energy Function EEF method Production system simulation at each stage of planning horizon calculates the expected energy produced by each unit The reliability indices LOLP and EENS are also determined by the used simulation procedure To solve the GEP problem a new Modified Shuffled Frog Leaping MSFL algorithm is proposed in this thesis The SFL algorithm is a meta heuristic optimization method that mimics the memetic evolution of a group of frogs seeking for a location with maximum amount of available food It consists of a frog leaping rule for local search and a memetic shuffling rule for global information exchange Some issues in the original SFL algorithm may cause it not to be able to find the global optimum in some optimization problems and may get trapped in local optimums To overcome this problem a new frog leaping rule and a new strategy for frog distribution into memeplexes is introduced to improve the local exploration and performance of the original SFL algorithm To show the effectiveness of the MSFL algorithm it is applied to a test system with 15 existing power plants and 5 types of new candidates for a 12 years and a 24 years planning horizon The original SFL algorithm and the Genetic Algorithm GA are also applied to solve the GEP problem Simulation results show the advantages of the proposed MSFL algorithm over the original SFL and GA The proposed MSFL algorithm could also achieve an order of magnitude of improvement especially for the GEP problems in larger scale than other two algorithms Therefore the dimensionality is not the key factor and it can be employed as a planning tool for long term generation expansion planning in a real scale systems Keywords Generation Expansion Planning Probabilistic Production Simulation Shuffled Frog Leaping Algorithm Combinatorial Optimization Power System Reliability

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مسعود رشيدي نژاد

غلامرضا يوسفي، مريم ذكري