OPTIMAL ALLOCATION OF FACTS DEVICES TO ENHANCE POWER SYSTEMS PERFORMANCE скачать в хорошем качестве

OPTIMAL ALLOCATION OF FACTS DEVICES TO ENHANCE POWER SYSTEMS PERFORMANCE

Design Details: IEEE 30 Bus System with Multi and individual FACTS (SVC, TCSC, UPFC) location with TLBO Optimization Algorithm and Mono Carlo simulation(MCS) Power Flow Method Results Evaluation: 1. Location of FACTS 2. Capacity 3. Reactive Loss Design Key Points • Variable reactant model of FACTS devices used in the program • Wind farm bus connection used in the design which includes correlation load • The location of FACTS used in the design is variable in TLBO • Model of FACTS used for each device in power flow power loss minimize • Design based on 2PEM-OPF, MCS-OPF method • Random values are generated based on Weibull distribution and normal distribution • Monte Carlo simulation, values are sampled at random from the input probability distributions. • Each set of samples is called an iteration, and the resulting outcome from that sample is recorded. • Monte Carlo simulation does this hundred or thousands of times, and the result is a probability distribution of possible outcomes. • 2PEM method based on Hong’s 2-point estimate process • Randomly generate initial value (example 10000 values) based on distribution from this initial find 2 best values using 2PEM method • Look the chapter 4.2, 4.31.,4.3.2 for more details about the design from the reference paper-1. Reference-1: Probabilistic optimal power flow for power systems considering wind uncertainty and load correlation Author’s Name: Xue Li, Jia Cao, Dajun Du Source: 2014 Elsevier-Neurocomputing Year:2014 Reference-2: Optimal distributed generation placement under uncertainties based on point estimate method embedded genetic algorithm Author’s Name: Vasileios A. Evangelopoulos, Pavlos S. Georgilakis Source: IET Generation, Transmission & Distribution Year:2013 Reference-3: Optimal flexible alternative current transmission system device allocation under system fluctuations due to demand and renewable generation Author’s Name: S.J. Galloway,I.M. Elders,G.M. Burt,B. Sookananta Source: IET Generation, Transmission & Distribution Year:2009 Reference-4: Probabilistic Load Flow Considering Wind Generation Uncertainty Author’s Name: Morteza Aien,Reza Ramezani and S. Mohsen Ghavami Source: ETASR - Engineering, Technology & Applied Science Year:2011 Request source code for academic purpose, fill REQUEST FORM below, http://www.verilogcourseteam.com/requ... If you need Matlab p-code(encrypted files) to check the results, contact us by email to info@verilogcourseteam.com You may also contact +91 7904568456 by WhatsApp Chat, for paid services. Visit Website: http://www.verilogcourseteam.com/ Visit Our Social Media Like our Facebook Page:   / verilogcourseteam   Subscribe:    / verilogcourseteamelectricalprojects   Subscribe:    / verilogcourseteammatlabproject   Subscribe:    / verilogcourseteam