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Intelligent optimization of renewable resource mixes incorporating the effect of fuel risk, fuel cost and CO2 emission

Intelligent optimization of renewable resource mixes incorporating the effect of fuel risk, fuel cost and CO2 emission

作     者:Deepak KUMAR D. K. MOHANTA M. Jaya Bharata REDDY 

作者机构:School of Electrical Sciences Indian Institute of Technology Bhuba-neswar Odisha 751013 India Electrical Engineering Department Birla Institute of Technology MesraRanchi 835215 India Electrical Engineering Department National Institute of TechnologyTrichy 620015 India 

出 版 物:《Frontiers in Energy》 (能源前沿(英文版))

年 卷 期:2015年第9卷第1期

页      面:91-105页

核心收录:

学科分类:080703[工学-动力机械及工程] 07[理学] 08[工学] 070602[理学-大气物理学与大气环境] 0807[工学-动力工程及工程热物理] 0706[理学-大气科学] 

主  题:modem portfolio theory energy policy CO2 emissions multi-objective optimization planning commis-sion 

摘      要:Power system planning is a capital intensive investment-decision problem. The majority of the conven- tional planning conducted since the last half a century has been based on the least cost approach, keeping in view the optimization of cost and reliability of power supply. Recently, renewable energy sources have found a niche in power system planning owing to concerns arising from fast depletion of fossil fuels, fuel price volatility as well as global climatic changes. Thus, power system planning is under-going a paradigm shift to incorporate such recent technologies. This paper assesses the impact of renewable sources using the portfolio theory to incorporate the effects of fuel price volatility as well as CO2 emissions. An optimization framework using a robust multi-objective evolutionary algorithm, namely NSGA-II, is developed to obtain Pareto optimal solutions. The performance of the proposed approach is assessed and illustrated using the Indian power system considering real-time design prac- tices. The case study for Indian power system validates the efficacy of the proposed methodology as developing countries are also increasing the investment in green energy to increase awareness about clean energy technologies.

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