Economic cost-benefit analysis for power system operations with environmental considerations

Author(s):  
Alberto J. Lamadrid ◽  
Daniel L. Shawhan ◽  
Carlos E. Murillo-Sanchez ◽  
Ray D. Zimmerman ◽  
Yujia Zhu ◽  
...  
2011 ◽  
Vol 51 (2) ◽  
pp. 687
Author(s):  
Michael Nolan

This paper explores the lessons learnt from the Optimising Adaptation Investment projects for the Department of Climate Change and Energy Efficiency–it includes coastal settlements, water supply and rail infrastructure case studies. These projects are the first of their kind in Australia and are considered internationally as a leading example of economic cost benefit analysis. They have been used effectively to inform decision making on specific adaptation responses to climate change risks to existing and new infrastructure. The lessons learnt will be explored for offshore platforms, ports, rail, road, drainage, tailings dams, mine facilities, water, and power supply, which includes the following elements: What decision makers require to make informed decisions under the uncertainty of climate change impacts. Reducing the uncertainty through economic modelling and cost benefit analysis. Optimising the right timing and scale of various adaptation options. Benefiting from oil and gas infrastructure adaptation opportunities. To further support the elements above, the applied process for integrating climate adaptation into infrastructure planning, design and operation will be illustrated by AECOM project experiences. AECOM has completed more than 60 significant climate change risk and adaptation projects for mines, ports, water supply and treatment, energy generation, transmission and distribution, rail, road, and coastal settlements in Australia, including the report: Climate Change Impacts to Infrastructure in Australia for the Garnaut Climate Change Review.


2017 ◽  
Vol 25 (9) ◽  
pp. 638-642 ◽  
Author(s):  
Dong J. Cho ◽  
Hyung T. Kim ◽  
Jaywon Lee ◽  
Sang H. Park

1995 ◽  
Vol 10 (3) ◽  
pp. 1667-1675 ◽  
Author(s):  
E.G. Neudorf ◽  
D.L. Kiguel ◽  
G.A. Hamoud ◽  
B. Porretta ◽  
W.M. Stephenson ◽  
...  

2014 ◽  
Vol 8 (3) ◽  
pp. 395-428 ◽  
Author(s):  
Sekharan Sreejith ◽  
Sishaj P. Simon

Purpose – The aim of this paper is to compare the performance of static VAR compensator (SVC) and unified power flow controller (UPFC) in dynamic economic dispatch (DED) problem. DED schedules the online generator outputs with the predicted load demands over a certain period so that the electric power system is operated most economically. During last decade, flexible alternating current transmission systems (FACTS) devices are broadly used for maximizing the loadability of existing power system transmission networks. However, based on the literature survey, the performance of SVC and UPFC incorporated in the DED problem and its cost–benefit analysis are not discussed earlier in any of the literature. Design/methodology/approach – Here, the DED problem is solved applying ABC algorithm incorporating SVC and UPFC. The following conditions are investigated with the incorporation of SVC and UPFC into DED problem: the role of SVC and UPFC for improving the power flow and voltage profile and the approximate analysis on cost recovery and payback period with SVC and UPFC in DED problem. Findings – The incorporation of FACTS devices reduces the generation cost and improves the stability of the system. The percentage cost recovered with FACTS devices is estimated approximately using equated monthly installment (EMI) and non-EMI scheme. It is clear from the illustrations that the installation of FACTS devices is profitable after a certain period. Research limitations/implications – In this research work, the generation cost with FACTS devices is only taken into account while calculating the profit. The other benefits like congestion management, cost gained due to land and cost due to stability issues are not considered. For future work, these things can be considered while calculating the benefit. Originality/value – The originality of the work is incorporation of FACTS devices in DED problem and approximate estimation of recovery cost with FACTS devices in DED problem.


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