Performance evaluation of a novel biomass-based hybrid energy system employing optimisation and multi-criteria decision-making techniques

2020 ◽  
Vol 42 ◽  
pp. 100861
Author(s):  
Dibyendu Roy
Keyword(s):  
Decision Making ◽  
Performance Evaluation ◽  
Energy System ◽  
Multi Criteria Decision Making ◽  
Hybrid Energy System ◽  
Hybrid Energy

Performance evaluation and life cycle analysis of RES-hydrogen hybrid energy system for office building

2020 ◽  
Author(s):  
Antonis Peppas ◽  
Konstantinos Kollias ◽  
Antonis Politis ◽  
Lampros Karalis ◽  
Maria Taxiarchou ◽  
...  
Keyword(s):  
Performance Evaluation ◽  
Life Cycle ◽  
Life Cycle Analysis ◽  
Energy System ◽  
Office Building ◽  
Hybrid Energy System ◽  
Hybrid Energy

An intelligent strategy for hybrid energy system management

2019 ◽  
Vol 17 ◽  
pp. 550-554 ◽  
Author(s):  
I. Riverón ◽  
◽  
J.F. Gómez ◽  
B. González ◽  
J. Albino Méndez
Keyword(s):  
Energy System ◽  
System Management ◽  
Hybrid Energy System ◽  
Hybrid Energy

Nuclear Hybrid Energy System Reliability Model Progress Report

2017 ◽  
Author(s):  
Askin Guler Yigitoglu ◽  
Thomas Harrison ◽  
Michael Scott Greenwood
Keyword(s):  
System Reliability ◽  
Energy System ◽  
Progress Report ◽  
Reliability Model ◽  
Hybrid Energy System ◽  
Hybrid Energy

Robust Benchmarking of Indian Mutual Funds-A Partial Frontier Approach

2015 ◽  
Vol 5 (2) ◽  
Author(s):  
Ram Pratap Sinha
Keyword(s):  
Decision Making ◽  
Performance Evaluation ◽  
Mutual Funds ◽  
Mutual Fund ◽  
Multi Criteria Decision Making ◽  
Risk Framework ◽  
Programming Techniques ◽  
Risk Free Rate ◽  
Risk Ratios ◽  
Free Rate

Performance analysis of mutual funds is usually made on the basis of return-risk framework. Traditionally, excess return (over risk-free rate) to risk ratios were used for the purpose mutual fund evaluation. Subsequently, the application of non-parametric mathematical programming techniques in the context of performance evaluation facilitated multi-criteria decision making. However,the estimates of performance on the basis of conventional programming techniques like DEA and FDH are affected by the presence of outliers in the sample observations. The present, accordingly uses more robust benchmarking techniques for evaluating the performance od sectoral mutual fund schemes based on observations for the second half of 2010. The USP of the present study is that it uses two partial frontier techniques (Order-m and Order- a) which are less susceptible to the problem of extreme data.

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