Energy, exergy and exergoeconomic analyses and optimisation of 137 MW gas power station implementing MOPSOCD
by Rajesh Arora
International Journal of Energy Technology and Policy (IJETP), Vol. 16, No. 4, 2020

Abstract: Performance evaluation and optimisation of operating parameters of gas power plants are the key challenges for the researchers and the power plant designers. Traditional performance evaluation techniques being utilised operate on the first law of thermodynamics. Exhaustive studies in this area suggest scope of improvement in view of power output, thermal efficiency and cost effectiveness through more valuable evaluation techniques as second law analysis, exergoeconomic analysis and evolutionary algorithms. In this perspective, energy, exergy and exergoeconomic investigations of the gas power plant are executed in context with 1st and 2nd laws of thermodynamics. The multi-objective optimisation is also performed using NSGA-II and MOPSOCD evolutionary algorithms in MATLAB 9.2 in order to explore best input parameters and to find best trade off amongst two challenging objectives. The validation of the present work is done by correlating the obtained outcomes with 137 MW running gas power plant, Faridabad, India. The analysis illustrates a considerable enhancement in exergy efficiency of the power plant (around 18%) with a drop-in cost of the fuel and product as 15.72% and 13.24% respectively. However, total capital cost is increased by 10.61%.

Online publication date: Wed, 01-Jul-2020

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Energy Technology and Policy (IJETP):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?


Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com