The host of conventional and metaheuristic approaches for optimal sizing of HRES have been reported. Which technique is ought to perform better, especially for region like north-west India?
This is what I have written that may address your research question. I used real options and portfolio theories to evaluate the value of portfolios when renewables are incorporated with power supplies from coal or gas. In my forthcoming book - Energy Investments: An adaptive approach to profiting from uncertainties - I examined this farther. My book is scheduled for release by Palgrave Macmillan in time for the Autumn 2017 term.
Article Renewable Energy with Volatile Prices: Why NPV Fails to Tell...
I have seen several studies where evolutionary algorithms are applied for the optimization. However, it strongly depends on the decision variables, constraint (Linear or non-linear) and the number of objective functions. You can see the paper attached.
There are several optimization techniques for hybrid renewable energy system (HRES). You can select a suitable technique based on the complexity the system, site specifications and number of objective functions. Artificial and hybrid algorithms are more recommended. Please refer to the below article that provides the most recent optimization methodologies of HRESS.
Regards.
Article A review on recent size optimization methodologies for stand...
I think that best and absolutely more common method for this purpose is NSGA-II method. You can find more information about this method in the introduced publication:
If you and all of dear readers have more questions, please let me know.
Regards,
Article Modeling and multi-objective optimization of an M-cycle cros...
Many commercial HRES system analysis environments and DSS (Decision support systems) like (IPSEpro, Homer,Open Gain....) use Genetic algorithms...
This a link to Berrazouane S. PhD theis paper in Energy Conversion Management Journal http://www.sciencedirect.com/science/article/pii/S0196890413007395
Parameter optimization via cuckoo optimization algorithm of fuzzy controller for energy management of a hybrid power system