A review of multi-criteria decision making applications for renewable energy site selection

Large-vscale hydrogen production and storage technologies: Current status and future directions

In this study, we developed a new hybrid mathematical model that combines wind-speed range with the log law to derive the wind energy potential for wind-generated hydrogen production in Pakistan. In addition, we electrolyzed wind-generated power in order to assess the generation capacity of wind-generated renewable hydrogen. The advantage of the Weibull model is that it more accurately reflects power generation potential (i.e., the capacity factor). When applied to selected sites, we have found commercially viable hydrogen production capacity in all locations. All sites considered had the potential to produce an excess amount of wind-generated renewable hydrogen. If the total national capacity of wind-generated was used, Pakistan could conceivably produce 51,917,000.39 kg per day of renewable hydrogen. Based on our results, we suggest that cars and other forms of transport could be fueled with hydrogen to conserve oil and gas resources, which can reduce the energy shortfall and contribute to the fight against climate change and global warming. Also, hydrogen could be used to supplement urban energy needs (e.g., for Sindh province Pakistan), again reducing energy shortage effects and supporting green city programs.

https://www.mdpi.com/2227-9717/7/4/196/pdf

Assessment of Wind Energy Potential for the Production of Renewable Hydrogen in Sindh Province of Pakistan

A review on hydrogen production and utilization: Challenges and opportunities

The water needs of the inhabitants of Saudi Arabia are met by desalination powered by electricity generated from fossil fuel. Excessive burning of fossil fuels results in faster depletion and causes an adverse impact on the local environment. Reverse osmosis (RO) desalination based on a hybrid renewable energy system (HRES) has emerged as a cleaner alternative. The primary objective of this review is to assess the current status of utilizing renewable energy for small and large-scale water desalination plants. An overview of the expansion of domestic and global desalination plant capacities is presented with the evaluation of Saudi Arabia’s renewable energy potential. Numerous studies on coupling various combinations of renewable energy sources to power desalination processes are reviewed. A comprehensive analysis of the trends and technical developments of PV-RO, Wind-RO, and hybrid PV-Wind-RO for a wide range of capacities over the past three decades is provided. Designing and modeling HRES-RO desalination systems using different combinations of renewable energy sources are thoroughly analyzed and the technical aspects of their performance are presented. The application of a range of optimization and sizing software tools available for conducting pre-feasibility analysis and the comparison of the available software tools for HRES-RO desalination are also presented. The study also demonstrated that the replacement of fossil fuel with renewable energy for desalination will significantly decrease greenhouse gas emissions. The review also highlights the effect of solar and wind profiles on the economics of desalination powered by renewables. The economic analysis indicates a significant decrease in the cost of water production by hybrid PV-wind-RO systems, implying good prospects for the technology in the near future. Finally, the study provides a flowchart depicting the steps involved in installing a hybrid PV-wind-RO system in KSA.

A hybrid renewable energy system as a potential energy source for water desalination using reverse osmosis: A review

Renewable microgrids are new solutions for enhanced security, improved reliability and boosted power quality and operation in power systems. By deploying different sources of renewables such as solar panels and wind units, renewable microgrids can enhance reducing the greenhouse gasses and improve the efficiency. This paper proposes a machine learning based approach for energy management in renewable microgrids considering a reconfigurable structure based on remote switching of tie and sectionalizing. The suggested method considers the advanced support vector machine for modeling and estimating the charging demand of hybrid electric vehicles (HEVs). In order to mitigate the charging effects of HEVs on the system, two different scenarios are deployed; one coordinated and the other one intelligent charging. Due to the complex structure of the problem formulation, a new modified optimization method based on dragonfly is suggested. Moreover, a self-adaptive modification is suggested, which helps the solutions pick the modification method that best fits their situation. Simulation results on an IEEE microgrid test system show its appropriate and efficient quality in both scenarios. According to the prediction results for the total charging demand of the HEVs, the mean absolute percentage error is 0.978, which is very low. Moreover, the results show a 2.5% reduction in the total operation cost of the microgrid in the intelligent charging compared to the coordinated scheme.

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Mostafa Rezaei

Papers

An Advanced Machine Learning Based Energy Management of Renewable Microgrids Considering Hybrid Electric Vehicles' Charging Demand

Using fuzzy MCDM technique to find the best location in Qatar for exploiting wind and solar energy to generate hydrogen and electricity

Wind energy utilization for hydrogen production in an underdeveloped country: An economic investigation

Investigation of the optimal location design of a hybrid wind-solar plant: A case study

Investigation of off-grid photovoltaic systems for a reverse osmosis desalination system: A case study