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Summary This article gives an overview of the state‐of‐the‐art biomass‐based hydrogen production technologies. Various biological and thermochemical processes of biomass are taken into consideration to find the most economical method of hydrogen production. Biohydrogen generated by biophotolysis method, photo‐fermentation and dark fermentation is studied with respect to various feedstocks in Malaysia. The fermentation approaches of biohydrogen production have shown great potential to be a future substitute of fossil fuels. Dark fermentation method is a simple biological hydrogen production method that uses a variety of substrate and does not require any light as a source of energy. A promising future for biohydrogen production is anticipated by this process both industrially and commercially. Feasibility of hydrogen production from pyrolysis and water gasification of various biomass feedstock confirm that supercritical water gasification (SCWG) of biomass is the most cost‐effective thermochemical process. Highly moisturized biomass could be employed directly in SCWG without any high‐cost drying process. Indeed, a small amount of energy is required to pressurize hydrogen in the storage tank because of highly pressurized SCWG process. The cost of hydrogen produced by SCWG of biomass is about US$3/GJ (US$0.35/kg), which is extremely lower than biomass pyrolysis method (in the range of US$8.86/GJ to US$15.52/GJ) and wind‐electrolysis systems and PV‐electrolysis systems (US$20.2/GJ and US$41.8/GJ, respectively). The best feedstock for biomass‐based hydrogen production is identified based on the availability, location of the sources, processes required for the preparation of the feedstock and the total cost of acquiring the feedstock. The cheapest and most abundantly available biomass source in Malaysia is the waste of palm industry. Hydrogen production from palm oil mill effluent and palm solid residue could play a crucial role in the energy mix of Malaysia. Malaysia has this great capability to supply about 40% of its annual energy demand by hydrogen production from SCWG of palm solid waste. Copyright © 2015 John Wiley & Sons, Ltd.

This paper focuses on the detection and classification of the faults on electrical power transmission line using artificial neural networks. The three phase currents and voltages of one end are taken as inputs in the proposed scheme. The feed forward neural network along with back propagation algorithm has been employed for detection and classification of the fault for analysis of each of the three phases involved in the process. A detailed analysis with varying number of hidden layers has been performed to validate the choice of the neural network. The simulation results concluded that the present method based on the neural network is efficient in detecting and classifying the faults on transmission lines with satisfactory performances. The different faults are simulated with different parameters to check the versatility of the method. The proposed method can be extended to the Distribution network of the Power System. The various simulations and analysis of signals is done in the MATLAB® environment.

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a b s t r a c tThe United Arab Emirates (UAE) is an oil-rich country which is located in the eastern part of the Arabian Gulf. The country is considered among the highest energy consumer in the world. Likewise of the other GCC countries, UAE's economy mainly depends on the oil, gas and other fossil fuels. In the recent timings, with a continuous increase in UAE's population require further demand in its energy production which is essential for its economic growth. However as the fossil fuels are limited sources, consequently additional sustainable and renewable energy (RE) resources are necessary to be explored. In this context, the UAE is considering alternative RE resources to overcome such issues as well as to reduce environmental pollution and its carbon emission. The present work addresses the issues and challenges related with the RE resources technologies, in the scenario of UAE. The possible current, RE resources choices for UAE and potential future prospects of such technologies are mentioned. Further at the present timings, renewable energy resources such as photovoltaic energy, concentrated solar power, wave energy and fuel cell energy etc., which UAE's is mainly focusing are reviewed. Similarly the past and ongoing research work conducted on such technologies has been also discussed. It is expected that by exploring RE technologies, with proper utilization and with better planning these renewable energy sources will provide a suitable solution for the UAE's energy, economy and environmental issues.

Increasing concern about the shortage of energy resources and harmful outcome of fossil fuel emission has initiated new requirement of reliable and cleaner green power sources. Hence, solar photovoltaic and wind power system are fastest developing sources among different renewable energy sources. In the proposed work, the urgency of the national policy to upgrade the existing coal-based plant as integrated solar, wind and coal-based power plant to reduce the carbon emission and to evaluate the feasibility of developing grid-connected hybrid energy system in Ramapuram Chennai, India has been presented. Moreover, the regression models for estimation of global solar radiation using different metrological parameters are developed and compared with the results of other models. In this work, Ramapuram, Chennai, India area is chosen to install the wind and solar photovoltaic systems to feed three types of load (residential, commercial and industrial). In this study, ENNORE thermal power station, Chennai is considered to reduce the carbon emission as the integration of solar photovoltaic system and wind system to the grid reduce the units generation from this plant. Hence, study shows that 110329.56 kg emission is reduced from ENNORE thermal power station by using this system.

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