No abstract

Solar hydrogen generation is one of the new topics in the field of renewable energy. Recently, the rate of investigation about hydrogen generation is growing dramatically in many countries. Many studies have been done about hydrogen generation from natural resources such as wind, solar, coal etc. In this work we evaluated global scientific production of solar hydrogen generation papers from 2001 to 2014 in any journal of all the subject categories of the Science Citation Index compiled by Institute for Scientific Information (ISI), Philadelphia, USA. Solar hydrogen generation was used as keywords to search the parts of titles, abstracts, or keywords. The published output analysis showed that hydrogen generation from the sun research steadily increased over the past 14 years and the annual paper production in 2013 was about three times 2010-paper production. The number of papers considered in this research is 141 which have been published from 2001 to this date. There are clear distinctions among author keywords used in publications from the five most high-publishing countries such as USA, China, Australia, Germany and India in solar hydrogen studies. In order to evaluate this work quantitative and qualitative analysis methods were used to the development of global scientific production in a specific research field. The analytical results eventually provide several key findings and consider the overview hydrogen production according to the solar hydrogen generation.Electronic supplementary materialThe online version of this article (doi:10.1007/s11192-015-1730-3) contains supplementary material, which is available to authorized users.

A Hybrid Energy System (HES) is a mechanism that combines multiple sources of energy connected together to achieve synchronised energy output. However, increased energy consumption, operator energy expenses, and the potential environmental impact of increased emissions from the exhaustion of non-renewable energy resources (fossil fuel) pose major challenges to HES. This research is to conduct energy management strategy based on a demand response (DR) program and a hydrogen storage system by designing a Program Logic Controller (PLC) unit. The hybrid system is evaluated by comparing different scenarios such as a hydrogen energy system and demand response. The purpose of this research is to reducing peak demand, minimise the cost of the system and also to extract surplus power generation out of the rate of the battery. This can be achieved by improving the system performances and by eliminating any degradation at the early stages. Organisations or companies must be sure their systems are working properly and that their investments will pay off.

Photovoltaic system (PV) has nonlinear characteristics which are affected by changing the climate conditions and, in these characteristics, there is an operating point in which the maximum available power of PV is obtained. Fuzzy logic controller (FLC) is the artificial intelligent based maximum power point tracking (MPPT) method for obtaining the maximum power point (MPP). In this method, defining the logical rule and specific range of membership function has the significant effect on achieving the best and desirable results. This paper presents a detailed comparative survey of five general and main fuzzy logic subsets used for FLC technique in DC-DC boost converter. These rules and specific range of membership functions are implemented in the same system and the best fuzzy subset is obtained from the simulation results carried out in MATLAB. The proposed subset is able to track the maximum power point in minimum time with small oscillations and the highest system efficiency (95.7%). This investigation provides valuable results for all users who want to implement the reliable fuzzy logic subset for their works.

Pollution in Southeast Asia is a major public energy problem and the cause of energy losses. A significant problem with respect to this type of pollution is that it decreases energy yield. In this study, two types of photovoltaic (PV) solar arrays were used to evaluate the effect of air pollution. The performance of two types of solar arrays were analysed in this research, namely, two units of a 1 kWp tracking flat photovoltaic (TFP) and two units of a 1 kWp fixed flat photovoltaic arrays (FFP). Data analysis was conducted on 2,190 samples at 30 min intervals from 01st June 2013, when both arrays were washed, until 30th June 2013. The performance was evaluated by using environmental data (irradiation, temperature, dust thickness, and air pollution index), power output, and energy yield. Multiple regression models were predicted in view of the environmental data and PV array output. Results showed that the fixed flat system was more affected by air pollution than the tracking flat plate. The contribution of this work is that it considers two types of photovoltaic arrays under the Southeast Asian pollution 2013.