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This article presents an artificial neural network (ANN)-based approach for predicting photovoltaic (PV) module temperature using meteorological variables. The proposed approach utilizes actual hourly records of various meteorological parameters, such as ambient temperature Ta, solar irradiation G, relative humidity RH, and wind speed Ws as input variables. The hourly meteorological data were collected over 9 months in the year 2009 from a 92-kWp installed PV system in Selangor, Malaysia. The data were divided into two sets: training data, which are a set of 1849 (April-October) hourly data, and 578 (November-December) hourly records of working as test data. Four ANN models have been developed by using different combination of meteorological parameters as inputs, and, for each model, the output is the PV module temperature Tm. It was found that the model using all parameters, including RH and Ws as inputs, gave the most accurate results with correlation coefficient ( r) 95.9%, and 0.41, 0.1, and 4.5% for MBE, RMSE, and MPE, respectively. To show the superiority and applicability of the developed ANN model, results from the proposed ANN model have been compared with the conventional model adopted by Malaysia Energy Center and another mathematical model based on regression. With the model's simplicity, the proposed approach can be used as an effective tool for predicting the PV module temperature, for any type of PV systems, in remote or rural locations with no direct measurement equipments. The developed model also will be very useful in studying PV system performance and estimating its energy output. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This article presents solar energy or specifically the solar photovoltaic (PV) development outlook in Malaysia. The paper first introduces the massive potential of solar energy in the country, the key players in the solar energy development and the early solar energy policies, and programmes in the country. The most important to the PV development is the Malaysia Building Integrated Photovoltaic initiative, which is presented in this paper followed by an explanation on the Feed-in Tariff recently introduced in the country to encourage new solar PV projects. The outlook for solar PV in Malaysia is optimistic and as the uptake of solar PV increases, the unit cost is coming down rapidly. Solar PV is expected to be the most competitive Renewable Energy (RE) source, with the potential to achieve grid parity for electrical power in the country in the near future, and surpassing all other REs combined by 2050. [ABSTRACT FROM PUBLISHER]