It is estimated that oil reserves will not last very much longer; thus, a switch to alternative energy solutions is crucial. The Malaysian government has already prepared to face the situation decades before. Many policies have been implemented, as well as programmes and initiative. Now, Malaysia is waiting for the ultimate solutions, the Malaysian Fit-in Tariff (FiT), which is scheduled to be implemented second quarter of 2011. This paper presents the main sources of alternative renewable energy in Malaysia and its potential as well as the main reasons Malaysia is turning to alternative energy solutions; to fully utilize its renewable energy (RE) resources, fulfill the energy demand in the future and to reduce carbon emissions. This paper also discusses the steps taken by the government in preparation for FiT and overcoming the barriers in RE development.

The Malaysian Government has set an ambitious target to achieve a higher penetration of Renewable Energy (RE) in the Malaysian energy mix. To date, Malaysia has approximately 2% of its energy coming from RE generation sources compared to the total generation mix and targets achieving 20% penetration by 2025. The current energy mix for Malaysia power generation is mainly provided by natural gas and coal. The discussion will cover the traditional sources of generation including natural gas, coal and big hydro stations. In addition, the paper will cover in depth the potential of RE in the country, challenges, and opportunities in this sector. This study can give an initial evaluation of the Malaysian energy industry, especially for RE and can initiate further research and development in this area in order to support the Government target to achieve RE target of 20% by 2025.

Improper placement of distributed generation (DG) units in power systems would not only lead to an increased power loss, but could also jeopardise the system operation. To avert these scenarios and tackle this optimisation problem, this study proposes an effective method to guide electric utility distribution companies (DISCOs) in determining the optimal size and best locations of DG sources on their power systems. The approach, taking into account the system constraints, maximises the system loading margin as well as the profit of the DISCO over the planning period. These objective functions are fuzzified into a single multi-objective function, and subsequently solved using genetic algorithm (GA). In the GA, a fuzzy controller is used to dynamically adjust the crossover and mutation rates to maintain the proper population diversity (PD) during GA's operation. This effectively overcomes the premature convergence problem of the simple genetic algorithm (SGA). The results obtained on IEEE 6-bus and 30-bus test systems with the proposed method are evaluated with the simulation results of the classical grid search algorithm, which confirm its robustness and accuracy. This study also demonstrates DG's economic viability relative to upgrading substation and feeder facilities, when the incremental cost of serving additional load is considered.

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Strong and huge interests on smart grid have increased extensively in recent years around the world. This scenario could be a promising reason for future research in this area. This next form of electricity grid will be able to manage various parts of power production from power plants to the customers. Smart grid has become a major challenge in developed nations in both research and utilization aspects. On the other side, application of smart grid in developing countries is still lagging behind as compared to the developed ones. However, most of developing nations are currently investigating potentials of some pilot projects or few research works. In this article, the applied activities in developing countries for smart grid are reviewed and categorized into two major groups: group of pioneer developing countries in smart grid and other developing countries are placed in another group. The findings demonstrate that a few countries such as China, India and Brazil have had proper planning and development in this technology. In some cases like China, the efforts are considered comparable with developed nations like U.S. Therefore, according to the development progress for smart grid in China, India and Brazil, a pattern of reference for other developing countries is suggested.

This paper presents a solar power modelling method using artificial neural networks (ANNs). Two neural network structures, namely, general regression neural network (GRNN) feedforward back propagation (FFBP), have been used to model a photovoltaic panel output power and approximate the generated power. Both neural networks have four inputs and one output. The inputs are maximum temperature, minimum temperature, mean temperature, and irradiance; the output is the power. The data used in this paper started from January 1, 2006, until December 31, 2010. The five years of data were split into two parts: 2006–2008 and 2009-2010; the first part was used for training and the second part was used for testing the neural networks. A mathematical equation is used to estimate the generated power. At the end, both of these networks have shown good modelling performance; however, FFBP has shown a better performance comparing with GRNN.

The limited availability of fossil energy carriers and environmental impact of energy consumption demand mid-and long-term strategies both for the rational use of energy and for increased renewable energy utilization. Despite the establishment of the National Energy Policy, there is still an obstacle in reaching those objectives and targets. In the 7th Malaysia Plan for instance, the government has highlighted that a third of the Government's total allocation of RM469 million for rural electrification programmes under the has been allocated for the provision of solar powered installations for rural and remote communities. This paper outlines a detailed description of various existing solar technologies, the understanding of each technology and its associated challenges, which will provide a suitable basis to recognize advantages and drawbacks in its implementation in Malaysia. The paper finally justifies some of the barriers in promoting the full scale utilization for the solar energy in Malaysia.

The study assessed the effect of conscious halal slaughter and slaughter following minimal anesthesia on bleeding efficiency of goats and keeping quality of goat meat. Ten Boer cross bucks were divided into two groups and subjected to either halal slaughter without stunning (HS) or minimal anesthesia prior to slaughter (AS). The blood lost during exsanguination was measured. Residual blood was further quantified by determination of hemoglobin and myoglobin content in longissimus lumborum muscle. Storage stability of the meat was evaluated by microbiological analysis and lipid oxidation. Blood loss at exsanguination, residual hemoglobin and lipid oxidation were not significantly different (p>0.05) between HS and AS. Lactic acid bacteria was the only microbe that was significantly elevated after 24h of storage at 4°C in the AS group. In conclusion, slaughtering goats under minimal anesthesia or fully conscious did not affect bleeding efficiency and keeping quality of goat meat.