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Sensor-based agriculture monitoring systems have limited outcomes on the detection or counting of vegetables from agriculture fields due to the utilization of either conventional color transformations or machine learning-based methods. To overcome these limitations, this research is aimed at proposing an IoT-based smart agriculture monitoring system with multiple algorithms such as detection, quantification, ripeness checking, and detection of infected vegetables. This paper presents smart agriculture monitoring systems for Internet of Things (IoT) applications. The CHT has been applied to detect and quantify vegetables from the agriculture field. Using color thresholding and color segmentation techniques, defected vegetables have also been detected. A machine learning method-convolutional neural network (CNN) has been used for the development and implementation of all algorithms. A comparison between traditional methods and CNN has been simulated in MATLAB to find out the optimal method for its implementation in this agricultural monitoring system. Compared to the traditional methods, the CNN is the optimal method in this research work which performed better over the previously developed algorithms with an accuracy of more than 90%. As an example (case study), a tomato field in Chittagong, Bangladesh, was chosen where a camera-mounted mobile robot captured images from the agriculture field for which the proposed IoT-based smart monitoring system was developed. This system will benefit farmers through the digitally monitored output at an agriculture field in Bangladesh as well as in Malaysia. Since this proposed smart IoT-based system is still driven by bulky, costly, and limited powered sensors, in a future work, for the required power of sensors, this research work is aimed at the design and development of an energy harvester (hybrid) (HEH) based on ultralow power electronics circuits to generate the required power of sensors. Implementation of multiple algorithms using CNN, circular Hough transformation (CHT), color thresholding, and color segmentation methods for the detection, quantification, ripeness checking, and detection of infected crops. [ABSTRACT FROM AUTHOR]

The government has set an ambitious target of renewable energy development in Malaysia. As a promising renewable energy source, wind energy plays an important role in the Malaysia renewable energy roadmap. Compared to onshore wind energy, offshore wind resources with better quality can be provided in the areas away from the coast, which has greater potential to contribute to electricity generation. Wind and bathymetry conditions are two important factors that determine the feasibility and economics of offshore wind turbines. In this paper, an investigation is conducted on wind and bathymetry conditions around Malaysia. The data source mainly originates from the Global Wind Atlas. The conditions of the coastal areas in different states and federal territories of both Peninsular Malaysia and East Malaysia are analysed, with a specific focus on wind speed, wind energy density, and bathymetry conditions in high-wind-speed regions. The data and survey are verified and compared with the past published literature. This paper aims to investigate the wind and bathymetry conditions around Malaysia, assess the potential of offshore wind energy, discuss the feasibility of offshore wind turbines, and provide references for offshore wind development in Malaysia. [ABSTRACT FROM AUTHOR]

Solar energy serves as a great alternative to fossil fuels as they are clean and renewable energy. Accurate solar radiation (SR) prediction can substantially lower down the impact cost pertaining to the development of solar energy. Lately, many SR forecasting system has been developed such as support vector machine, autoregressive moving average and artificial neural network (ANN). This paper presents a comprehensive study on the meteorological data and types of backpropagation (BP) algorithms used to train and develop the best SR predicting ANN model. The meteorological data, which includes temperature, relative humidity and wind speed are collected from a meteorological station from Kuala Terrenganu, Malaysia. Three different BP algorithms are employed into training the model i.e., Levenberg–Marquardt, Scaled Conjugate Gradient and Bayesian Regularization (BR). This paper presents a comparison study to select the best combination of meteorological data and BP algorithm which can develop the ANN model with the best predictive ability. The findings from this study shows that temperature and relative humidity both have high correlation with SR whereas wind temperature has little influence over SR. The results also showed that BR algorithm trained ANN models with maximum R of 0.8113 and minimum RMSE of 0.2581, outperform other algorithm trained models, as indicated by the performance score of the respective models. [ABSTRACT FROM AUTHOR]

For a decade, distributed energy resources in Malaysia have growth as one of the paths in battling with sustainable energy crisis and environmental pollution. Several intriguing initiatives and incentives have been established to encourage the use and sales-side of renewable energy at the distribution consumers. However, Malaysia's distributed energy resources penetration is still at its slow pace, with only 7.6% (excluding large hydropower) shared in energy mix generation. Therefore, innovation in power systems is required to drive the uptake of distributed energy resources. This paper reviews the business model innovation that allows distributed energy resources to participate in national grid services and the wholesale electricity market. Different technical and non-technical challenges with high shares of variable renewable energy in power systems are highlighted, and the current update on compensation scheme, Net-Energy-Metering 3.0 is also discussed. Along with these challenges, stance the prospect of adopting distributed energy resources innovation projects such as peer-to-peer energy trading and virtual power plant in the electricity market. It could further furnish the benefits to a better environmental and power system in terms of carbon dioxide avoidance, grid flexibility and increase revenue for distributed energy resources owners respectively. Through the review, it led to observation that policy and regulatory in Malaysia are the main factors in accelerating the distributed energy resources deployment. Therefore, the abilities and roles of Malaysia Energy Commission and Sustainable Energy Development Authority as a regulator and implementing agencies are crucial in determining the present and future distributed energy resources business model. [ABSTRACT FROM AUTHOR]

The Sustainable Energy Development Authority of Malaysia (SEDA) regularly receives complaints about damaged components and distribution boards of PV systems due to lightning strikes. Permanent and momentary interruptions of distribution circuits may also occur from the disturbance. In this paper, a solar PV Rooftop system (3.91 kWp) provided by SEDA was modelled in the PSCAD/EMTDC. The Heidler function was used as a lightning current waveform model to analyse the transient current and voltage at two different points susceptible to the influence of lightning events such as different lightning current wave shape, standard lightning current and non-standard lightning current. This study examines the effect on the system components when lightning directly strikes at two different points of the installation. The two points lie between the inverter and the solar PV array and between inverter and grid. Exceptionally high current and voltage due to the direct lightning strike on a certain point of a PV Rooftop system was also studied. The result of this case study is observed with and without the inclusion of surge protective devices (SPDs). The parameters used were 31 kA of peak current, 10 metres cable length and lightning impulse current wave shape of 8/20μs. The high current and voltage at P1 striking point were 31 kA and 2397 kV, respectively. As for the AC part, the current and voltage values were found to be 5.97 kA and 5392 kV, respectively.Therefore, SPDs with suitable rating provided by SEDA were deployed. Results showed that high transient current voltage is expected to clamp sharply at the values of 1.915 kV and 0 A at the P1 striking point. As for the AC part, the current and voltage values were found to be 0 kA and 0.751 V, respectively. Varying lightning impulse current wave shapes at striking point P2 showed that the highest voltage was obtained at waveshape 10/350 μs at 11277 kV followed by wave shapes of 2/70 μs, 8/20 μs and 0.7/6 μs. The high value of transient voltage was clamped at a lower level of 2.029 kV. Different lightning amplitudes were also applied, ranging from 2–200 kA selected based on the CIGRE distribution. It showed that the current and voltage at P1 and P2 were directly proportional. Therefore, the SPD will be designed at an acceptable rating and proper position of SPD installation at solar PV Rooftop will be proposed. The results obtained in this study can then be utilised to appropriately assign a SPD to protect the PV systems that are connected to the grid. Installing SPDs without considering the needs of lightning protection zones would expose the expensive equipment to potential damage even though the proper energy coordination of SPDs is in place. As such, the simulation results provide a basis for controlling the impacts of direct lightning strikes on electrical equipment and power grids and thus justify SPD coordination to ensure the reliability of the system. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents models for diffuse solar energy on a horizontal surface for main five sites in Malaysia. The diffuse solar energy is modeled using linear, non-linear and ANN models. Three statistical values are used to evaluate the developed solar energy models, namely, the mean absolute percentage error, MAPE, root mean square error, RMSE and mean bias error, MBE. The results showed that the ANN models are superior compared to the other models in which the MAPE of the ANN model is 1.53%, while the MAPE of the linear and nonlinear models are 4.35% and 3.74%, respectively. The accurate ANN models can therefore be used to predict solar energy in Malaysia and nearby regions. [Copyright &y& Elsevier]

Urbanization in Kenya and perhaps in sub-Saharan Africa can be described as prescriptive rather than organic. We posit that this prescriptive urbanization can be checked and balanced by employing the governance model of devolution and rural capacity. We first review competing views on urbanization in Kenya during the colonial and postcolonial era and its contribution to disenfranchising both urban and rural inhabitants. We then examine devolution in Kenya through the lens of Lefebvre's theory of production of space and the right to the city, enabling us to contextualize and redefine 'the right to the city'. In the second part we analyze the potential of rural capacity in Malaysia to absorb a large influx of return immigrants and demonstrates how they have adapted and benefited from the prosperity of land in the face of diminishing energy resources and de-industrialization. We conclude that coupling devolution with rural capacity may hold the key to check rapid urbanization, especially in Kenya. [ABSTRACT FROM AUTHOR]

Abstract: Asia’s largest biofuels producers are currently Indonesia, Malaysia, the Philippines, Thailand, China and India. This paper first examines the current status of biofuels in these countries, including the national development targets, strategies, incentives and policies. It then identifies the fundamental driving forces behind the development and promotion of these industries and considers their economic, social and environmental impacts. [Copyright &y& Elsevier]

Background: The global commitment to climate change mitigation enforces the worldwide development of renewable energy sources. Therefore, various studies have investigated the growth of renewable energy in Malaysia, most commonly based on biogas and hydropower. In this article, the dynamics of Malaysia's renewable energy development is critically examined by using the latest official national reports and other reliable resources. Results: The study reveals the influencing factors that shape renewable energy growth in a developing country endowed with substantial biomass resources, such as Malaysia. Likewise, it evaluates the evolution of renewable energy in the electricity sector. In 2017, renewable energy represented about 3.5% of the Malaysian electricity generation mix with 1122 MW of installed capacity. A closer look into the renewable energy resources, i.e. biomass, biogas, solar and small hydro power, revealed that over 47% of the grid-connected power generation came from solar photovoltaic (PV) energy. While solar PV capacity continues to accelerate, the development of other renewable resources, especially biomass, is seeing growth at a significantly slower pace. This article investigates the underlying causes of the skewed development rate as well as the potential strategies that may be adopted to promote a diversification of renewable energy resources. In light of this, introduction of a new national bioenergy policy is proposed, through which four essential programmes could be implemented: (i) enhanced bioenergy conversion efficiency and waste management, (ii) biomass co-firing in coal power plants, (iii) conversion of biogas to biomethane and bio-compressed natural gas (bio-CNG), (iv) large-scale biomass power plants. A total of 4487 MW of additional power could be connected to the grid upon successful implementation of a large-scale biomass power plant programme. Conclusions: The establishment of a comprehensive and inclusive national bioenergy policy will lead towards a sustainable future of renewable energy development in Malaysia. [ABSTRACT FROM AUTHOR]

The present study aimed to investigate the psychosocial impacts of large-scale solar (LSS) power projects. There were 225 participants (n = 109 women, n = 3 did not indicate gender) participated in our study by completing a series of questionnaires. We found that participants who lived farther from the LSS power project location and those who viewed the project as being impactful were optimistic about the benefits LSS power projects could bring. Our participants also demonstrated support for renewable energy development in Malaysia. These findings may provide important implications for the implementation and execution of LSS power projects and policies. [ABSTRACT FROM AUTHOR]