<span>The main components of a Stand-Alone Photovoltaic (SAPV) system consists of PV array, DC-DC converter, load and the maximum power point tracking (MPPT) control algorithm. MPPT algorithm was used for extracting maximum available power from PV module under a particular environmental condition by controlling the duty ratio of DC-DC converter. Based on maximum power transfer theorem, by changing the duty cycle, the load resistance as seen by the source is varied and matched with the internal resistance of PV module at maximum power point (MPP) so as to transfer the maximum power. Under sudden changes in solar irradiance, the selection of MPPT algorithm’s sampling time (T_{S_MPPT}) is very much depends on two main components of the converter circuit namely; inductor and capacitor. As the value of these components increases, the settling time of the transient response for PV voltage and current will also increase linearly. Consequently, T_{S_MPPT}needs to be increased for accurate MPPT and therefore reduce the tracking speed. This work presents a design considerations of DC-DC Boost Converter used in SAPV system for fast and accurate MPPT algorithm. The conventional Hill Climbing (HC) algorithm has been applied to track the MPP when subjected to sudden changes in solar irradiance. By selecting the optimum value of the converter circuit components, a fast and accurate MPPT especially during sudden changes in irradiance has been realized.</span>

No abstract

<span lang="EN-US">With the proliferation of numerous soft computing (SC)–based maximum power point tracking (MPPT) algorithms for photovoltaic (PV) systems, determining which algorithm performs better than others is becoming increasingly difficult. This is primarily due to the absence of standardized methods to benchmark their performances using consistent and systematic procedures. Moreover, the module technology, power ratings, and environmental conditions reported by numerous publications all differ. Based on these concerns, this paper presents a critical evaluation of the five most important and recent SC-based MPPTs, namely, genetic algorithm (GA), cuckoo search (CS), particle swarm optimization (PSO), differential evolution (DE), and evolutionary programming (EP). To perform a fair comparison, the initialization, selection, and stopping criteria for all methods are fixed in similar conditions. Thus, the performance is determined by its respective reproduction process. Simulation tests are performed using the MATLAB/SIMULINK environment. The performance of each algorithm is compared and evaluated based on its speed of convergence, accuracy, complexity, and success rate. The results indicate that EP appears to be the most promising and encouraging SC algorithm to be used in MPPT for a PV system under the multimodal partial shading condition.</span>

St. Louis Bay, along with its two major tributaries, Wolf River and Jourdan River, are included in the Mississippi 1998 Section 303(d) List for violation of the designated water use of recreation and shellfish harvesting. Fecal coliform was identified as one of the pollutants that caused the water quality impairment. In order to facilitate the total maximum daily loads (TMDL) development, the fecal coliform dynamics was investigated under 2 flow scenarios with a calibrated and validated modeling framework by integration of Environmental Fluid Dynamic Code (EFDC) and Hydrological Simulation Program Fortran (HSPF). EFDC was used to model the hydrodymics and fecal coliform transportation in the Bay and the tributaries, whereas HSPF was applied to compute the flow and fecal coliform loadings from the watersheds. The total amount of precipitation in the dry year simulation corresponds to a 50-year return period of low flow condition, and a 10-year return period of high flow condition for wet weather simulation. For EFDC modeling, the fecal coliform sources considered were the contributions from the 2 upper watersheds (no tidal influence), the 28 small surrounding watershed, and 12 municipal, industrial, and domestic point sources. When simulating the fecal coliform loadings from the 2 upper watersheds using HSPF, the simulated non-point source loadings of fecal coliform included wildlife, land application of hog and cattle manure, land application of poultry litter, and grazing animals. The EFDC modeling results indicated that the wet weather exerted greater stress on fecal coliform water quality conditions. The number of exceedance of fecal coliform water quality standard in wet year simulation is much higher than that in dry year simulation. The impact of the upper rural watersheds loads on fecal coliform levels in the St. Louis Bay is much less significant than that from the surrounding urban runoff. Fecal coliform TMDL development should be based on high flow conditions since the decision makers are more concerned about worse scenarios. This fecal coliform modeling research would provide useful information of critical condition selection for TMDLs development in similar coastal areas.

Malaysia is experiencing high economic growth which requires the construction industry to fulfill development demands. Building Information Modelling (BIM) had been widely publicized by the government in order to increase the industry’s productivity by instigating numerous initiatives aimed to spearhead its progression. In contrast with the aspiration, architects as key players of construction industry are still facing issues in adopting BIM into practice. Previous researches had broadly covered about BIM in construction industry, but few concentrations in specific to the local architect thus imposing gap of knowledge. In addressing the issues, the research aim to probe the current state of BIM implementation, primarily on the challenges that hinders its adoption. The BIM factors which covers people, process, policy and technology were derived and investigated through the use of 322 questionnaires distributed to architects at management and operational level. The study revealed the key barriers that contributes towards the problem is within the people factor, where majority highlighted the lacked of skilled and experienced BIM workforce which contributes towards steep learning environment as well as high cost of applying BIM. Consequently, several key strategic solutions had been indicated through both external and internal factors in addressing the challenge of BIM. Results suggested that there is a need of further support from the industry’s professional bodies, development of legal instruments, BIM enforcement, specific BIM education as well as BIM R&D programs.

Predicting the impact of climate change and human activities on river systems is imperative for effective management of aquatic ecosystems. Unique information can be derived that is critical to the survival of aquatic species under dynamic environmental conditions. Therefore, the response of a tropical river system under climate and land-use changes from the aspects of water temperature and dissolved oxygen concentration were evaluated. Nine designed projected climate change scenarios and three future land-use scenarios were integrated into the Hydrological Simulation Program FORTRAN (HSPF) model to determine the impact of climate change and land-use on water temperature and dissolved oxygen (DO) concentration using basin-wide simulation of river system in Malaysia. The model performance coefficients showed a good correlation between simulated and observed streamflow, water temperature, and DO concentration in a monthly time step simulation. The Nash-Sutcliffe Efficiency for streamflow was 0.88 for the calibration period and 0.82 for validation period. For water temperature and DO concentration, data from three stations were calibrated and the Nash-Sutcliffe Efficiency for both water temperature and DO ranged from 0.53 to 0.70. The output of the calibrated model under climate change scenarios show that increased rainfall and air temperature do not affects DO concentration and water temperature as much as the condition of a decrease in rainfall and increase in air temperature. The regression model on changes in streamflow, DO concentration, and water temperature under the climate change scenarios illustrates that scenarios that produce high to moderate streamflow, produce small predicted change in water temperatures and DO concentrations compared with the scenarios that produced a low streamflow. It was observed that climate change slightly affects the relationship between water temperatures and DO concentrations in the tropical rivers that we include in this study. This study demonstrates the potential impact of climate and future land-use changes on tropical rivers and how they might affect the future ecological systems. Most rivers in suburban areas will be ecologically unsuitable to some aquatic species. In comparison, rivers surrounded by agricultural and forestlands are less affected by the projected climate and land-uses changes. The results from this study provide a basis in which resource management and mitigation actions can be developed.

No abstract

No abstract