Support vector machine based prediction of photovoltaic module and power station parameters

ABSTRACT

The uncertainty in the output power of the photovoltaic (PV) power generation station due to variation in meteorological parameters is of serious concern. An accurate output power prediction of a PV system helps in better design and planning. The present study is carried out for the prediction of output power of PV generating station by using Support Vector Machines. Two cases are considered in the present study for prediction. Case-I deals with the prediction of PV module parameters such as V_oc, I_sh, R_s, R_sh, I_max, V_max, P_max, and case-II deals with the prediction of power generation parameters such as P_DC, P_AC, and system efficiency. Historical data of PV power station with an installed capacity of 10 MW and weather information are used as input to develop four different seasons-based SVM models for all parameters. The performance results of the models are presented in terms of Mean Relative Error (MRE) and Root Mean Square Error (RMSE). Additionally, the performance results obtained with polynomial and Radial Based Function kernel are also compared to show that which kernel has better prediction accuracy, and practicability. The result shows that the minimum average RMSE and MRE for case-I with Radial Based Function kernel are 0.034%, 0.055%, 0.002%, 1.726%, 0.044%, 0.047%, 2.342%, and 0.005%, 0.014%, 0.079%, 0.885%, 0.005%, 0.007%, 0.013%, and for case-II with poly kernel are 0.014%, 0.016%, 0.149% and 0.011%, 0.0175, 1.03%, respectively. The present study will be helpful to provide technical guidance to the prediction of the PV power System.     

Urinary arsenic,cadmium, manganese,nickel, and vanadium levels of schoolchildren in the vicinity of the industrialised area of Asaluyeh,Iran

Asaluyeh is one of the most heavily industrialised areas in the world where gas, petrochemical, and many downstream industries are located. This study aims to survey the biomonitoring of four metals and one metalloid in children living in the vicinity of Asaluyeh area. To do this, we analysed the creatinine-adjusted urinary levels of arsenic (As), cadmium (Cd), vanadium (V), manganese (Mn), and nickel (Ni) in 184 elementary schoolchildren (99 boys and 85 girls) living in Asaluyeh and compared them with a reference population. The comparisons were done for two seasons (spring and fall). The results showed that in the case area (Asaluyeh), the levels of As, V, Mn, and Ni were significantly higher and that of Cd was not significantly higher than the reference city for both seasons. The mean concentration of metal(loid)s in Asaluyeh (case) and Sadabad (reference) area as μg g^?1 creatinine was As 2.90 and 2.24, V 0.06 and 0.03, Mn 0.28 and 0.25, Ni 0.54 and 0.29, and Cd 0.31 and 0.28 in spring and As 3.08 and 2.28, V 0.07 and 0.03, Mn 0.30 and 0.26, Ni 0.91 and 0.30, and Cd 0.36 and 0.31 in the fall. Seasonal variations played a key role in determining urinary metal(loid) concentration, as we saw the significant level of As, Cd, V, and Ni in fall than in spring. With regard to the impact of gender on the absorption and accumulation of urinary metal(loid)s, boys showed higher levels of the studied elements, especially for As, than girls as outdoor activities are more popular among boys. Due to the values being lower than those reported in literature, more research is needed on various population groups and other exposure sources in order to judge whether living in the vicinity of the gas and petrochemical industries in Asaluyeh is a threat to nearby residents.     

An alternative approach for delineating eco-sensitive zones around a wildlife sanctuary applying geospatial techniques

The dynamics, degradation, and conservation of forest ecosystems are matters of prime concerns worldwide at the present. Proper planning and management of a forest area are essentially needed to protect it from the grasp of burgeoning pressure of urban-industrial sprawl. Establishment of eco-sensitive zones (ESZs), which act as buffer areas around the core forests, is one of the key approaches towards achieving this goal. This paper deals with the applicability of geospatial techniques to identify the ESZ around an Indian wildlife sanctuary following the different rules and acts prescribed by the Government of India. Gumti Wildlife Sanctuary, located in the northeastern state of Tripura in India, has been selected here as a case study. Collected pieces of information on the distribution of biodiversity and human population in the area were also used to make the approach more holistic. As inferred from this study, remote sensing and geographical information systems were found to be easily implementable and time as well as cost-effective tools for this purpose with a distinct advantage of spatial as well as temporal accuracy in identifying the existing land use and land cover patterns in pilot assessments. However, the results indicated that only appropriate hybridization of field-based information on the biodiversity and ecological aspects of the forest as well as patterns of human interferences with the remote sensing and GIS-based data could make this approach more relevant in actual implementations.     

Multifarious revolutionary aspects of microbial keratinases: an efficient green technology for future generation with prospective applications

Environmental Science and Pollution Research - Since the dawn of century, tons of keratin bio-waste is generated by the poultry industry annually, and they end up causing environmental havoc....     

Designing a sustainable reverse logistics channel: the 18 generic structures framework

Remanufacturing end-of-life products requires setting up an economically and environmentally viable reverse logistics channel for supplying reusable used modules to the production chain. This paper introduces a framework to allow generating and assessing different reverse logistics channel structures. The framework is then applied to a product remanufacturing case. We analyze the current reverse logistics channel structure and propose alternative structures with less environmental impact and higher economic benefits.     

Field data: a study on trend and prediction of fatal traffic injuries prevalence in Shanghai

OBJECTIVE: The main objectives of the study are to analyze fatal traffic-injury trends in 1987-2003 in Shanghai and predict its prevalence in near future and provide scientific data for the local governmental decision on developing practical working methods on traffic-injury prevention and control. METHODS: In this study, epidemiological method and Grey dynamic model GM (1,1) were introduced to analyze and forecast traffic-injury mortality rates respectively. RESULTS: There was an apparent increasing trend of traffic-related injuries in Shanghai from 1987 to 2003 with the rate of growth in motorization. The average rates of annual increase are 3.59% in fatalities (from 7.78 per 100,000 population to 14.18 per 100,000 population) during the period. Pedestrians were the most common type of victims (29.6%), followed by bicyclists (25.1%), and motorcyclists (24.1%). Males accounted for the majority of all victims, over 69%. The population of high-school and lower high-school education level represented 66.4% victims of total road-traffic injuries. And if no special factors effect its development, the traffic fatalities would be up to 17.84 per 100,000 population in 2010, when calculating from equations we found and validated Y(t) = 359.90 x e0.027(t-1)-352.13, (t = 1, 2, ..., N) for Shanghai. CONCLUSION: Our data indicate the risk of fatal traffic injuries has increased in recent years and will go on growing in the near future in Shanghai. The findings showed that Grey dynamic model GM (1,1) is eligible on the prediction and can be a tool for injuries forecasting, implementing effective policies, programs, and interventions for reducing traffic injuries in the big cities.     

Vehicle pollution toxicity induced changes in physiology,defence system and biochemical characteristics of Calotropis procera L.

The present study aims to examine the physiological, biochemical and defence system responses of Calotropis procera to vehicle exhaust pollution. We selected various sample sites along two major roads in the Punjab province of Pakistan, i.e. Faisalabad to Sargodha road (FSR) and Pindi Bhattian to Lillah motorway (M-2). Traffic density at all sites and plant responses (i.e. chlorophyll a, chlorophyll b, total chlorophyll and carotenoid contents, transpiration rate, stomatal conductance, photosynthetic rate, sub-stomatal CO₂ concentration, water use efficiency, total free amino acids, total soluble proteins and total antioxidant activity) were measured. Levels of carbon (C) and nitrogen (N) and four metals of most possible concern – i.e. lead (Pb), zinc (Zn), cadmium (Cd) and nickel (Ni) – were also examined in all samples. We found their considerable deposition in all the samples along roads. Inhibitory effects of roadside pollutants were noted for photosynthetic pigments, stomatal conductance, transpiration rate, photosynthetic rate and total soluble proteins, whereas stimulatory effects were noted for sub-stomatal CO₂ concentration, free amino acids and total antioxidant activity. The stimulation of antioxidant enzymes activity revealed stress and mitigation of reactive oxygen species. The present study clearly signifies that C. procera has great potential to endure the stress caused by roadside pollutants.     

Effects of catholyte conditioning on electrokinetic extraction of copper from mine tailings

Effect of electrokinetic treatment on copper partitioning and distribution in mine tailings were studied. In particular the effects of catholyte enhancement by HAc-NaAc, HCl, HAc-NaAc+EDTA and lactic acid+NaOH were evaluated. The results show that conditioning the catholyte plays a very important role in improving Cu removal. When HAc-NaAc is used in the catholyte, the removal percentage of total Cu from the mine tailings sample reached 12.3% under 40 V in 15 days of treatment. The removal percentage of Cu increased to 31.2% when EDTA was used together with HAc-NaAc in the catholyte. At the same time, increasing the applied voltage and treatment time result in an increase in the Cu removal from the mine tailings. Compared with HAc-NaAc (pH=3.52), the use of lactic acid+NaOH (pH=3.15) in the catholyte resulted in better performance in Cu removal from the mine tailings. HCl treatment resulted in removal of about 17.5% of Cu from the mine tailings; however, it resulted in production of significant amounts of toxic chlorine gas. Copper partitioning in the mine tailings was analyzed before and after the electrokinetic treatments. The analysis was conducted using 0.25 mol/l MgCl2 and 0.5 mol/l HCl as extractants, consequently, to assess the mobility of Cu after treatment. The results showed that lowering the pH of the mine tailings increased the exchangeable Cu fraction (or the portion extracted by MgCl2). Accordingly, further acidification results in an increased mobility of Cu and increase in the environmental risk of mine tailings.     

Mapping pesticide contamination potential

Groundwater contamination by agricultural chemicals is a major environmental pollution issue nation-wide. The regulatory agencies of towns and counties face the problem of finding a methodology for assessing the ground-water contamination potential of a large number of agricultural pesticides. Because of the spatial nature of the problem and the limited data availability for comprehensive pesticide movement models, a contamination potential index was employed for preliminary assessment. A specially designed geographic information system was used to create ground-water contamination likelihood maps for a 1500 km² area. The results suggest that this methodology can be used successfully for evaluating the relative contamination potential of a large number of pesticides over large areas with limited input data. A tentative approach for using this method for monitoring and registration of pesticides is also discussed.