WEPA: Wind energy potential assessment-spatial decision support system

Spatial Decision Support System (SDSS) assist in strategic decision-making activities considering spatial and temporal variables, which help in Regional planning. WEPA is a SDSS designed for assessment of wind potential spatially. A wind energy system transforms the kinetic energy of the wind into mechanical or electrical energy that can be harnessed for practical use. Wind energy can diversify the economies of rural communities, adding to the tax base and providing new types of income. Wind turbines can add a new source of property value in rural areas that have a hard time attracting new industry. Wind speed is extremely important parameter for assessing the amount of energy a wind turbine can convert to electricity: The energy content of the wind varies with the cube (the third power) of the average wind speed. Estimation of the wind power potential for a site is the most important requirement for selecting a site for the installation of a wind electric generator and evaluating projects in economic terms. It is based on data of the wind frequency distribution at the site, which are collected from a meteorological mast consisting of wind anemometer and a wind vane and spatial parameters (like area available for setting up wind farm, landscape, etc.). The wind resource is governed by the climatology of the region concerned and has large variability with reference to space (spatial expanse) and time (season) at any fixed location. Hence the need to conduct wind resource surveys and spatial analysis constitute vital components in programs for exploiting wind energy. SDSS for assessing wind potential of a region / location is designed with user friendly GUI’s (Graphic User Interface) using VB as front end with MS Access database (backend). Validation and pilot testing of WEPA SDSS has been done with the data collected for 45 locations in Karnataka based on primary data at selected locations and data collected from the meteorological observatories of the India Meteorological Department (IMD). Wind energy and its characteristics have been analysed for these locations to generate user-friendly reports and spatial maps. Energy Pattern Factor (EPF) and Power Densities are computed for sites with hourly wind data. With the knowledge of EPF and mean wind speed, mean power density is computed for the locations with only monthly data. Wind energy conversion systems would be most effective in these locations during May to August. The analyses show that coastal and dry arid zones in Karnataka have good wind potential, which if exploited would help local industries, coconut and areca plantations, and agriculture. Pre-monsoon availability of wind energy would help in irrigating these orchards, making wind energy a desirable alternative.

Comparative Assessment of Techniques for Bioresource Monitoring Using GIS and Remote Sensing

Growing concern over the status of global and regional bioenergy resources has necessitated the analysis and monitoring of land cover and land use parameters on spatial and temporal scales. The knowledge of land cover and land use is very important in understanding natural resources utilization, conversion and management. Land cover, land use intensity and land use diversity are land quality indicators for sustainable land management. Optimal management of resources aids in maintaining the ecosystem balance and thereby ensures the sustainable development of a region. Thus sustainable development of a region requires a synoptic ecosystem approach in the management of natural resources that relates to the dynamics of natural variability and the effects of human intervention on key indicators of biodiversity and productivity. Spatial and temporal tools such as remote sensing (RS), geographic information system (GIS) and global positioning system (GPS) provide spatial and attribute data at regular intervals with functionalities of a decision support system aid in visualisation, querying, analysis, etc., which would aid in sustainable management of natural resources. Remote sensing data and GIS technologies play an important role in spatially evaluating bioresource availability and demand. This paper explores various land cover and land use techniques that could be used for bioresources monitoring considering the spatial data of Kolar district, Karnataka state, India. Slope and distance based vegetation indices are computed for qualitative and quantitative assessment of land cover using remote spectral measurements. Differentscale mapping of land use pattern in Kolar district is done using supervised classification approaches. Slope based vegetation indices show area under vegetation range from 47.65 % to 49.05% while distance based vegetation indices shoes its range from 40.40% to 47.41%. Land use analyses using maximum likelihood classifier indicate that 46.69% is agricultural land, 42.33% is wasteland (barren land), 4.62% is built up, 3.07% of plantation, 2.77% natural forest and 0.53% water bodies. The comparative analysis of various classifiers, indicate that the Gaussian maximum likelihood classifier has least errors. The computation of talukwise bioresource status shows that Chikballapur Taluk has better availability of resources compared to other taluks in the district.

Solar energy potential assessment using GIS

Renewable energy resources are those having a cycling time less than 100 years and are renewed by the nature and their supply exceeds the rate of consumption. Renewable energy systems use resources that are constantly replaced in nature and are usually less polluting. In order to tap the potential of renewable energy sources, there is a need to assess the availability of resources spatially as well as temporally. Geographic Information Systems (GIS) along with Remote Sensing (RS) helps in mapping on spatial and temporal scales of the resources and demand. The spatial database of resource availability and the demand would help in the regional energy planning. This paper discusses the application of geographical information system (GIS) to map the solar potential in Karnataka state, India. Regions suitable for tapping solar energy are mapped on the basis of global solar radiation data, and this analysis provides a picture of the potential. The study identifies that Coastal parts of Karnataka with the higher global solar radiation is ideally suited for harvesting solar energy. The potential analysis reveals that, maximum global solar radiation is in districts such as Uttara Kannada and Dakshina Kannada. Global solar radiation in Uttara Kannada during summer, monsoon and winter are 6.31, 4.40 and 5.48 kWh/sq.m, respectively. Similarly, Dakshina Kannada has 6.16, 3.89 and 5.21 kWh/sq.m during summer, monsoon and winter.

Ecological Assessment of Lentic Water Bodies of Bangalore

The restoration, conservation and management of water resources require a thorough understanding of what constitutes a healthy ecosystem. Monitoring and assessment provides the basic information on the condition of our waterbodies. The present work details the study carried out at two waterbodies, namely, the Chamarajasagar reservoir and the Madiwala Lake. The waterbodies were selected on the basis of their current use and locations. Chamarajasagar reservoir serves the purpose of supplying drinking water to Bangalore city and is located on the outskirts of the city surrounded by agricultural and forest land. On the other hand, Madiwala lake is situated in the heart of Bangalore city receiving an influx of pollutants from domestic and industrial sewage. Comparative assessment of the surface water quality of both were carried out by instituting the various physico–chemical and biological parameters. The physico-chemical analyses included temperature, transparency, pH, electrical conductivity, dissolved oxygen, alkalinity, total hardness, calcium hardness, magnesium hardness, nitrates, phosphates, sodium, potassium and COD measurements of the given waterbody. The analysis was done based on the standard methods prescribed (or recommended) by (APHA) and NEERI. The biological parameter included phytoplankton analysis. The detailed investigations of the parameters, which are well within the tolerance limits in Chamarajasagar reservoir, indicate that it is fairly unpolluted, except for the pH values, which indicate greater alkalinity. This may be attributed to the natural causes and the agricultural runoff from the catchment. On the contrary, the limnology of Madiwala lake is greatly influenced by the inflow of sewage that contributes significantly to the dissolved solids of the lake water, total hardness, alkalinity and a low DO level. Although, the two study areas differ in age, physiography, chemistry and type of inflows, they still maintain a phytoplankton distribution overwhelmingly dominated by Cyanophyceae members,specifically Microcystis aeruginosa. These blue green algae apparently enter the waterbodies from soil, which are known to harbour a rich diversity of blue green flora with several species common to limnoplankton, a feature reported to be unique to the south Indian lakes.Chamarajasagar water samples revealed five classes of phytoplankton, of which Cyanophyceae (92.15 percent) that dominated other algal forms comprised of one single species of Microcystis aeruginosa. The next major class of algae was Chlorophyceae (3.752 percent) followed by Dinophyceae (3.51 percent), Bacillariophyceae (0.47 percent) and a sparsely available and unidentified class (0.12 percent).Madiwala Lake phytoplankton, in addition to Cyanophyceae (26.20 percent), revealed a high density of Chlorophyceae members (73.44 percent) dominated by Scenedesmus sp.,Pediastrum sp., and Euglena sp.,which are considered to be indicators of organic pollution. The domestic and industrial sewage, which finds its way into the lake, is a factor causing organic pollution. As compared to the other classes, Euglenophyceae and Bacillariophyceae members were the lowest in number. Thus, the analysis of various parameters indicates that Chamarajasagar reservoir is relatively unpolluted except for the high percentage of Microcystis aeruginosa, and a slightly alkaline nature of water. Madiwala lake samples revealed eutrophication and high levels of pollution, which is clarified by the physico–chemical analysis, whose values are way above the tolerance limits. Also, the phytoplankton analysis in Madiwala lake reveals the dominance of Chlorophyceae members, which indicate organic pollution (sewage being the causative factor).

Geographical Information System Approach for Regional Biogas Potential Assessment

The economic prosperity and quality of life in a region are closely linked to the level of its per capita energy consumption. In India more than 70% of the total population inhabits rural areas and 85-90% of energy requirement is being met by bioresources. With dwindling resources, attention of planners is diverted to viable energy alternatives to meet the rural energy demand. Biogas as fuel is one such alternative, which can be obtained by anaerobic digestion of animal residues and domestic and farm wastes, abundantly available in the countryside. Study presents the techniques to assess biogas potential spatially using GIS in Kolar district, Karnataka State, India. This would help decision makers in selecting villages for implementing biogas programmes based on resource availability. Analyses reveal that the domestic energy requirement of more than 60% population can be met by biogas option. This is based on the estimation of the per capita requirement of gas for domestic purposes and availability of livestock residues.

Quality Assurance and Assessment in Technical Education System: A Web Based Approach

Engineering education quality embraces the activities through which a technical institution satisfies itself that the quality of education it provides and standards it has set are appropriate and are being maintained. There is a need to develop a standardised approach to most aspects of quality assurance for engineering programmes which is sufficiently well defined to be accepted for all assessments.We have designed a Technical Educational Quality Assurance and Assessment (TEQ-AA) System, which makes use of the information on the web and analyzes the standards of the institution. With the standards as anchors for definition, the institution is clearer about its present in order to plan better for its future and enhancing the level of educational quality.The system has been tested and implemented on the technical educational Institutions in the Karnataka State which usually host their web pages for commercially advertising their technical education programs and their Institution objectives, policies, etc., for commercialization and for better reach-out to the students and faculty. This helps in assisting the students in selecting an institution for study and to assist in employment.

Dynamics of rural energy access in India: An assessment

India's rural energy challenges are formidable with the presence of majority energy poor. In 2005, out of a rural population of 809 million, 364 million lacked access to electricity and 726 million to modern cooking fuels. This indicates low effectiveness of government policies and programs of the past, and need for a more effective approach to bridge this gap. However, before the government can address this challenge, it is essential that it gain a deeper insight into prevailing status of energy access and reasons for such outcomes. Toward this, we perform a critical analysis of the dynamics of energy access status with respect to time, income and regions, and present the results as possible indicators of effectiveness of policies/programmes. Results indicate that energy deprivations are highest for poorest households with 93% depending on biomass for cooking and 62% lacking access to electricity. The annual growth rates in expansion in energy access are gradually declining from double digit growth rates experienced 10 years back to just around 4% in recent years. Regional variations indicate, on an average, cooking access levels were 5.3 times higher in top five states compared to bottom five states whereas this ratio was 3.4 for electricity access. (C) 2011 Elsevier Ltd. All rights reserved.

Self Assessment-Based Decision Making for Multiagent Cooperative Search

This paper addresses a search problem with multiple limited capability search agents in a partially connected dynamical networked environment under different information structures. A self assessment-based decision-making scheme for multiple agents is proposed that uses a modified negotiation scheme with low communication overheads. The scheme has attractive features of fast decision-making and scalability to large number of agents without increasing the complexity of the algorithm. Two models of the self assessment schemes are developed to study the effect of increase in information exchange during decision-making. Some analytical results on the maximum number of self assessment cycles, effect of increasing communication range, completeness of the algorithm, lower bound and upper bound on the search time are also obtained. The performance of the various self assessment schemes in terms of total uncertainty reduction in the search region, using different information structures is studied. It is shown that the communication requirement for self assessment scheme is almost half of the negotiation schemes and its performance is close to the optimal solution. Comparisons with different sequential search schemes are also carried out. Note to Practitioners-In the futuristic military and civilian applications such as search and rescue, surveillance, patrol, oil spill, etc., a swarm of UAVs can be deployed to carry out the mission for information collection. These UAVs have limited sensor and communication ranges. In order to enhance the performance of the mission and to complete the mission quickly, cooperation between UAVs is important. Designing cooperative search strategies for multiple UAVs with these constraints is a difficult task. Apart from this, another requirement in the hostile territory is to minimize communication while making decisions. This adds further complexity to the decision-making algorithms. In this paper, a self-assessment-based decision-making scheme, for multiple UAVs performing a search mission, is proposed. The agents make their decisions based on the information acquired through their sensors and by cooperation with neighbors. The complexity of the decision-making scheme is very low. It can arrive at decisions fast with low communication overheads, while accommodating various information structures used for increasing the fidelity of the uncertainty maps. Theoretical results proving completeness of the algorithm and the lower and upper bounds on the search time are also provided.