Wind energy potential assessment spatial decision support system

T. V. Ramachandra *, K. J. Rajeev, S. Vamsee Krishna, B. V. Shruthi
*Energy Research Group, Centre for Ecological Sciences, Indian Institute of Science. Bangalore 560 012, India
Citation: Ramachandra T.V., Rajeev K.J., Vamsee Krishna S., and Shruthi B.V., 2005. WEPA: Wind energy potential assessment - spatial decision support system, Energy Education Science and Technology, 14(2): 61-80.


A decision support system (DSS) is an interactive system that is able to produce data and information and in some cases, even promote understanding related to a given application domain in order to give useful assistance in resolving complex and ill-defined problems [1]. It
is a spatially based computer application or data that assists a researcher or planner in making decisions. It couples the intellectual resources of individuals with the capabilities of the computer to improve the quality decisions. Decision-making processes are analyzed from
different viewpoints and the implementation of analytical methods and models and support tools must take into consideration not only the organizational structure in question, but also the procedures, processes and the dynamics of the decision makers involved. DSS includes the analysis of integrated, subject oriented, spatial and temporal data, and assist in decision making by:

  1. Extending the decision maker's ability to tackle large-scale, time-consuming, complex problems;
  2. Shortening the time associated with making a decision;
  3. Improving the reliability of a decision process or outcome;
  4. Encourage exploration and discovery of the decision maker;
  5. Generating new evidence in support of a decision or confirmation of existing assumptions;
  6. Improving the decision maker's ability to process information and knowledge;
  7. Analyzing spatially the variability associated with the resources.

SDSS for assessing the wind potential is designed to assist the decision makers in regional planning in making appropriate decisions and also visualization of decisions.

1. 1. Wind energy

Solar energy falling on the earth produces large-scale motion of the atmosphere, on which is superimposed, local variations caused by several factors. Winds are caused by rotation of the earth and heating of the atmosphere by the sun. Due to the heating of the air at the equatorial regions, the air becomes lighter and starts to rise, and at the poles the cold air starts sinking. The rising air at the equator moves northward and southward. Differential heating of sea causes more minor changes in the flow of air. The nature of the terrain, ranging from mountains and valleys to more local obstacles such as buildings and trees, also has an important effect on the wind [2].

The power in the wind is proportional to the cube of the wind speed or velocity. It is therefore essential to have detailed knowledge of the wind and its characteristics, if the performance of wind turbines is to be estimated accurately. Various parameters need to be known of the wind energy are mean wind speed, directional data and velocity variations periodically daily/yearly/monthly and height of the anemometer. These parameters are used to assess the performance and economics of the wind plant.

Harnessing of wind energy could playa significant role in the energy mix of a region. Windmills have been used for centuries to grind grain and pump water in rural areas. Wind energy is renewable and environmentally benign. It has the advantage of being harnessed locally for applications in rural and remote areas. Wind driven electric generators could be utilized as an independent power source, and for purposes of augmenting the electricity supply from grids. In densely populated taluks, decentralized production of electricity would help local industries, especially seasonal agro-processing industries, etc.

The extent to which wind can be exploited as a source of energy depends on the probability density of occurrence different speeds. To optimize the design of a wind energy device, data on speed range over which the device must operate to maximize energy extractions are required, which requires the knowledge of frequency distribution of the wind speed. Data on mean monthly and annual wind speeds for a long time (30 - 50 years) are available at meteorological observatories and the data on frequency distribution is available from various locations. Various parameters need to be known of the wind energy are mean wind speed, directional data and velocity variations periodically - daily / yearly / monthly and height of the anemometer. These parameters are used to assess the performance and economics of the wind plant.

1. 2. Environmental issues

A comprehensive environmental assessment considering the following is required before the project implementation.

  1. Land use analysis: helps in assessing the changes in land use pattern for setting up wind energy stations.
  2. Ecological and Environmental Assessment: Impact on Flora and Fauna
  3. Visual and landscape assessment: a map is prepared showing those areas from which the wind turbines may be seen; more sophisticated techniques of visual assessment may be appropriate for larger projects.
  4. Noise assessment: to ensure the wind farm will not create any nuisance at local dwellings.
  5. Hydrological assessment: the impact of the proposed project on watercourses.
  6. Economic effects on local economy: includes an estimate of the number of permanent and temporary jobs, which may be created.
  7. Mitigating measures: ways in which any adverse environmental impact may be minimized.
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