Literature Review

A hypertext based DSS was developed to aid deployment of bioenergy systems. These approaches are discussed with reference to a short rotation forestry production information system and DSS for harvesting wood for energy from conventional forestry and short rotation forestry. Existing models and DSS were linked together to produce an integrated biomass electricity model, to investigate the interface between supply and conversion and to assess the impact of different feedstocks and conversion processes on the costs of generating electricity [3].

GIS based DSS was developed, which provides the tools to identify the geographic distribution of the economically important bioresources. The procedure introduces a four level analysis to determine the theoretical, available, technological and economically exploitable potential. The DSS handles all possible restrictions and candidate power plants are identified using an iterative procedure that locates bioenergy units and establishes the needed cultivated area for biomass collection. Electricity production cost is used as a criterion in the identification of the sites for biomass based power generation [10].

DSS was developed to assess the possibility of biomass exploitation for both thermal and electric energy production in a given area, while relating this use to an efficient and sustainable management of the forests within the same territory. In the proposed approach, geographic information system based techniques are integrated with mathematical programming methods to yield a comprehensive system that allows the formalization of the problem, decision taking and evaluation of effects. This DSS helps in identifying the optimal location for plants as well as computation of their optimal sizing (specifying energy types for the specific area), taking into account several aspects (economic, technical, regulatory and social) and deciding how to plan biomass collection and harvesting [2].

Using GIS, spatial mapping of the resources has been done for assessing the bioenergy potential for Karnataka state. Bioresource availability analysis shows that horticulture constitutes the major share of 43.6%, followed by forests (39.8%), agricultural residues (13.6%), animal residues (3.01%) and plantations (0.15%). Talukwise demand analysis shows that taluks such as Thirthahalli, Sirsi and Sagar have surplus bioresource compared to taluks such as Anekal, Malur, Gudibanda and Sidlaghatta. The computation of bioenergy availability, demand and talukwise status shows that Siddapura taluk in Uttara Kannada district has the highest bioenergy status of 2.004. Anekal taluk in Bangalore Urban district has the least status of 0.004 [8].

A spatial decision support system with algorithms specific for bioresources assessment and conservation was designed incorporating routines for forest mapping and monitoring changes at landscape level. It also provides inputs to decision--makers to deal with global issues such as global warming and understanding of carbon flux. Integration of biomass assessment and productivity models offered rapid and customized methods for resource estimation [11].