The Republic of Kazakhstan has significant deposits of fossil fuels and is one of the largest energy producers among the countries of Central Asia. At the same time, The Republic of Kazakhstan is one of the richest countries of the world in terms of renewable resources, evaluated to over 1000 billion kWh/year. The application of therenewable energy sources (RES), both on a large scale and at the level of a single household, ensures the transformation of the energy system to a ''green state''. However, these initiatives should be substantiated by relevant supportive information to promote transformation of the country's economy to a qualitative ecological state.The paper covers developed multi-criteria decision-making system (MCDM) and software tools for processing of spatial heterogeneous data which could be applied for evaluation of the RES potential.The developed system serves to evaluate the potential of usable RES as it allows the assessment of a territory of the country in terms of installing photovoltaic and wind generators.A feature of the proposed MCDM is the use of an analytical hierarchical process (AHP) in combination with the Bayesian approach, which allows obtaining two complementary assessments of the territory areas. The method allows a rough estimate in an event of lack of data.The verification performed based on the available data on the installed solar and wind power stations shows that the system gives a relatively small root-mean-square error within 15%.INDEX TERMS Decision making support methods, geo information systems, intelligent information technologies, heterogeneous data, machine learning, renewable energy, spatially distributed resources, spatial decision making (SDM), multiple-criteria decision analysis, multiple-criteria decision making (MCDM).

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The chapter considers information systems that provide analysis of the RES resource base and support decision making. RES resources in the Republic of Kazakhstan are briefly analyzed. The methods and systems for evaluation of theoretical, technical, and economic potential of renewable energy sources are considered. Based on this overview, the authors propose six steps of estimation that should be realized in intellectual GIS. One of the major steps is the identification the factors that affect using of renewable energy sources. These factors can contribute to impeding the development of green energy. The simple taxonomy of these factors is proposed. The second important step is to aggregate estimations of the factors. As a result, the authors propose the aggregation method based on Bayes rule. Compared to other methods, this approach allows us to obtain two estimates: probabilities of positive and negative hypotheses. The methods discussed are at the heart of the information system supporting the development of renewable energy sources in the Republic of Kazakhstan.

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The chapter considers information systems that provide analysis of the RES resource base and support decision making. RES resources in the Republic of Kazakhstan are briefly analyzed. The methods and systems for evaluation of theoretical, technical, and economic potential of renewable energy sources are considered. Based on this overview, the authors propose six steps of estimation that should be realized in intellectual GIS. One of the major steps is the identification the factors that affect using of renewable energy sources. These factors can contribute to impeding the development of green energy. The simple taxonomy of these factors is proposed. The second important step is to aggregate estimations of the factors. As a result, the authors propose the aggregation method based on Bayes rule. Compared to other methods, this approach allows us to obtain two estimates: probabilities of positive and negative hypotheses. The methods discussed are at the heart of the information system supporting the development of renewable energy sources in the Republic of Kazakhstan.