چكيده به لاتين
Due to the increasing population growth and industrialization in societies, human need for using fossil fuels follows an upward trend. In spite of high reliability of fossil fuels, because of abundant pollution created by them and adverse effect on environment, considerable attention is paid to renewable energy sources like wind and solar in both academic, and practical.
Using renewable energy sources like wind and solar in format of distributed generation (DG) power plants, in addition to decreasing detrimental effect on environment, is more considered by energy policy makers in terms of economical and technical aspects such as lower foundation cost and reduction of voltage fluctuation. Choosing the best location for installing DG power plants that use wind and solar sources depends on numerous factors. In this study and in first step, using data envelopment analysis (DEA) and factors affecting on DG performance, we specify the potential locations with higher efficiency for establishing DG power plants. In this research, by developing a mixed integer mathematical programming model, decisions like location of DG power plants in different fortification level (locations obtained from previous step), production amount in large-scale and DG power plants and flow between network different nodes are made. To deal with disruption risk, different fortification level for DG power plants are considered so that the higher the fortification level, the more cost and the less vulnerability in the face of disruption.
For modeling disruption risk in this problem and considering decision maker’s risk-aversion degree, robust stochastic approach is applied. Some of the input parameters used in mathematical modeling such as demand and costs are epistemic so that for dealing with this kind of uncertainty, possibilistic fuzzy programming with credibility measure is utilized. Presented model is a multi –objective mixed integer linear programming that using applying TH method is converted to a single objective model. Developed model is solved in GAMS using Cplex Solver. Guilan power generation and distribution network is utilized as a case study, and sensivity analysis is carried out on some critical parameters, and managerial and practical insights are presented.
Results in high level of confidence show that two DG power plants should be constructed in Kiashahr and Anzali in third fortification level (With the lowest cost). Each of these DG power plants is connected to one demand point in their covering radius and improves the power network. Obtained results reveal that with increasing in risk-aversion of DM, system costs follow an increasing trend due to growth in production volume in both large scale and DG power plants and also increasing in transmission and operational costs.
