According to the increasing in the usage of electricity, saving energy is so important. It can be occurred by both, optimizing consumption and the increasing of production efficiency. Small scale power plant (Distributed Generation (DG)) by reducing the distance of power production and consumption, declines a large part of this industry loss that is related to the distribution. The generators also have the ability to transform into the cogeneration system; As a result, by increasing efficiency, a great saving will happen in the production side of electricity industry. The issue of this article is the determination of priority of location of building DG. In this regard by using deviation from the optimum method and Human Development Index (HDI), according to data published by the Statistical Center of Iran and the Ministry of Energy, 9 provinces in the central area of Iran were selected and evaluated with 9 indicators. The results show that among the selected provinces the priority execution of power plant is first in Tehran, and then Isfahan.

Plant location selection has invariably a significant impact on the performance of many companies or manufacturing systems. In this paper, a new integrated methodology is structured to solve this selection problem. Two well-known decision making methods, namely analytic hierarchical process (AHP) and VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR), are combined in order to make the best use of information available, either implicitly or explicitly. In addition, the Delphi method is utilized to select the most influential criteria by a few experts. The aim of using the AHP is to give the weights of the selected criteria. Finally, the VIKOR method is taken into account to rank potential alternatives. Finally, an application example demonstrates the suitability of the proposed methodology.

One of the most important factors leading to the success of a cement plant is its location. A multicriteria decision-making method is used to rank alternative plant locations. The set of criteria is established and corresponding criteria should be established for each case study, although this multicriteria decision-making approach has broader applicability. In this paper, ELECTRE approach with five criteria is used to develop a location evaluation for Alumina - cement plant in East- Azerbaijan province of Iran. Five alternatives for the plant location are evaluated. The main criteria are transportation consideration, water supply, power supply, fuel supply and land consideration. Other criteria have the same importance as for five alternatives. Finally Alternatives are ranked and the best site is proposed.

One of the most important factors leading to the success of a cement plant is its location. A multicriteria decision-making method is used to rank alternative plant locations. The set of criteria is established and corresponding criteria should be established for each case study, although this multicriteria decision-making approach has broader applicability. In this paper, Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) with five criteria is used to develop a location evaluation for Alumina - cement plant in East- Azerbaijan province of Iran. Five alternatives for the plant location are evaluated. The main criteria are transportation consideration, water supply, power supply, fuel supply and land consideration. Other criteria have the same importance as for five alternatives. Finally, Alternatives are ranked and the best site is proposed.

Today, the attention to energy security, the increase in the need for electrical energy and the need to create new power plants, especially the power plants that use renewable energy, has increased significantly both in Asia and globally. Wind power is expected to make the largest contribution to global decarburization, ranking first or second in terms of projected capacity by 2050. This type of power plant directly uses natural energy as fuel. And as a result, climate change affects the efficiency of these power plants. Two parameters of the natural phenomenon of wind, which include wind speed and direction, are the main factors of wind power plant efficiency. The science of remote sensing is the process of identifying and monitoring the physical characteristics of a remote area by means of satellites. Google Earth Engine is an artificial intelligence to use this knowledge. Google Earth Engine combines a multi-petabyte catalog of satellite imagery and geospatial datasets with planetary-scale analysis capabilities. Google Earth Engine provides us with these  parameters. In this article, by collecting and then analyzing these data, we try to choose suitable candidate locationsfor the establishment of these two types of power plants, and based on priority, we provide a list for the establishment of solar and wind power plants

Due to the ever-increasing use of Distributed Generations (DGs), and special attentions toward wind power plants in recent years, this research investigates the wind plants from the viewpoint of lightning protection. In comparison to all other type of generators connected to the electric power systems, wind turbine generators are placed in areas which are more likely to be stricken by lightning. Lightning damages are divided into two major categories: direct and indirect damages. This paper studies the strategies to reduce the indirect damages o the wind turbine. Modeling of wind turbine components, i.e., blades, towers and connected cables, are frequency-dependent. Lightening arresters are used to reduce over-voltages caused by lightning currents in wind farms. Lightning arrester placement in wind farm is performed based on the objective function composed of insulation risk constraint and lightning failure and weighting coefficients are considered for the stress-exposed insulation devices. Optimization process is performed using Genetic Algorithm (GA), and finally the simulation results are analyzed.

Co-firing biomass plants are of extensive demand due to utilization of both agricultural residues (main) and natural gas (stand-by). Researchers have shown that one strategic decision in establishment of agricultural residues based plants, is location optimization problem. Moreover, mismatch between agricultural lands and biomass plants can lead to high transportation costs and related carbon dioxide emissions. Standard indicators are considered and used for the stated multi-objective mathematical problem. This article presents a novel approach based on Z-number data envelopment analysis (DEA) model to handle severe uncertainty associated with actual data. The multi-objective mathematical model considers environmental, economic and social aspects of biomass plants. Moreover, fuzzy DEA model is utilized to verify and validate the results of Z-number DEA model through 30 independent experiments. The obtained results indicate that “ accessibility to water” , “ population” , “ cost of land” , and “ unemployment rate” are the most significant factors in location optimization of co-firing power plants. The obtained results also indicate that “ Ilam” , “ Semnan” , “ Kohgiluyeh and Boyer-ahmad” , “ South Khorasan” , and “ Chaharmahal and Bakhttiari” are the optimum locations. This is the first unique approach for location optimization of co-firing plants based on combined agricultural residues and natural gas under uncertainty. Second, a unique fuzzy mathematical optimization approach is presented. Third, it is a practical approach for biomass power plants.