نشریه انرژی ایران
سال نوزدهم شماره 4 (پیاپی 73، زمستان 1395)

Cascading failures and blackouts are the most significant threats for power system security. If the process of cascading failures proceeds by further line tripping, the system will face uncontrolled islanding. Establishing of uncontrolled islands with deficiency in active or reactive power balance is the main reasons for system blackouts.
Controlled islanding is an active and effective way of avoiding catastrophic wide area blackouts. It is usually considered as a constrained combinatorial optimization problem. However, the combinatorial explosion of the solution space that occurs for large power systems increases the complexity of this problem. This study proposes a controlled islanding algorithm using genetic algorithm to find a suitable islanding solution for preventing the initiation of wide area blackouts by un-damped electromechanical oscillations or voltage instability. The objective function used in this controlled islanding algorithm is the minimal power-flow disruption. In this study to improve voltage stability after separation, minimal active and reactive power disruption is considered.
The sole constraint applied to this solution is related to generator coherency. In the first step of the algorithm, the generator nodes are grouped using normalized spectral clustering, based on their dynamic models, to produce groups of coherent generators. In the second step of the algorithm, GA search for islanding solution that provides the minimum power-flow disruption while satisfying the constraint of coherent generator groups is determined by grouping all nodes. Simulation results, obtained using MATLAB and DigSilent software on the IEEE 39 bus test systems show that the proposed algorithm is efficient and have a well performance regarding voltage and transient stability when solving the controlled islanding problem. Also, results compared with spectral clustering algorithm that is newest and strongest research in this field.

Energy consumption management according to lack of resources and the increasing cost of non-renewable energy and as well as the environmental impacts due to its indiscriminate utilize is unavoidable. Therefore, the purpose of this study was to investigate the energy flow and greenhouse gas emissions in industrial dairy farm at ferdowsi university of mashhad. total energy input and energy efficiency in production per liter of milk produced 7.73 MJ and 0.92, respectively. Data analysis revealed that two inputs including feed stock and fossil fuel with share of 64% and 23% were widely consumed in the production of energy resources, respectively. As what is accounted, both diesel fuel and electricity inputs with shares of 65% and 34% most greenhouse gas emissions, respectively. The results showed that about 35 percent of the needed electricity can be supplied with using the biogas system (clean energy).The total greenhouse gas emissions was calculated per head and per liter of cow milk produce 1295.1 and 0.14 kgCo2- eq, respectively.

Customer Relationship Management is a marketing strategy that involve the integration of all activities related to customers and one of the main aims are to increase the level of customer satisfaction. The aim of this study was to investigate the effect of using customer relationship management system (CRM) on customer satisfaction in Mashhad Electricity Distribution Company. The study was practical and the research method was Survey and. Statistical population of the study was composed of customers of Mashhad Electricity Distribution Company. 200 people were chosen among them by using convenience sampling. The gathering data tool was questionnaire and construct validity of the questionnaire has been approved after using factor analysis, also the reliability of the questionnaire tested and approved by Alpha-Cronbach’s Method. Multiple Regression method has been used for the data analysis. The research findings indicate that information Technology (IT) as a moderator have a positive impact on the trust and quality of service that will ultimately lead to more customer's satisfaction of the Mashhad Electricity Distribution Company.

The factors affecting the non-diffusing of the solar water heaters (SWH) in Iran has been inspected in this research. The energy audit implies that the efficiency of SWH convertors during cold period is not satisfactory and they need backup systems. A survey from users, experts, and suppliers of SWH reveals that the low price of energy carriers, low efficiency during cold period, un-reliability, water pipes freeze problem, non-economic, repair and maintenance issue, and high electrical energy consumption have been the main factors for non-widespread application of SWH in Iran. The financial consideration show that SWH are not economical, so the increase of the energy carriers prices up to their world values is the main factor and prior to the complementary solutions for developing the domestic applications of solar water heaters in Iran.

Limitation reserves of fossil energy, the human is challenging for replace a new energy source. However, wind as one of the manifestations of renewable energies is a special place. According to Topography and their relative position Isfahan province, is the best place to build a wind power plant. In this study, to determine appropriate locations for the construction of wind power plants in the Isfahanprovince, several criteria were considered and Analytical Hierarchy Process (AHP) for weighting the selected layers Expert choice software was implemented. The parameters of the fuzzy data into IDRISI software were based on expert opinions, the control points and fuzzy function for each layer was determined. Then the software Arc GIS. was used to overlay layers, and finally, the Isfahan province potential wind power plant constructed in were four levels: excellent, good, fair and poor.

In this paper, a single switch transformerless high step up dc-dc converter with low voltage stress on the power switch for solar energy application is proposed. In the proposed converter only one power switch is used which makes the control scheme simple as well as reducing the switching power loss. The voltage gain of the proposed converter is higher than the conventional boost converter and buck boost converter. The proposed converter has low voltage stress on the power switch which makes reducing the switching power loss. The proposed converter can be operated in the continuous conduction mode (CCM) and the discontinuous conduction mode (DCM). In this paper, different operation modes of the proposed converter, calculation of the voltage gain, the currents that flow through the components, efficiency and capacitors voltage ripple are presented. To verify the operation of the proposed converter, simulation results via PSCAD software and experimental results are provided.

Air conditioning and cooling systems are one of the most pollutant of the environment in the world and especially our country, because of its warm and dry climate. In this regard, passive systems have an effective role in providing comfort and health of inhabitants. Furthermore they decrease energy consumption. The purpose of this research is to determine the most efficient systems of passive cooling for the desert cities. Isfahan and Yazd has been chosen as case studies. So the efficiency of passive cooling systems has been compared and analyzed in these two cities. The main strategy of this research is descriptive- analytical. To obtain the efficiency of systems, the comfort condition of building has been analyzed before and after using these systems. Afterward the most efficient system has been determined for each city based on the completed analysis of each passive cooling system. The results show that indirect evaporative cooling is the most efficient system in the warmest months of the year for hot and dry climate (B). Night purge ventilation is an efficient system for Isfahan and the cities with the same climate (Bsk) and direct evaporative cooling is an efficient system for Yazd and other cities with the same climate (Bwh).

It is widely accepted that natural gas is a clean energy source that can be used to meet energy demand for heating and industrial purposes among the fossil fuels and its usage remarkably increases in order to maintain a clean environment in many countries in the world. In this paper, factors affecting gas consumption were firstly identified and then GMDH-Type Neural Networks has been used for modeling and prediction of gas consumption using input-output data set. To validate the proposed model, a case study was carried out based on the data consisted of 84 sets for 7 years obtained from regional gas distribution company of Rasht city. For modeling, the experimental data were divided into train and test sections (70% for training and 30% for testing). The predicted values were compared with those of experimental values . The GMDH-Type Neural Network model values showed a very good regression with the experimental results and the Coefficient of determination was obtained 0.8943.

Limited energy resources and the need to conserve it, make the optimum and proper design of buildings in terms of energy consumption, indispensable. The type of climate in which the building is constructed in, will also decrease or increase the necessity of this attention. The objective of this study is to evaluate the effect of the window angle on the indoors Mean Radiant Temperature. For this purpose, in the present study, hot and dry climate as one of high priority in regard of energy consumption, has been selected so as to determine the right angle which will reduce the energy consumption by comparing the angle of the window and its effect on the mean radiant temperature. To achieve this goal, the South facade which receives the most exposure over the years, was selected. The daily average Mean Radiant Temperature for the whole year, simulated in ten different angle, in Energy PLus software, was calculated. According to the role in which we expect of window in summer (means avoiding exposure), and winter (means transferring radiation to the inside of the building), and with compering the results for summer and winter, angle of 75 to 80 degrees has selected as the best angle for the whole year.

Use of various organic fluids in Organic Rankine Cycle is investigated as hybrid cycle with Gas Turbine (GT/ORC). Analysis presents a first and second law of thermodynamics for fourteen Organic fluids. Using the first and second laws of thermodynamics, the performance of an ORC can be evaluated under diverse working conditions for different working fluids. Superheating for some organic fluids performed are investigated. Viable results have been obtained for R245fa, propane and R152a ORC combined cycles, with reasonably high global efficiencies for low temperatures and for temperature more than 100 °C results demonstrate that GT/ORC using R113 shows the maximum efficiency.

The availability of new generation combined heat and power (CHP) plants in high efficiencies and diverse sizes in the recent decade has attracted many industrial and residential centers to decentralized power generation via natural gas. This achievement of new technologies has been studied in this paper aimed at decreasing long-term power generation costs. The recent increasing trend for use of district heating systems besides recent improvements in CHP technologies has contributed to more discussions about the so-called “energy hub” approach for supply of energy. Energy hub is an approach for joint operation of several energy carriers to supply electrical, heat, etc loads. Through this approach, all capabilities of different energy supply devices are optimally utilized to decrease operational costs. In this paper, a new comprehensive formulation has been introduced for optimal planning of devices, which unlike the common approaches, has employed the precise operational characteristics of CHP units in solving the optimal operation and planning problems. The planning results have been presented for a test case, and amount of decrease in costs as well as the effect of using precise CHP model in the problem formulation have been studied.

In this research, propitious agricultural residues in Iran for the biofuel production and provinces for the biorefineries construction were determined. Cereals are the most Iran's crop production. Iran contributes 0.86% of the global cereal production and 0.9% of the global agricultural residues, so have a potential to produce biofuels. Among top 10 countries in the biofuel production, Iran's cereal residues are more than Netherland's ones. Khuzestan, Fars, Tehran, Qazvin, Razavi Khorasan, Sistan and Baluchestan, Hamedan, Mazandaran, Golestan, Isfahan, Kerman, West Azerbaijan, East Azerbaijan, Ardabil, Lorestan, Kermanshah and Markazi provinces have a potential to produce biofuels from agricultural residues.