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Electricity distribution companies are in-charge-of supplying stable electric energy to urban customers over a wide geographical area. In these distribution networks, large number of Distribution-Transformers (DTs) are installed on towers or in electric-rooms with the ratings below 1000 kVA, which are the most important assets of distribution companies. Periodic maintenance and test services are not economically feasible for all in-operation transformers. Hence, estimating the remaining useful life and scheduling the maintenance times of DTs are of great technical and economic importance. An analytical approach is presented in this paper for predicting lifetime of DTs based on degree of polymerization. An appropriate Machine-Learning (ML) algorithm trained by measured data is selected for forecasting driven load according to the ambient temperature and humidity and day-hour schedules. The relation of Hot-Spot-Temperature in IEC60076∼7 is modified based on the measured data for accounting unbalanced-loading. Neutral-current is predicted using a trained ML-model. Another approach is proposed for determining times of oil filtering services aiming to minimize the maintenance cost and maximizing the remaining life. The proposed lifetime estimation method is validated by comparing its results with the damaged DT data of a sample network chosen as the case studies for this research, i.e., Bushehr province, Iran. [ABSTRACT FROM AUTHOR]

Due to the scarcity of fossil fuels in the future, the optimal use of these products can not only increase the efficiency of power plants, but it can also be effective in reducing the production of pollutants. To deal with these situations, optimal resource allocation and reallocation was studied using the data envelopment analysis (DEA) models. The current study adopted a resource allocation model in DEA framework when undesired outputs are produced in production process. This alternative resource allocation model is, however, sensitive to uncertainty of the data. In this contribution, we, therefore, introduce a stochastic resource allocation model when there are random data and undesirable products. An applied illustrative study to the power industry consisting 21 electricity production & distribution companies for eight years (2011–2019) is performed to compare the resource reallocations and their efficiencies. The important findings are: First, if we decide to deactivate two companies, the fuel consumption, employees and net electricity generation must be reduced. These reductions will lead to a reduction in pollutants. Second, the low price of electricity in Iran leads to excessive consumption of this product, which in turn leads to the inefficiency of many companies. In order to improve the performances of the companies, the amount of sold-out electricity must significantly be increased. • This paper adopted a resource allocation model in DEA with undesired outputs. • Our resource allocation model is sensitive to uncertainty of the data. • A stochastic resource allocation model is given when we have random data and undesirable products. • An application on 21 electricity production & distribution companies for eight years is given. [ABSTRACT FROM AUTHOR]

An optimum maintenance plan for the protection systems of substations leads to improve the reliability while reducing the related costs. Reliability-centered maintenance (RCM) is one of the widely used strategies to obtain an optimal maintenance plan. An important issue in the protection systems is lack of a direct way between normal operation states of the pieces of equipment and their failure states, which is named "hidden function". This hidden function of the equipment in the protection systems is the main issue challenging the implementation of RCM on such systems. Over-current protection systems are one of the main protection systems which are installed in the outgoing distribution feeders of substations. This paper presents a novel approach for the implementation of RCM on the over-current protection systems. The main advantage of the proposed approach is its global consideration of a protection system instead of only focusing on relays. The proposed approach has been applied on two different substations using real data of their over-current protection systems obtained from The Organization of Generation, Transmission, and Distribution Management of Electric Power in Iran (Tavanir). The results reveal a higher reliability and lower costs of the proposed maintenance plan in comparison with current maintenance plans. [ABSTRACT FROM AUTHOR]

Located in the south of Iran, Jiroft Paper Mill Company requires an integrated combined heat and power plant, which can provide 50 MW of electric power and 100 ton h-1 saturated steam at 13 bar, to produce paper from an adjacent eucalyptus forest. The plant is composed of an air compressor, combustion chamber, air preheater, turbine, as well as a heat recovery steam generator. The design parameters of the plant were chosen as: compressor pressure ratio (rc), compressor isentropic efficiency (ηAC), gas turbine isentropic efficiency (ηT), combustion chamber inlet temperature (T3), and turbine inlet temperature (T4). In order to optimally find the design parameters a thermoeconomic approach has been followed. An objective function representing the total cost of the plant in terms of dollar per second was defined as the sum of the operating cost related to the fuel consumption and the capital investment for equipment purchase and maintenance costs. Subsequently, different parts of the objective function have been expressed in terms of decision variables. Finally, the optimal values of decision variables were obtained by minimizing the objective function using sequential quadratic programming. The influence of changes in the demanded power and steam on the design parameters has also been studied for 40, 50, 60, and 70 MW of net power output, and 100, 120, and 150 ton h-1 of saturated steam mass flow rate. Finally, the sensitivity analysis of change in design parameters with change in fuel or investment cost was performed. Copyright © 2009 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This paper presents an LCA model to estimate the carbon footprint of a fossil fuel power plant for better policy implementation in an energy portfolio. The frameworks of the proposed model have integrated two groups of parameters (parameters affecting emissions and parameters affecting the amount of electricity) into one model. The model is developed to handle three types of power plants: gas turbine, combined cycle, and steam power with different fuel types and different utility transfer policies. The model is verified with two case studies in Iran. The results show good agreement between the model output and existing conditions. [ABSTRACT FROM AUTHOR]

Energy drives national economies with a positive correlation. Global environmental concerns, growth of the world population, and emerging of developing economies with more need for energy resources, would change the future of energy markets and human lives. To manage energy shortage and energy-related environmental threats, decision-makers have to decide between three potential solutions [1], to develop supply value [2], to suppress energy (all types) demands, or [3] to adopt a hybrid strategy. This paper is aimed to uncover potential saving capacities to fill the supply-demand gap based on efficiency improvements for the case of Iran as a developing economy with increasing energy needs. The methodology has been designed based on energy balance calculations which have been evaluated and validated through 47 expert panels under 9 major themes. Then, policy sets have been determined and to map how defined policies were interacting in the living energy, a system interpretive structural model was performed to determine direct and indirect relationships among policies. As a result, policymakers can prioritize and set a roadmap to approach the desired future. Findings showed for the case of supply-side Iranian energy management [1] maximizing electricity transmission and distribution efficiency [2], upgrading the consumption standard in equipment and processes (in the terms of energy production, conversion, and transmission), and [3] online monitoring of distribution networks are most basic and top priority policies. While for the case of demand-side "targeting energy subsidies" is the most crucial policy to support the Iranian energy efficiency improvement targets. • Iran's potential saving capacities to fill the supply-demand gap based on efficiency improvements are studied. • Policy sets have been proposed through 47 expert panels containing 9 main themes. • An interpretive structural model was performed to map policy relationships and dedicate a macro-level action plan. [ABSTRACT FROM AUTHOR]

Abstract: One of the primary concerns on target setting the electricity distribution companies is the uncertainty on input/output data. In this paper, an interactive robust data envelopment analysis (IRDEA) model is proposed to determine the input and output target values of electricity distribution companies with considering the existence perturbation in data. Target setting is implemented with the uncertain data and the decision maker (DM) can search the envelop frontier and find the targets based on his preference. In order to search the envelop frontier, the paper combine the DEA and multi-objective linear programming method such as STEM. The proposed method of this paper is capable of handling uncertainty in data and finding the target values according to the DM’s preferences. To illustrate ability the proposed model, a numerical example is solved. Also, the input and output target values for some of the electricity distribution companies in Iran are reported. The results indicate that the IRDEA model is suitable for target setting based on DM’s preferences and with considering uncertain data. [Copyright &y& Elsevier]

Abstract: Over the past decade, several new approaches have emerged to renewable energy education that seek to address the needs of the 21st century for sustainable energy supply systems. In addition, unlike conventional architectural education which does not cover renewable energy issues in its curriculum, these days, renewable energy education has an identity of its own within the discipline of architecture. This paper will clarify academic obstacles that are impeding the development of sustainable architectural education. These obstacles include: ambiguous definitions of sustainable architecture, confusion over the meaning of sustainability, and lack of experts in this field. In the last part of this paper we compare academic architectural education in the field of renewable energy in two countries, Iran as a developing country in Asia and Australia as a developed country in Oceania. Lessons can be drawn from these case studies in regard to the obstacles and progress in the development of sustainable architecture education. [Copyright &y& Elsevier]

This paper presents a model for use in the problem of composite generation and transmission expansion planning considering distributed generation. Generation expansion planning is defined as the problem of determining what capacity, which, and when new generating units should be constructed over a long range planning horizon, to satisfy the expected energy demand using single nodal generation planning model. Then, the place of every planned generating units and distributed generation is determined simultaneous with transmission expansion planning considering nonuniform geographical fuel supply cost and potential of distributed generation technology. The problem is formulated as a Mixed-Integer Linear Programming. By allocating the overall generation capacity among the grid nodes and determining the new transmission element additions along the planning horizon, the overall cost of the system is minimized. To assess the capabilities of the proposed approach, the Iranian Power Grid as a large scale system is considered. The effectiveness of the proposed modifications is illustrated in detail. [ABSTRACT FROM AUTHOR]

The paper reports on a study in which the power loss, energy loss, and loss factor were measured in an actual distribution network in Iran (Qazvin Power Distribution Company) by using an innovative method of load estimation before evaluating five ways of approaching the problem from the point of view of operating costs. The objective function was to minimize the costs. adjusting the load imbalance, optimall placing capacitors, and removing inappropriate transformers, dilapidated conductors, and weak connections. Another consideration was to maximize the financial gain from the power-loss reduction. The results showed that the method proposed for the estimating load was appropriate because the general pattern of the load curve was similar to the pattern obtained from the actual measurements. Another finding was that adding capacitors and adjusting the load imbalance turned out to be the most efficient and cost-effective ways of reducing the loss concerning the facilities available in the network under study. This work was fully funded by the Qazvin Electrical Distribution Utility under contract number 420. [ABSTRACT FROM AUTHOR]

Abstract: In Iran and other developing countries, transmitting electricity power to remote and inaccessible areas is not cost effective and involves a lot of problems due to high transmission costs and insufficient supply. Therefore local water potential would seem a better alternative to supply electricity. This paper is an investigation into all the issues concerning finding suitable sites for micro hydropower plants in remote areas in Lorestan province in Iran. Therefore, the basins, river network, and rural electricity condition in the province were studied. Then, we came up with a list of locations which would lend themselves best to the installation of micro hydropower plants in accordance to the existing parameters. Finally, an estimation of optimum nominal capacity for each micro hydropower was studied and related economic concerns were discussed. [Copyright &y& Elsevier]

Distribution Network (DN) face sundry transient conditions, resulting in incorrect detection of fault and mal-operation based on load type, capacity, and number of transformers in the operation mode. In this paper, a novel method is proposed to provide separability while increasing fault detection capability from other transient conditions in the DN, all in all by using the recorded currents at the beginning of feeder. Using current components of Park transformation, the method proposes a novel pattern, based on the graph of component d compared to component q of the current recorded at the beginning of the feeder, for analyzing transience in normal and faulty operation modes of the network. Fault curves and other transient trends of the DN, such as inrush current, inherit different characteristics that can be detected through classification. In this method, healthy and faulty operating modes are well distinguished in less than 2 ms. A sample of DN together with a real distribution feeder of Iran's Electricity Distribution Company is used to evaluate the proposed method. Simulation results verify the validity and accuracy of the proposed method. [ABSTRACT FROM AUTHOR]