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Hasani-Marzooni M.,Niroo Research Institute | Hosseini S.H.,Sharif University of Technology
Energy Policy | Year: 2013

This paper develops a system dynamics model to analyze the impacts of different kinds of capacity payment as investment incentive mechanisms in Iranian electricity market. Since it is aimed that the incurred capital and operating costs of generation technologies be recovered in Iranian electricity pool, the noncompetitive capacity payment mechanism has been introduced for this purpose in order to encourage new investments in electric power generation system. In the current mechanism, the capacity payments are designated to the generating units in the whole country electricity market. An annual base value of capacity payment is proposed based on recovering the capital cost of a benchmark generation technology. This value is altered according to the operational reserve in the day-ahead electricity market. This supporting policy is simulated and analyzed in the proposed dynamic framework in order to track the trend of new investments in the Iranian electricity market. The feasibility study of implementing the regional capacity assignment is the main focus of this paper. Different possible regulating policies such as floating rates for capacity payment and electricity price cap, the multiple capacity payments to various technologies, and the regional electricity market with territorial capacity allocation are examined in order to investigate the consequences and performances of different decisions and policies in the capacity investment of Iranian electricity market. © 2012 Elsevier Ltd.


Hosseini Hashemi B.,International Institute of Earthquake Engineering and Seismology | Jafari M.A.,Niroo Research Institute
Journal of Constructional Steel Research | Year: 2012

This research was performed to evaluate two analytical methods for predicting the compressive strength of batten columns. Batten columns were subjected to pure axial compression, and the compressive strength was measured. The analytical methods used included the well-known Ayrton-Perry and ultimate strength curve methods to calculate the compressive strength of imperfect solid web columns, but their validity has not yet been studied experimentally on built-up columns. The geometrical parameters considered included the batten plate spacing and dimensions and the distance between the two longitudinal chords. The results show that the analytical methods were generally valid for the prediction of the compressive strength in batten columns and solid web columns. Using the average results of the Ayrton-Perry and ultimate strength curve methods leads to the best prediction of the column compressive strength. It was also shown that the initial imperfections in the batten columns could have a more important effect than the geometrical specifications on the value of compressive strength. © 2011 Elsevier Ltd.


Bozorgmehri S.,University of Tehran | Bozorgmehri S.,Niroo Research Institute | Hamedi M.,University of Tehran
Fuel Cells | Year: 2012

An artificial neural network (ANN) and a genetic algorithm (GA) are employed to model and optimize cell parameters to improve the performance of singular, intermediate-temperature, solid oxide fuel cells (IT-SOFCs). The ANN model uses a feed-forward neural network with an error back-propagation algorithm. The ANN is trained using experimental data as a black-box without using physical models. The developed model is able to predict the performance of the SOFC. An optimization algorithm is utilized to select the optimal SOFC parameters. The optimal values of four cell parameters (anode support thickness, anode support porosity, electrolyte thickness, and functional layer cathode thickness) are determined by using the GA under different conditions. The results show that these optimum cell parameters deliver the highest maximum power density under different constraints on the anode support thickness, porosity, and electrolyte thickness. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.


Hasani-Marzooni M.,Niroo Research Institute | Hosseini S.H.,Sharif University of Technology
IEEE Transactions on Power Systems | Year: 2013

This paper proposes a dynamic time simulation model for long-term generation capacity investment decisions in the presence of either perfect or imperfect electricity market. The model is based on system dynamics concept in which the dynamics of capacity construction is traced using the forecast of electricity price cleared in the short-term electricity market. Both the perfect and oligopolistic competitions are considered and a market power index is defined to evaluate the competition level of the electricity market. The short-term and long-term dynamic analysis are used to represent the generation firms' behavior in bidding strategy and capacity investment, respectively. Both possibilities of using forward bilateral contracts and application of wind power generation have been assessed individually in the proposed model in order to mitigate the market power. The time simulation results derived from a case study demonstrate the effectiveness of the model in illustrating the oligopoly in electricity marketplace and also the alternative decisions to attenuate it. Such a decision tool enables both the generation firms and the regulators to gain perfect insight into the oligopoly and its consequences in the long-term capacity investment in the electricity market. © 2012 IEEE.


Tajik Mansouri M.,Niroo Research Institute | Ahmadi P.,Energy Optimization Research and Development Group EORDG | Ganjeh Kaviri A.,University of Technology Malaysia | Jaafar M.N.M.,University of Technology Malaysia
Energy Conversion and Management | Year: 2012

In the present research study, the effect of HRSG pressure levels on exergy efficiency of combined cycle power plants is investigated. Hence, three types of gas turbine combined cycles, with the same gas turbine as a topping cycle are evaluated. A double pressure, and two triple pressure HRSGs (with and without reheat) are modeled. The results show how an increase in the number of pressure levels of the HRSG affect the exergy losses due to heat transfer in the HRSG and the exhaust of flue gas to the stack. Moreover, the results show that an increase in the number of pressure levels affects the exergy destruction rate in HRSG, and as a result, it causes a tangible increase in exergy efficiency of the whole cycle. The results from thermodynamic analysis show that the losses due to heat transfer in the HRSG and the exhaust of flue gas to the stack in a triple pressure reheat combined cycle are less than the other cases. From the economic analysis, it is found that increasing the number of pressure levels of steam generation leads to an increase for the total and specific investment cost of the plant for about 6% and 4% respectively. The net present value (NPV) of the plant increases for about 7% for triple pressure reheat compared to with the double pressure CCPP. Therefore, the results of economic analysis show that it is economically justifiable to increase the number of pressure levels of steam generation in HRSG. © 2012 Elsevier Ltd. All rights reserved.

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