Sharif Digital Repository

In a competitive electricity market, a generation company (GenCo) optimizes its operation schedules, referred to as self-scheduling, in order to maximize its profit. However, various sources of uncertainty, such as market price fluctuations or forced outage of generating units, may impact the GenCo's profit. In this paper, a non-probabilistic information-gap model is proposed to model the uncertainties in short-term scheduling of a GenCo. The self-scheduling problem is formulated for risk-neutral, risk-averse, and risk-seeker GenCos. Robustness of the decisions against low market prices are evaluated using a robustness model. Furthermore, windfall higher profit due to unpredicted higher... 

This paper studies the economic impact of using inaccurate price forecasts on self-scheduling of generation companies (GenCos) in a competitive electricity market. Four alternative sets of price forecasts are used in this study which have different levels of accuracy. The economic impact of price forecast inaccuracies is calculated by comparing the economic benefits of the GenCos in two self-scheduling scenarios. In the first scenario, electricity market price forecasts are used to optimally schedule the GenCos' next day operation. In the second scenario, perfect price forecasts, i.e., actual market prices, are used for self-scheduling of the GenCos. Two indices are utilized to quantify the... 

In this paper, an approach for optimal determining reserve capacity in the electricity market is presented. This paper describes a method for setting the optimum value of reserve capacity based on the cost of its provision and the benefit derived from its availability. Reduction of customer outage cost is interpreted as the benefit of reserve capacity. In the proposed method, reserve is procured up to the point where the marginal cost of procuring reserve is equal to the marginal value of this reserve capacity. The proposed method can be formulated as a mixed-integer linear program (MILP) and solved with large-scale commercial solvers. The proposed method is applied to the IEEE reliability... 

This paper presents a risk-based approach for evaluating the participation strategy of a battery storage system in multiple markets. Simultaneous offering in day-ahead energy, spinning reserve, and regulation markets is considered in this paper. The uncertainties considered include predicted market prices as well as energy deployment in spinning reserve and regulation markets. A new nonprobabilistic model is introduced in this paper to handle the uncertain nature of spinning reserve and regulation markets. Robust optimization is implemented to model these uncertain parameters and manage their related risk. The proposed risk-based model is a max-min problem, which is converted to its... 

This paper presents a new model to maximize the utilization of existing transmission system infrastructure by optimally sizing and siting the future developments of variable renewable energy sources (VRES). The model tries to maximize the integration of VRES in power systems with minimum expected energy curtailment without relying on new investments in the transmission systems. The proposed model is formulated as a linear stochastic programming optimization problem where VRES output scenarios are generated such that their spatio-temporal correlations are maintained. The Progressive Hedging Algorithm (PHA) with bundled scenarios is utilized to solve the proposed model for large-scale cases.... 

A new model for long-term operation of hydrothermal power systems is introduced, and a method for obtaining an optimal solution is developed. We assume both reservoir inflows and energy demand are stochastic and all units are exposed to random outages. The objective is to minimize the total cost of the system as well as the expected interruption cost of energy (EIC) during a given planning horizon. This goal is reached through simultaneous determination of hydro plant discharges, thermal units energy output, and the system reliability level. Long-term hydrothermal system operation planning and system reliability determination are integrated in a unified model. Since the resulting model is a... 

A new model for long-term operation of hydrothermal power systems is introduced and a method for obtaining an optimal solution is also developed. We assume that reservoir inflows and energy demand are stochastic and all units are exposed to random outages. The objective is to minimize the total cost of the system as well as the expected interruption cost of energy (EIC) during a given planning horizon. This goal is reached through determination of hydroplant discharges, thermal units energy output, and the system reliability level simultaneously. In fact, we integrate long-term hydrothermal system operation planning and system reliability determination in a unified model. Since the resulting... 

For the 4th IUPAP International Conference of Women in Physics, we report on activities in science and engineering in Iran, and conditions for women in physics, in the three years since the 3rd IUPAP International Conference of Women in Physics was held in 2008. Iran has made prominent advancements and astonishing progress in laser technology, biotechnology, nanotechnology, genetics, computer software and hardware, and robotics. Iranian scientists have been very productive in several experimental fields, such as pharmaceutical, organic, and polymer chemistry. Conditions for women in physics have improved greatly in recent years. A project to improve the environment for learning physics, and... 

The lead is a heavy metal with hazardous impacts on environment and human life. Lead-free perovskite solar cells have attracted much attention in recent years, due to eco-friendly characteristics. Meanwhile, Pb-containing cells showed the highest efficiencies among the various types of cells. Hence, designing novel Pb-free solar cells with comparable or better performance than the Pb-containing ones is highly required. In this work, a lead-free methyl-ammonium-germanium-iodide (MAGeI3)-based perovskite solar cell with ITO/TiO2/MAGeI3/Spiro-OMeTAD/Ag multilayer nanostructure has been proposed and its main characteristics including open-circuit voltage (VOC) and power conversion efficiency (η)... 

Core/shell structure of ZnO nanowires coated with a monolayer of TiO 2 is investigated using Density Functional Theory (DFT). The electronic states of the semiconductor is calculated and compared before and after coating of the TiO2 monolayer on a ZnO [101 0] surface. The effect of TiO2 coating induce surface states changes and shifts the conduction and valence band edges to higher energies. Our results, in qualitative agreement with the experimental work of Matt Law et al. (J. Phys. Chem. B, 110, 22652), show an increase in open circuit voltage and a decrease in short circuit current in ZnO/TiO2 core shell dye sensitized solar cells. Regarding the semiconductor density of states (DOS), TiO2... 

Due to the important role of commitment and trust in the relationship marketing, the factors which can directly result in a committed relationship along with the factors which can influence the commitment through influencing trust, according to the model of commitment and trust by (Morgan & Hunt, 1994) have been introduced and their level of importance has been investigated here. The article uses fuzzy cognitive maps (FCMs) in the proposed model to find the most important paths leading to relationship commitment. The FCM analyzes the responses of a group of 30 people including general practitioners in dentistry, managers of dental departments in some of the public clinics and hospitals who... 

Conventionally, a film of TiO2 particles of 300 nm size is employed in Dye-sensitized solar cells (DSCs) as the back reflector film to enhance the light harvesting. Perfect reflectance of silver in visible and near infrared motivates to investigate its potential as the material for the light back reflector film in DSCs. In this study, light back reflector films consisting of 300 nm-sized silver particles, as well as vacuum evaporated silver flat film, were fabricated and compared to 300 nm-sized rutile-type TiO2 particulate reflector film to study their optical aspects. Conventional TiO2 rutile-type particulate film demonstrates slightly lower performance... 

Monolithic dye-sensitized solar cells are conventionally fabricated using carbon composite layer as the counter electrode. In the current research, the brittle carbon composite layer is replaced with a metal foil, aiming to decrease the device series resistance and using less catalyst material in counter electrode. This metallic structure has also an advantage of mechanical strength and decreases the fabrication complexity. The counter electrode is prepared by electrodepositing Cr film followed by electrodepositing Pt nanoparticles on a metal foil. As the porous spacer layer, different composite layers of SiO2, TiO2, and Al2O3 are investigated and the best results are obtained for TiO2... 

Microbial fuel cells (MFCs) have been a potential green energy source for a long time but one of the problems is that either the technology must be used on a large scale or special equipment have been necessary to keep the fuel cells running such as syringe pumps. Paper-based microbial fuel cells do not need to have a syringe pump to run and can run entirely by themselves when placed in contact with the fluids that are necessary for it to run. Paper-based microbial fuel cells are also more compact than traditional MFCs since the device doesn't need any external equipment to run. The goal of this paper is to develop a microbial fuel cell that does not require a syringe pump to function. This... 

This paper proposes a novel decentralized control approach for islanded direct-current (DC) microgrids (MGs) based on model predictive control (MPC) to regulate the distributed generation unit (DGU) output voltages, i.e. the voltages of the point of common coupling (PCC). A local controller is designed for each DGU, in the presence of uncertainties, disturbances, and unmodeled dynamics. First, a discrete-time state-space model of an MG is derived. Afterward, an MPC algorithm is designed to perform the PCC voltage control. The proposed MPC scheme ensures that the PCC voltages remain within an acceptable range. Several simulation studies have been conducted to illustrate the effectiveness of... 

Sophisticated surgeons are widely indicating the use of surgical robots in order to reject human error, increase precision, and speed. Among well-known robotic mechanisms, parallel robots are broadly more investigated regarding their special characters as higher acceleration, speed, and accuracy, and less weight. Specific surgical procedures confine, and restrict their workspace, while controlling and validating the robots are complicated regarding to their complex dynamic. To this end, in this paper, a 6-DOF robot, with rotary manipulators, is designed and controlled. Addressing nonlinearity of parallel robots, an innovative methodology is formulated to robustly penalize the error of... 

Sophisticated surgeons are widely indicating the use of surgical robots in order to reject human error, increase precision, and speed. Among well-known robotic mechanisms, parallel robots are broadly more investigated regarding their special characters as higher acceleration, speed, and accuracy, and less weight. Specific surgical procedures confine and restrict their workspace, while controlling and validating the robots are complicated based on their complex dynamic. To this end, in this paper, a 6-DOF robot, with linear manipulators, is designed and controlled. Addressing the inherent nonlinearity of the robot mechanism, an adaptive PID manipulator is employed and validated with nonlinear... 

Although so many advances have been proposed in the field of artificial intelligence and superconductivity, there are few reports on their combination. On the other hand, because of the nonlinear and multivariable characteristics of the superconductive elements and capabilities of neural networks in this field, it seems useful to apply the neural networks to model and control the superconductive phenomena or devices. In this paper, a new constructive neural network (CNN) trained by two different optimization algorithms; back-propagation and genetic algorithm, is proposed which models the behavior of the superconductive fault current limiters (SFCLs). Simulation results show that the proposed... 

In this paper, a new control strategy for optimal attitude tracking control of a multivariable satellite system has been presented. The approach is based on a Multilayer Perceptron Neural Network (MLPNN) and a classical PD Controller for its initial stabilization. It is shown how the network can be employed as a multivariable self-organizing and self-learning controller in conjunction with a PD controller for attitude control of a satellite. By using three thrusters and quaternion for kinematics representation, the attitude dynamics of the satellite has been presented. In contrast to the previous classical approaches, it is shown how this controller can be carried out in an on-line manner...