Sharif Digital Repository

In the restructured power markets, price of electricity has been the key of all activities in the power market. Accurately and efficiently forecasting electricity price becomes more and more important. Therefore in this paper, an Artificial Neural Network (ANN) model is designed for short term price forecasting of electricity in the environment of restructured power market. The proposed ANN model is a four-layered perceptron neural network, which consists of, input layer, two hidden layers and output layer. Instead of conventional back propagation (BP) method, Levenberg- Marquardt BP (LMBP) method has been used for the ANN training to increase the speed of convergence. Matlab is used for... 

Thermal management and temperature control of the electrical, electronic, and electrochemical devices during their operation have always been a challenge for proper performance and further development of them. In this regard, the utilization of liquid-cooled mini-channel heat sinks (MCHSs) and improving their capability for heat dissipation have been considered an effective method in past decades. The current study aims to improve the hydrothermal performance and temperature uniformity of MCHS. To this end, several channel configurations with novel geometrical cross sections, namely basic case and cases 1–4, are designed to investigate the influence of geometrical parameters on the... 

With increasing the presence of co-and tri-generating units, energy hub operators are encouraged to optimally schedule the available energy resources in an economic way. This scheduling needs to be run in an online manner due to the uncertainties in energy prices and demands. In this paper, the real-time scheduling problem of energy hubs is formulated in a dynamic pricing market. The energy hubs interaction is modeled as an exact potential game to optimize each energy hub’s payments to the electricity and gas utilities, as well as the customers’ satisfaction from energy consumption. The potential game approach enables us to study the existence and uniqueness of the Nash equilibrium (NE) and... 

The main purpose of this article is to generalize a theorem about the size of minimal submanifolds in Euclidean spaces. In fact, we state and prove a non-existence theorem about harmonic maps from a stochastically complete manifold into a cone type domain. The proof is based on a generalized version of the maximum principle applied to the Lapalace-Beltrami operator on Riemannian manifolds. © 2009 Birkhäuser Verlag Basel/Switzerland  

With increasing the presence of co- and tri-generating units, energy hub operators are encouraged to optimally schedule the available energy resources in an economic way. This scheduling needs to be run in an online manner due to the uncertainties in energy prices and demands. In this paper, the real-time scheduling problem of energy hubs is formulated in a dynamic pricing market. The energy hubs interaction is modeled as an exact potential game to optimize each energy hub's payments to the electricity and gas utilities, as well as the customers' satisfaction from energy consumption. The potential game approach enables us to study the existence and uniqueness of the Nash equilibrium and to... 

The In this paper, an Adaptive Particle Swarm Optimization (APSO) method is proposed for parameter identification of highly coupled electromechanical systems. Using some modifications on the APSO, better computational efficiency is achieved. In this way, the speed of real-time identification procedure is improved. In addition, to show the effectiveness of the proposed method, it is implemented on a real ball on plate setup and its dynamic model is achieved. Both the simulation and the experimental results show that parameter identification of the proposed algorithm is significantly improved when compared with other existing identification methods based on the traditional PSO and Genetic... 

The concept of smart grid (SG) has been introduced to improve the operation of the power systems. In modern structures of power systems, different reasons prompt researchers to suggest integrated analysis of multi-carrier energy systems. Considering synergy effects of the couplings between different energy carriers and utilising intelligent technologies for monitoring and controlling of energy flow may change energy system management in the future. In this paper, we propose a new solution which is entitled ‘smart energy hub’ (SEH) that models a multi-carrier energy system in a SG. SEH solutions allow homeowners to manage their energy consumption to reduce their electricity and gas bill. We... 

Plug-in Hybrid Electric Vehicles (PHEV) have the potential to limit emissions and reduce the cost of transportation. Although wide scale adoption of plug-in vehicles is still a few years away, politicians, electric utilities, and auto companies are eagerly awaiting the opportunities that may arise from reduction of emissions and gasoline and oil consumption, new services and increased revenues, and new markets that would create new jobs. For consumers, plug-in vehicles will significantly lower operational costs when compared with traditional gasoline cars. The savings are potentially high, in average, as electricity cost mile work out to about one forth of gasoline. But it is noticeable to... 

Owing to the local nature of voltage and reactive power control, the voltage control is managed in a zonal or regional basis. A new comprehensive scheme for optimal selection of pilot points is proposed in this study. The uncertainties of operational and topological disturbances of the power system are included to provide the robustness of the pilot node set. To reduce the huge number of probable states (i.e. combined states of load and topological changes), a scenario reduction technique is used. The resulted optimal control problem is solved using a new immune-based genetic algorithm. The performance of the proposed method is verified over IEEE 118-bus and realistic Iranian 1274-bus... 

New days, the concepts of 'Smart Grid' and 'Energy Hub' have been introduced to improve the operation of the energy systems. This paper introduces a new conception entitling Smart Energy Hub (S. E. Hub), as a multi-carrier energy system in a smart grid environment. To show the application of this novel idea, we present a residential S. E. Hub which employs Reinforcement Learning (RL) method for finding a near optimal solution. The simulation results show that by applying the S. E. Hub model and then using the proposed method for a residential customer, running cost is reduced substantially. While, comparing with the classical ones, the RL method does not require any data about the... 

The concept of smart grid (SG) has been introduced to improve the operation of the power systems. In modern structures of power systems, different reasons prompt researchers to suggest integrated analysis of multi-carrier energy systems. Considering synergy effects of the couplings between different energy carriers and utilising intelligent technologies for monitoring and controlling of energy flow may change energy system management in the future. In this paper, we propose a new solution which is entitled smart energy hub (SEH) that models a multi-carrier energy system in a SG. SEH solutions allow homeowners to manage their energy consumption to reduce their electricity and gas bill. We... 

In this letter, an incentive compatible contract is designed for purchasing energy and ancillary service (AS) simultaneously from strategic frequency regulation service providers (FRSPs) by considering information asymmetries between independent system operator and FRSPs. Here, AS is confined to frequency reserve (FR) for arresting nadir frequency following possible contingencies of the electrical grid. An FRSP has a multi-dimensional private information vector, which determines its operational cost and limitations. Moreover, there is a gaming opportunity for an FRSP that is arisen between energy and AS payments manifesting by manipulation of its bids. Thus, in this letter, a multi-object... 

A microgrid is a controllable component of the smart grid defined as a part of distribution network capable of supplying its own local load even in the case of disconnection from the upstream network. Microgrids incorporate large amount of renewable and non-renewable distributed generation (DG) that are connected to the system either directly or by power electronics (PE) interface. The diversity of technologies used in DGs and loads, high penetration of DGs, economic operation of DGs, dynamics of low-inertia conventional DGs and PE interfaced inertialess DGs and smart operation by means of enhanced communication infrastructure have raised challenges in widespread utilization of microgrids as... 

Synthetic inertial frequency response has attracted increasing attention due to the paradigm shift in power generation from synchronous generators toward wind turbines. This paper presents a novel nonlinear controller to enable inertial response of a variable speed wind turbine (VSWT). The VSWT has a nonlinear model which cannot efficiently be dealt with by linear control techniques as it may experience large deviations from its operating point during the frequency support period. To design the controller, a nonlinear model for the wind turbine together with power system is utilized. The output power of the wind turbine is expressed in terms of the state variables, and its exact Taylor... 

In this paper, we present an analytical approach in obtaining the probability density function (pdf) of the random decision variable Y, which is formed at the output of the power-cubic all-optical nonlinear preprocessor followed by the photodetector, with applications in ultrafast optical time-division multiplexing and optical code-division multiple-access systems. Our approach can be used to accurately evaluate the performance of ultrafast pulse detection in the presence of Gaussian noise. Through rigorous Monte Carlo simulation, the accuracy of the widely used Gaussian approximation of decision variable Y is refuted. However, in this paper, we show that the so-called log-Pearson type-3... 

In this paper, an accurate model for the probability density function (pdf) of the random decision variable Y in an ultrafast digital lightwave communication system, utilizing power-cubic all-optical nonlinear preprocessor is presented. The proposed model can replace the prevalent Gaussian approximation, as the accuracy of the latter is discredited by Monte-Carlo simulation. The Log-Pearson type-3 probability density function (LP3 pdf) is shown to appropriately represents the random decision variable Y. Three characteristic parameters of the LP3 pdf are also obtained through the three moments of the decision variable Y. Finally, the system error probability is revisited using the obtained... 

In this paper, a spectral-phase-encoded ultrashort light pulse optical code division multiple access (SPE-OCDMA) system employing a novel nonlinear power-cubic optical preprocessor at its receiver's front end is theoretically investigated. The system's mathematical model and the statistical distribution of the decision variable Y, prior to the decision module of the receiver, are discussed. The first three moments of the random decision variable Y are obtained in the context of the above OCDMA system and subsequently used in an appropriate Log-Pearson type 3 (LP3) distribution to represent the random decision variable $Y$. Multiple access interference (MAI) and amplified spontaneous emission... 

Nowadays, the incorporation of wind power in electrical grids and electricity markets is grown. Due to the fluctuation of wind speed, one of the main challenges of wind power would be selling power directly to the wholesale markets. A method for solving this challenge is coordination of wind power with energy storages, cascaded hydro, or gas turbine units in bidding strategy and operation. By coordinating with gas turbine units, wind power can be incorporated in real-time markets with fewer capital costs. In this paper, a stochastic bi-level optimization is proposed for coordinated wind power and gas turbine units in the real-time market. The uncertainties of wind power, demands, rivals'... 

Nowadays, the incorporation of wind power in electrical grids and electricity markets is grown. Due to the fluctuation of wind speed, one of the main challenges of wind power would be selling power directly to the wholesale markets. A method for solving this challenge is coordination of wind power with energy storages, cascaded hydro, or gas turbine units in bidding strategy and operation. By coordinating with gas turbine units, wind power can be incorporated in real-time markets with fewer capital costs. In this paper, a stochastic bi-level optimization is proposed for coordinated wind power and gas turbine units in the real-time market. The uncertainties of wind power, demands, rivals'... 

In this work, we address peak power and maximum temperature in multi-core Mixed-Criticality (MC) systems. In these systems, a rise in peak power consumption may generate more heat beyond the cooling capacity. Additionally, the reliability and timeliness of MC systems may be affected due to excessive temperature. Therefore, managing peak power consumption has become imperative in multi-core MC systems. In this regard, we propose an online peak power management heuristic for multi-core MC systems. This heuristic reduces the peak power consumption of the system as much as possible during runtime by exploiting dynamic slack and Dynamic Voltage and Frequency Scaling (DVFS). Specifically, our...