Sharif Digital Repository

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... 

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... 

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... 

This paper presents a robust decentralized proportional-integral (PI) control design as a solution of the load frequency control (LFC) in a multi-area power system. In the proposed methodology, the system robustness margin and transient performance are optimized simultaneously to achieve the optimum PI controller parameters. The Kharitonov's theorem is used to determine the robustness margin, i.e., the maximal uncertainty bounds under which the stable performance of the power system is guaranteed. The integral time square error (ITSE) is applied to quantify the transient performance of the LFC system. In order to tune the PI gains, the control objective function is optimized using the... 

United Nation aims to double the global rate of improvement in energy efficiency as one of the sustainable development goals. It means researchers should focus on energy systems to enhance their overall efficiency. One of the effective solution to move from suboptimal energy systems to optimal ones is analyzing energy system in Energy Hub (EH) framework. In EH framework, interactions between different energy carriers are considered in supplying the required loads. The couplings and selecting proper combinations of inputs energy carriers lead to more optimized and intelligent consumption. The appropriate combination is found by solving an optimization problem at each time step. Utilizing... 

The interests in 'Energy Hub' (EH) and 'Smart Grid' (SG) concepts have been increasing, in recent years. The synergy effect of the coupling between electricity and natural gas grids and utilizing intelligent technologies for communicating, may change energy management in the future. A new solution entitling 'Smart Energy Hub' (S. E. Hub) that models a multi-carrier energy system in a SG environment studied in this paper. Moreover, the optimal size of CHP, auxiliary boiler, absorption chiller, and also transformer unit as main elements of a S. E. Hub is determined. Authors proposed a comprehensive cost and benefit analysis to optimize these elements and apply Reinforcement Learning (RL)... 

Today, as a consequence of the growing installation of efficient technologies, e.g. micro-combined heat and power (micro-CHP), the integration of traditionally separated electricity and natural gas networks has been attracting attentions from researchers in both academia and industry. To model the interaction among electricity and natural gas networks in distribution systems, this paper models a residential customer in a multi-energy system (MES). In this paper, we propose a fully automated energy management system (EMS) based on a reinforcement learning (RL) algorithm to motivate residential customers for participating in demand side management (DSM) programs and reducing the peak load in... 

In this paper, methods for reduction of coupling between receiving and transmitting antenna arrays are proposed and tested. Coupling between RX and TX causes saturation and a higher noise level in IF. So, coupling reduction improves image quality of system. Antenna element of arrays are printed antipodal Yagi-Uda antenna with greater than 8 dBi gain and higher than 4 GHz bandwidth. Frequency bandwidth of this imaging system is 27 to 30.5 GHz. Half power beamwidth of this antenna element is larger than 90 dB. Front to back ratio of this antenna is improved in this paper to 30 dB at 29 GHz. © 2019 IEEE  

In this study, optimal offering strategy problem of a virtual power plant (VPP) as a price-maker player in day-ahead frequency constrained electricity market is presented. The optimal offering strategy problem is modelled as a bi-level optimisation problem. In the upper-level problem, the total profit of VPP is maximised. In the lower-level problem, the clearing conditions of frequency constrained electricity market are modelled. The proposed bi-level optimisation problem is reformulated as a mathematical programming with equilibrium constraints (MPEC) problem by using Karush-Kuhn-Tucker conditions. Then, the proposed MPEC problem, which is non-linear and hard to solve by commercial solvers,... 

In this paper, the problem of frequency-constrained electricity market (FCEM) is modeled in the presence of renewable energy sources (RESs) and price-maker players by using equilibrium problem with equilibrium constraints formulation. It is worth mentioning that due to the intermittency of RESs, the FCEM problem in the presence of price-maker players becomes more imperative as stability of power system frequency is a public good and the free-rider problem arises. Moreover, as players of FCEM do not know their rivals' objective functions, the problem is modeled based on Bayesian game theory. The FCEM problem is converted into a game of complete but imperfect information under the common prior... 

This article presents a comprehensive small signal model for a virtual synchronous generator (VSG) integrated into a microgrid. In the developed state-space, active and reactive power control loops of the VSG as well as resistances, and reactances of the lines are considered. Based on this model, the robust D-stable region in terms of different values of inertia constant $(M)$, and damping coefficient $(D)$ values of the VSG is obtained. To enhance both transient performance as well as guarantee the robust D-stable operation of VSG, an optimization problem is also proposed. Moreover, a new control method is suggested to damp frequency oscillations of the microgrid. The proposed controller is... 

In this paper, we develop a metaheuristic procedure for solving the discrete time/resource trade-off problem in the field of project scheduling. In this problem, a project contains activities interrelated by finish-start-type precedence constraints with a time lag of zero, which require a single constrained renewable resource. Each activity has a specified work content and can be performed in different modes, i.e. with different durations and resource requirements; as long as the required work content is met. The objective is to schedule each activity in one of its modes in order to minimize the project makespan. To tackle this problem, we use a genetic algorithm in which a new method based... 

In this paper, a robust multivariable Model based Predictive Control (MPC) is proposed for the solution of load frequency control (LFC) in a multi-area power system. The proposed control scheme is designed to consider multivariable nature of LFC, system uncertainty and generation rate constraint, simultaneously. A constrained MPC is employed to calculate optimal control input including generation rate constraints. Economic allocation of generation is further ensured by modification of the predictive control objective function. To achieve robustness against system uncertainty and variation of parameters, a linear matrix inequality (LMI) based approach is employed. To validate the... 

Wide-area monitoring and control system complements the classical protection systems and overcomes their drawbacks. In such systems a dynamic view of power system, using synchronized measurements in short time intervals, smaller than 20ms, is available. This new kind of system's information provides a novel preventive control action to prevent system's large disturbances. This paper proposes a new method to prevent frequency instabilities immediately after a disturbance occurs in a system. Based on online measurements sent by phasor measurement units, a single machine equivalent model including the governors' effect is computed. An accurate frequency prediction is done based on this novel... 

In most of the existing studies, the frequency response in the variable speed wind turbines (VSWTs) is simply realized by changing the torque set-point via appropriate inputs such as frequency deviations signal. However, effective dynamics and systematic process design have not been comprehensively discussed yet. Accordingly, this paper proposes a proportional-derivative frequency controller and investigates its performance in a wind farm consisting of several VSWTs. A band-pass filter is deployed before the proposed controller to avoid responding to either steady state frequency deviations or high rate of change of frequency. To design the controller, the frequency model of the wind farm is... 

Control of three phase inverters is of paramount importance in the realm of control applications. In this regard, this paper proposes active disturbance rejection control (ADRC) scheme as a new method for voltage control of three phase inverters in UPS applications. The main advantage of ADRC refers to the fact that it is model independent. In this paper, the controller is composed of a double loop structure including an inner current loop and outer voltage loop. This structure is used in a three phase inverter in order for implementation of voltage control. To draw a comparison between ADRC and PI as the common control method, a case study has been simulated in SIMULINK. Simulation results... 

To avoid the needless trip by magnetizing inrush current, the second harmonic component is commonly used for blocking differential relay in power transformers. However, the main problems of the current comparison method are in the very high inrush currents and relatively small fault currents regarding winding short circuits. Also The second harmonic component in fault current is increased in long lines which may blocks the relay operation. This paper describes a method to discriminate internal fault from inrush current and faults with a high second harmonic component by the sum of active power flowing into the transformer from each terminal. The average power is almost negligible for... 

In this paper, we study a resource-constrained project scheduling problem in which a set of project activities have due dates. If the finish time of each one of these activities is not equal to its due date, an earliness or a tardiness cost exists for each tardy or early period. The objective is to minimize the sum of discounted weighted earliness-tardiness penalty costs of these activities. Scatter Search algorithm is used to deal with this extended form of resource-constrained project scheduling problem. Our implementation of Scatter Search integrates the advanced methods such as dynamic updating of the reference set and the use of frequency-based memory within the diversification... 

This paper presents a novel stochastic planning framework for the integration of renewable distributed energy resources (DERs) into existing power systems without relying on new investments in the transmission networks. The upper-level problem of the proposed model aims at minimizing the total expected social cost of supplying demand that includes the expected cost of getting energy from conventional generating units and DERs, the congestion cost of transmission networks, and the greenhouse gas (GHG) emission cost, while each of the privately invested DER satisfies a specified rate of return. The lower-level problem clears the electricity market to find locational marginal prices (LMPs) and... 

This article presented an efficient deep learning technique to predict the compressive strength of high-performance concrete (HPC). This technique combined the convolutional neural network (CNN) and genetic algorithm (GA). Six CNN architectures were considered with different hyper-parameters. GA was employed to determine the optimum number of filters in each convolutional layer of the CNN architectures. The resulted CNN architectures were then compared to each other to find the best architecture in terms of accuracy and capability of generalization. It was shown that all of the proposed CNN models are capable of predicting the HPC compressive strength with high accuracy. Finally, the best of...