Sharif Digital Repository

Planning of distribution networks is usually accomplished using a cost-based conventional model that minimizes the total cost of construction and reinforcement of substations and feeders. The resulted expansion plan designed by this cost-based model is not necessarily the best choice for an electrical distribution company (DISCO) in the nowadays deregulated structure. This happening is mainly due to the fact that the utility seeks to maximize its profit in this competitive environment. On the other hand, this model does not consider the upcoming new challenges ahead of distribution systems, such as smart grid and distribution automation technologies. This paper presents a novel profit-based... 

Access to a computational tractable method for representing the system more realistically has always been an important issue in power system reliability assessment. The Post Optimal Analysis (POA), as a well recognized technique to attack a set of similar optimization problems, has been successfully used to assess the reliability of composite systems. This method exploits the similarity of the system states to speed up the contingency evaluation procedure without sacrificing the accuracy of the results. In this paper, the performance and practical feasibility of the POA technique for power system reliability evaluation is tested using the Iran power grid. The POA based approach is applicable... 

Plug-in hybrid electric vehicle (PHEV) technology provides one of the most promising solutions to tackle the threatening challenges such as air pollution in urban areas. Dramatic increases in the number of PHEVs could have major impacts on power system operations because of their high electricity demand. From the distribution system operator facet, distribution system congestion during PHEVs charging is an economic and security concern. It is, therefore, necessary to investigate the effects of widespread using of PHEVs on the performance of distribution networks. In this paper, PHEV characteristics are exactly studied and a comprehensive model for investigation of PHEV impacts is achieved.... 

This paper discusses various aspects of unified power flow controller (UPFC) control modes and settings and evaluates their impacts on the power system reliability. UPFC is the most versatile flexible ac transmission system device ever applied to improve the power system operation and delivery. It can control various power system parameters, such as bus voltages and line flows. The impact of UPFC control modes and settings on the power system reliability has not been addressed sufficiently yet. A power injection model is used to represent UPFC and a comprehensive method is proposed to select the optimal UPFC control mode and settings. The proposed method applies the results of a contingency... 

In this paper, the agent velocity in robotic swarm was determined by using particle swarm optimization (PSO) to maximize the robotic swarm coordination velocity. A swarm as supposed here is homogenous and includes at least two members. Motion and behavior of swarm members are mostly result of two different phenomena: interactive mutual forces and influence of the agent. Interactive mutual forces comprise both attraction and repulsion. To be more realistic the field of the swarm members' view is not infinity. So influence of the coordinator agent on the robotic swarm would be local. The objective here is to guide the robotic swarm with maximum possible velocity. According to equation motion... 

In this paper, a class of uncertain piecewise affine (PWA) systems, subject to system and measurement external disturbances are studied. The uncertainties are assumed to be norm bounded and the external disturbance signals belong to the L2 space. The problem of optimizing the system response in the H?sense, by means of a piecewise affine observer-controller, is formulated as an optimization problem subject to a number of constraints in the form of matrix inequalities. The derived constraints are obtained by considering a partially piecewise quadratic Lyapunov function in combination with the general conditions for H?stability. Then the uncertain PWA approximation of the nonlinear attitude... 

Fast charging stations are vital components for public acceptance of electric vehicle (EV). The stations are connected to the electric grid and can recharge an electric vehicle in less than 20. min. Charging station development is highly influenced by the government policy in allocating station development costs. This paper presents a Mixed-Integer Non-Linear (MINLP) optimization approach for optimal placing and sizing of the fast charging stations. The station development cost, EV energy loss, electric gird loss as well as the location of electric substations and urban roads are among the factors included in the proposed approach. Geographic information has been used to determine EV energy... 

We propose an algorithm based on mutual information to address the problem of online reconstruction of dynamic MRI from partial k-space measurements. Most of previous compressed sensing (CS) based methods successfully leverage sparsity constraint for offline reconstruction of MR images, yet they are not used in online applications due to their complexities. In this paper, we formulate the reconstruction as a constraint optimization problem and try to maximize the mutual information between the current and the previous time frames. Conjugate gradient method is used to solve the optimization problem. Using Cartesian mask to undersample k-space measurements, the proposed method reduces... 

Estimation of distribution algorithms have evolved as a technique for estimating population distribution in evolutionary algorithms. They estimate the distribution of the candidate solutions and then sample the next generation from the estimated distribution. Bayesian optimization algorithm is an estimation of distribution algorithm, which uses a Bayesian network to estimate the distribution of candidate solutions and then generates the next generation by sampling from the constructed network. The experimental results show that the Bayesian optimization algorithms are capable of identifying correct linkage between the variables of optimization problems. Since the problem of finding the... 

Adjusting control factors (independent variables) to achieve an optimal level of output (response variable) is usually required in many real-world manufacturing problems. Common optimization methods often begin with estimating the relationship between a response and independent variables. Among these techniques, response surface methodology (RSM), due to its simplicity, has recently attracted extensive attention. However, on the one hand, in some cases, the relationship between a response and independent variables is too complex to be estimated using polynomial regression models. On the other hand, solving the obtained optimization model is not easy by exact methods. This paper introduces a... 

The practicality of robust model predictive control of systems with model uncertainties depends on the time consumed for solving a defined optimization problem. This paper presents a method for the computational complexity reduction in a robust model predictive control. First a scaled state vector is defined such that the objective function contours in the defined optimization problem become vertical or horizontal ellipses or circles, and then the control input is determined at each sampling time as a state feedback that minimizes the infinite horizon objective function by solving some linear matrix inequalities. The simulation results show that the number of iterations to solve the problem... 

In this work, the wind farm layout optimization problem is dealt with using a new approach. The aim of wind farm layout optimization is to maximize the output power of a wind farm considering the wake losses. Layout optimization minimizes the wake losses regarding the location of the turbines. Three different wind scenarios with different wind direction angles, wind direction blowing probabilities, and Weibull distribution parameters are assumed. Since, the problem is nonlinear and constrained, imperialist competitive algorithm is used as a modern and powerful algorithm for continuous optimization problems. The optimization outcomes indicate that imperialist competitive algorithm yields... 

A novel and robust approach is proposed to find the optimum shape of concrete arch dams located on any unsymmetrical shape of a valley. The approach is capable of finding the optimum shape for any given valley type in suitable time, based on abutment stability analysis, against thrust forces from an arch dam. The behavior and stability of a concrete arch dam is strongly dependent on the bedrock on which the dam rests. The stability of the abutment is considered a constraint in the proposed approach. In addition, a new objective function is introduced to decrease the final volume of the arch dam. Furthermore, a computer program was developed, which takes the effect of the dam foundation... 

In this paper, an autonomous orbit control of a satellite in Low Earth Orbit is investigated using model predictive control. The absolute orbit control problem is transformed to a relative orbit control problem in which the desired states of the reference orbit are the orbital elements of a virtual satellite which is not affected by undesirable perturbations. The relative motion is modeled by Gauss's variational equations including J2 and drag perturbations which are the dominant perturbations in Low Earth Orbit. The advantage of using Gauss's variational equations over the Cartesian formulations is that not only the linearization errors are much smaller, but also each orbital element can be... 

Distribution companies try to meet different goals such as increasing profitability, reducing investment and improving reliability indices. Therefore, distribution network planning has converted into complex multi-objective optimization problems. Mathematicians and operation research experts have developed many methods which can be used for solving these problems. Despite all efforts to develop applicable approaches for these problems, there is still no general consensus on project selection policy. Evaluating the strengths and weaknesses of each network optimization strategy selection in pragmatic manner is the objective of current research. In this paper, many methods used in network... 

This paper presents a new approach based on multi leader follower game in order to find the optimal contract price of distributed generation in distribution network considering competition among them. The leader problems correspond to the independent DG units who decide to maximize the individual profits, while the follower problem refers to the distribution company (DisCo) which seeks the minimization of the payments incurred in attending the expected demand while satisfying network constraints. Disco can purchase energy either from the transmission network through the substations or from the DG units within its network. The DisCo minimization problem acts as a constraint into the each DG... 

In this work a microgrid is established within the geographical perspective of interest. The characteristics of the grid and its urban are employed to determine the candidate points for establishment of EV charging stations. The investment costs and operation costs are calculated for each station realizing the required constraints. This process resulted in optimum selection of EV stations. The optimization is achieved based on two different types of preliminary assumptions. In the first one, it is assumed to have only one station, while in the second one possibility of having multi-stations is considered. Using the total investment and operation costs as the objective function of... 

In this paper, three fundamental properties of a potential field-based flocking algorithm, i.e. merging of neighbouring graphs during the system evolution, collision avoidance and convergence of position of the centre of mass of informed agents to that of virtual leader are discussed. Next, these properties are utilized to determine required number of informed agents based on initial position of uninformed ones and consequently reduce the domain of search in optimization problems defined for finding the optimal number of required informed agents. Finally, a new optimization framework is proposed, which benefits Voronoi diagrams in order to reduce the number of informed agents required for... 

In this paper, we study the impact of sensing error and channel fading on the decision process of a multiple secondary user network in a primary network whose channel occupancy states are modelled as a Bernoulli process. We present a randomized access strategy to maximize total secondary network throughput. The proposed method guarantees that the probability of collision between primary and secondary users in each channel is less than the predefined value of P c = ξ. To find the optimal access strategy, we formulate secondary network throughput as an optimization problem. Then, using the KKT method to find the solution, we break the original problem into multiple sub-problems. Then, we... 

During the last decade, there has been a growing interest toward the problem of sparse decomposition. A very important task in this field is dictionary learning, which is designing a suitable dictionary that can sparsely represent a group of training signals. In most dictionary learning algorithms, the cost function to determine the the optimum dictionary is the ℓ0 norm of the matrix of decomposition coefficients of the training signals. However, we believe that this cost function fails to fully express the goal of dictionary learning, because it only sparsifies the whole set of coefficients for all training signals, rather than the coefficients for each training signal individually. Thus,...