Sharif Digital Repository

Distribution systems management is becoming an increasingly complicated issue due to the introduction of new technologies, new energy trading strategies and new deregulated environment. In the new deregulated energy market and considering the incentives coming from the technical and economical fields, it is reasonable to consider distributed generation (DG) as a viable option to solve the lacking electric power supply problem. This paper presents a mathematical distribution system planning model considering three planning options to system expansion and to meet the load growth requirements with a reasonable price as well as the system power quality problems. DG is introduced as an attractive... 

The intelligent well technology provides the capability to remotely monitor and control multiple production zones using Inflow Control Valves (ICV) installed on the production tubing. Employing intelligent completions, the objective might be to allocate the inflow rates for each zone such that the objective function (cumulative oil or net present value of the well) is maximized. In this paper, a method for determining the optimized application of different intelligent well control strategies is presented. The optimization algorithm, which is based on trust region method, has been coupled with a commercial flow simulator and applied to a conceptual sandstone thin oil rim model containing a... 

A new and general procedure for history matching that uses streamline simulation and a gradual deformation technique has been proposed. Streamline trajectories define the major flow paths and help the algorithm to modify the reservoir model only in the regions that cause the mismatch between simulation results and field observations. The use of a gradual deformation technique enables the algorithm to remain constrained to reservoir geostatistics. It also reduces the number of independent variables in the optimization problem. In our algorithm, effective conductivities are defined along each streamline. The effective streamline conductivities are then adjusted using the values of measured and... 

In the present work, a thermal modeling is conducted for optimal design of compact heat exchangers in order to minimize cost and entropy generation. In this regard, an εNTU method is applied for estimation of the heat exchanger pressure drop, as well as effectiveness. Fin pitch, fin height, fin offset length, cold stream flow length, no-flow length, and hot stream flow length are considered as six decision variables. Fast and elitist nondominated sorting genetic algorithm (i.e., nondominated sorting genetic algorithm II) is applied to minimize the entropy generation units and the total annual cost (sum of initial investment and operating and maintenance costs) simultaneously. The results for... 

Bus terminal assignment with the objective of maximizing public transportation service is known as bus terminal location problem (BTLP). We formulate the BTLP, a problem of concern in transportation industry, as a p-uncapacitated facility location problem (p-UFLP) with distance constraint. The p-UFLP being NP-hard (Krarup and Pruzan, 1990), we propose evolutionary algorithms for its solution. According to the No Free Lunch theorem and the good efficiency of the distinctive preserve recombination (DPX) operator, we design a new recombination operator for solving a BTLP by new evolutionary and memetic algorithms namely, genetic local search algorithms (GLS). We also define the potential... 

Osmotic power generation is one of the cleaner and sustainable methods for energy generation. This paper presents a study on the optimal size and design of pressure retarded osmosis (PRO) power plant as a viable source of renewable energy in the selected site in Bahmanshir river of Iran. The optimal sizing and design problem is formulated as a Non-Linear Programming (NLP) optimization problem and solved using the standard optimization software titled generalized algebraic modeling system (GAMS). The objective function is minimizing the total cost while considering the technical and economic constraints. Optimization results show that the optimal capacity of the PRO osmotic power plant is... 

This paper presents a residential energy hub model for a smart multi-carrier energy home consisting of plug-in hybrid electric vehicle (PHEV), combined heat and power (CHP), solar panels, and electrical storage system (ESS). The energy hub inputs are electricity and natural gas that provide electrical and heat demands at the output ports. In this paper, an optimization-based program is proposed to determine the optimal operation mode of the energy hub, to manage the energy consumption of responsive appliances, to schedule charging/discharging of PHEV and the storage system, and to coordinate solar panels operation with household responsive demand in response to day-ahead time-varying tariffs... 

Proliferation of private distributed energy resources (DERs) necessitates devising effective energy management frameworks. This paper aims at establishing a decentralized model for the optimal dispatch of DERs in smart grids. The objective function is to minimize expected procurement cost of demand while profit of private DER owners is not sacrificed. Unit management modules (UMMs) embedded in private DERs and a central agent are autonomous agents of the model. The approach is iterative. In each iteration, the central agent announces to UMMs its procurement strategy, which contains purchased powers and their prices. Then, UMMs optimize and send back their output power and selling price... 

In this paper, we introduce a novel approach based on Tucker Decomposition and quasi-periodic nature of ECG signal for fetal ECG extraction from abdominal ECG mixture. We adapt variable periodicity constraint of the ECG components to main objective function of the Tucker Decomposition and shape it to matrix form in order to simply optimize the objective function. We form a 3rd order tensor by stacking the mixed multichannel ECG and reconstructed fetal and maternal subspaces using BSS methods in order to have the benefit of further artificial observations, and apply our proposed penalized decomposition on it. The proposed method is evaluated on synthetic and real datasets using the criteria... 

This paper presents evolutionary methods for optimization in dynamic mobile robot path planning. In dynamic mobile path planning, the goal is to find an optimal feasible path from starting point to target point with various obstacles, as well as smoothness and safety in the proposed path. Pattern search (PS) algorithm, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) are used to find an optimal path for mobile robots to reach to target point with obstacle avoidance. For showing the success of the proposed method, first they are applied to two different paths with a dynamic environment in obstacles. The first results show that the PSO algorithms are converged and minimizethe... 

Robust optimization (RO) approach is inherently a multi-objective paradigm. The proposed multi-objective optimization formulation would attempt to find the optimum - yet robust - water injection policies. Two multi-objective, Pareto-based robust optimization scenarios have been investigated to encounter the permeability uncertainties. These multi-objective RO scenarios have been done based on a small representative set of realizations but they have introduced optimum points that could be reliable for the original set of realizations either. In both scenarios, the desired objective functions are expected value and variance of Net Present Value (NPV). The underlying RO scenarios have been done... 

The process of coarsening the detailed geological model of a reservoir to simulation models is known as upscaling. There are two fundamental steps in the procedure of upscaling, i.e., defining the coarse grid geometry and calculating the average properties for the generated coarse grid. In this paper, the focus will be on investigating the applicability of optimization in the context of coarse grid geometry definition. To do so, different objective function candidates will be defined, and their behavior in terms of predicting the two-phase flow accuracy of coarse grids will be analyzed to determine the proper objective function. A modified objective function employing the idea of analytical... 

An optimum electromagnetic design of a nonsalient magnetic-cored superconducting synchronous machine (SSM) is presented in this paper. First, self- and mutual inductances of a nonsalient magnetic-cored SSM are calculated using the magnetic energy method and analytical equations of magnetic vector potential. Then, a design approach for an SSM machine is proposed based on the inductances of the machine. An optimal design is finally performed using a genetic algorithm, considering the machine efficiency as an objective function. The finite-element method is utilized in each step to verify the analytical results  

This paper surveys the literature associated with the application of evolutionary algorithms (EAs) in coastal groundwater management problems (CGMPs). This review demonstrates that previous studies were mostly relied on the application of limited and particular EAs, mainly genetic algorithm (GA) and its variants, to a number of specific problems. The exclusive investigation of these problems is often not the representation of the variety of feasible processes may be occurred in coastal aquifers. In this study, eight EAs are evaluated for CGMPs. The considered EAs are: GA, continuous ant colony optimization (CACO), particle swarm optimization (PSO), differential evolution (DE), artificial bee... 

Multi-floor facility layout problem concerns the arrangement of departments on the different floors. In this paper, a new mathematical model is proposed for multi-floor layout with unequal department area. Maximising the number of useful adjacencies among departments is considered as the objective function. The adjacencies are divided into two major categories: horizontal and vertical adjacencies. The horizontal adjacency may be occurred between the departments assigned to same floors while the vertical can be happened between departments assigned to any consecutive floors. A minimum common boundary length (surface area) between any two horizontal (vertical) adjacent departments is... 

This paper presents the feedback linearization control of HIV infection. A multi-input multi-output (MIMO) dynamic nonlinear HIV infection model for this purpose has been used. For this purpose, three widely used drugs are considered. A Luenberger-like nonlinear observer (LNO) is designed for estimation of unavailable states. To minimize the side effects of drugs, the concentration of ZDV which has the highest side effect is fixed to a minimum value and the external controllers parameters are obtained by maximizing an objective function. In the control design, limitations on drug consumption and unavailability of all states are taken into account. The closed-loop stability has been... 

The existing learning methods usually assume that training data and test data follow the same distribution, while this is not always true. Thus, in many cases the performance of these methods on the test data will be severely degraded. In this paper, we study the problem of unsupervised domain adaptation, where no labeled data in the target domain is available. The proposed method first finds a new representation for both the source and the target domain and then learns a prediction function for the classifier by optimizing an objective function which simultaneously tries to minimize the loss function on the source domain while also maximizes the consistency of manifold (which is based on... 

In this paper, a multiproduct single vendor-single buyer supply chain problem is investigated based on the economic production quantity model developed for the buyer to minimize the inventory cost. The model to be more applicable for real-world supply chain problems contains five stochastic constraints including backordering cost, space, ordering, procurement, and available budget. The objective is to find the optimal order quantities of the products such that the total inventory cost is minimized while the constraints are satisfied. The recently-developed sequential quadratic programming (SQP), as one of the best optimization methods available in the literature, is used to solve the... 

This paper shows a new possible way with particle swarm optimisation (PSO) to achieve an exergoeconomic optimisation of combinedcycle power plants. The optimisation has been done using a classic exergoeconomic and genetic algorithm, and the effects of using three methods are investigated and compared. The design data of an existing plant is used for the present analysis. Two different objective functions are proposed: One minimises the total cost of production per unit of output, and maximises the total exergetic efficiency. The analysis shows that the total cost of production per unit of output is 2%, 3%and 5% lower and exergy efficiency is 4%, 8% and 6% higher with respect to the base case... 

Summary Increasing interest in smart grids exhibits its potential benefits for providing reliable, secure, efficient, environmental friendly and sustainable electricity from renewable energy resources. Here, reliability models of four types of renewable and hybrid distributed generation were developed. A fuzzy multi-objective function was suggested for simultaneous optimization of reliability, electricity generation cost, grid loss and voltage profile. This not only considers uncertainty of renewable energy resources but also provides smart generation dispatching. An efficient reliability index consisting of energy and interruption frequency terms was also defined. A novel hybrid heuristic...