Sharif Digital Repository

The problem of distributed generation (DG) optimization in distribution systems has normally been assessed by assuming a constant power (real and reactive) load model. Such assumptions may lead to inconsistent and misleading results about loss reduction, DG optimization and other subsequent calculations. In this paper, the effect of different types of demand, e.g. industrial, residential and commercial, and its time varying effects on distribution networks is investigated. Customer demand type is defined by the load model that is voltage dependent and the load patterns from real life hourly demand data. The study shows that by defining the energy loss minimization as the objective function,... 

The multi-carrier microgrid (MCMG) is a restricted district comprising convertors and energy storage systems (ESSs) that are used to fulfill various energy demands. The structure and optimal operation of these MCMGs with regard to fulfilling multi-carrier demands are presented in relation to their rapid spread. In this paper, a two-stage optimum planning and design method for an MCMG is presented in the planning horizon. The investment and operation (fuel and maintenance) costs are considered concurrently to find the optimal type and size of components over the planning horizon. At the first stage, the genetic algorithm (GA) is applied to determine the optimal type and size of components,... 

The array factor (sidelobe level, SLL) of a linear array is optimized using modified continuous genetic algorithms in this work. The amplitudes and phases of the currents as well as the separation of the antennas are all taken as variables to be controlled. The results of the design using modified GA versions are compared with other methods. Two design problems were studied using several continuous modified GA versions and the results are presented as several plots. As a final example, the design specifications for an array with 200 elements are given. The effectiveness and advantages of the proposed modified GA versions are outlined  

The reinforcement of concrete columns with fabric reinforced cementitious matrix (FRCM) is one of the most challenging issues in the construction of concrete structures, as there is still an absence of a promising model to assess their performance. This is because the behavior of such elements is complex and accompanied by a high margin of uncertainty. To address this issue, this study compiles a large dataset of the performance of FRCM-reinforced concrete columns under monotonic load. The obtained dataset is then used to train an artificial neural network (ANN) as a promising method for predicting the compressive strength of concrete columns with acceptable accuracy. Afterward, using a... 

The present study investigated a counter-flow cooling tower performance by integrating the Artificial Neural Networks and Intelligent Optimisation Algorithms (ANN-IOAs). For this purpose, two scenarios were evaluated. In the first scenario, inlet air wet-bulb temperature (T aw), inlet air dry bulb temperature (T ad), water to the air mass flow rate ratio (mw /ma), and rotor speed (υ) were the input parameters for the ANNs, while the output temperature (T wo) was the ANNs output. In the second scenario, the same input parameters applied for the first scenario were used as input variables and the tower efficiency (ε) was considered as an output parameter. The well-known IOAs methods, namely,... 

Semi-active devices are low-cost as well as small and by changing the properties of low-power intensive structures, the aims of control are accomplished. On the other hand, the limited control force which can be applied to the structure for each damper causes more dampers to be used in the structures compared to the larger and stronger control devices which are more costly. These dampers coupled with sensors and the structure themselves make a complex dynamic system which is best controlled by a decentralized method such as Market-Based Control (MBC). In MBC, the actuators and the supply energy are modeled as buyer and seller respectively in the market place. To define the demand function of... 

Space-time block codes (STBCs) with orthogonal structures provide full-diversity reception and simple decoupled detection at the receiver. Rate-one orthogonal STBCs (OSTBC) for complex constellations have been found only for two transmit antennas. On the other hand, STBCs' designs are classically based on the assumption of independent and identically distributed (i.i.d.) fading channels. However, poor scattering conditions may have harmful effects on the performance of STBCs. In this paper, we first derive the average of received signal power at the receiver over Rician fading channel, when the signals are coded with linear dispersion code (LDC). Then by using a genetic algorithm (GA), we... 

Nowadays, discovery the association rules is an important and controversial area in data mining research studies. These rules, describe noticeable association relationships among different attributes. While most studies have focused on binary valued transaction data, in real world applications, there data usually consist of quantitative values. With that in mind, in this paper, we propose a fuzzy data mining algorithm for extracting membership functions from quantitative transactions. This is a hybrid genetic-pso algorithm for finding membership functions suitable for mining problems by a strong cooperation of GA and PSO. This algorithm integrates the two techniques entire run of simulation... 

During power system restoration, it is necessary to check the phase angle between two buses before closing circuit breakers to connect a line between them. A novel approach for reducing large standing phase angle (SPA) based on Genetic Algorithm (GA) is presented in this paper. The proposed approach starts with a state estimation on Wide Area Monitoring System (WAMS) data measurements and considering power system operation and angular stability constraints, seeks an optimal control action scenario for reducing SPA. Since these constraints are evaluated based on WAMS data, the presented approach is considerably high speed and accurate. As an optimization problem, objective function of the... 

Exploration of the ejector refrigeration cycle (ERC) in the combination with well-known power cycles to produce cooling output as well as power output is highlighted in recent decades. Since organic Rankine cycle (ORC) is practically usable than other power cycles, a combination of the ORC/ERC in a novel form is presented. Power and refrigeration sub-cycles are combined by a common condenser in separate loops to form dual-loop power/refrigeration cycle. The exhaust of the turbine is mixed with the outlet flow of the ejector, and then the mixed flow is fed into the condenser. Thermodynamic and thermoeconomic analysis of the proposed cycle are carried out with different working fluids (i.e.,... 

This paper addresses a novel formulation and solution for the security constrained reserve management (SCRM) problem in both normal and N − 1 contingency conditions. Indeed, the SCRM problem is a modified version of the security constraint unit commitment problem which is updated with the operational reserve management and frequency stability constraints in both normal and N − 1 contingency conditions. The objective of this problem is to determine the optimal amounts of generation associated with different units and frequency regulation reserve (FRR) and allocate the FRR among the generation units. Therefore, the SCRM problem is a mixed integer nonlinear problem which is solved using the... 

This paper presents an efficient High-Level Synthesis (HLS) approach to improve RT-Level concurrent testing. The proposed method used for both fault detection and fault location. At first the available resources are used in their dead intervals to test active resources for fault detection, and then some changes are applied to the RT-Level controller to locate the faults. The fault detection step is based on a genetic algorithm (GA) search technique. This genetic algorithm is applied to the design after high level synthesis process to explore the test map. The proposed method has been evaluated based on dependability enhancement and area/latency overhead imposed to different benchmarks after... 

Vendor-managed inventory (VMI) is a popular policy in supply chain management (SCM) to decrease bullwhip effect. Since the transportation cost plays an important role in VMI and because the demands are often fuzzy, this paper develops a VMI model in a multi-retailer single-vendor SCM under the consignment stock policy. The aim is to find optimal retailers' order quantities so that the total inventory and transportation cost are minimized while several constraints are satisfied. Because of the NP-hardness of the problem, an algorithm based on particle swarm optimization (PSO) is proposed to find a near optimum solution, where the centroid defuzzification method is employed 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... 

This paper presents a novel profit-based model for multistage distribution network expansion planning. In the proposed model, some capabilities of the distribution automation system are considered to achieve a plan that is more compatible with the strategic plan towards a smart distribution grid. Moreover, a method for reliability evaluation of a distribution network in the planning studies is proposed. The objective function of the planning problem is the net present value of the company's profit. The problem is solved by employing the genetic algorithm approach as a promising technique in solving the mixed-integer nonlinear programming problem. The proposed method is evaluated on an... 

An accurate estimation of aquifer hydraulic parameters is required for groundwater modeling and proper management of vital groundwater resources. In situ measurements of aquifer hydraulic parameters are expensive and difficult. Traditionally, these parameters have been estimated by graphical methods that are approximate and time-consuming. As a result, nonlinear programming (NLP) techniques have been used extensively to estimate them. Despite the outperformance of NLP approaches over graphical methods, they tend to converge to local minima and typically suffer from a convergence problem. In this study, Genetic Algorithm (GA) and Ant Colony Optimization (ACO) methods are used to identify... 

The purpose of this paper is to develop a multi-item economic order quantity (EOQ) model with shortage for a single-buyer single-supplier supply chain under green vendor managed inventory (VMI) policy. This model explicitly includes the VMI contractual agreement between the vendor and the buyer such as warehouse capacity and delivery constraints, bounds for each order, and limits on the number of pallets. To create a kind of green supply chain, tax cost of green house gas (GHG) emissions and limitation on total emissions of all items are considered in the model. A hybrid genetic and imperialist competitive algorithm (HGA) is employed to find a near-optimum solution of a nonlinear... 

This paper describes the concept and a sample design of a broadband loaded monopole antenna with a novel matching network integrated with the antenna body. The proposed monopole antenna is designed by loading three different lumped loads integrated on a wire antenna and a simple input matching network. Parameters of the matching circuits and the lumped loads optimized by using a genetic algorithm (GA). The proposed antenna loads and the matching network is integrated into the antenna body by the use of printed circuit technology making the antenna fabrication process easy. A prototype of the proposed 1.19-meter monopole antenna is fabricated and measured. The simulation and measurement... 

One of the novel applications of gas turbine technology is the integration of combined heat and power (CHP) system with micro-gas turbine which is spreading widely in the field of distributed generation and low-energy buildings. It has a promising great potential to meet the electrical and heating demands of residential buildings. In this study, a MATLAB code was developed to simulate and optimize the thermoeconomic performance of a gas turbine based CHP cycle. Three design parameters of this cycle considered in this research are compressor pressure ratio, turbine inlet temperature, and air mass flow rate. Firstly, two objective functions including exergetic efficiency and net power output... 

Nowadays, the growth of energy consumption in buildings is an important topic. Rammed earth (RE) structures have attracted the attention of engineers and contractors in recent years due to their advantages such as sustainability, availability and low embodied energy content. These advantages result in less energy consumption in the life cycle of the RE structures. However, there is a lack of research on the mixture composition of RE materials containing admixtures. This research introduced integrated analytic network process (ANP) and genetic algorithm (GA) methodology to select the optimum mixture of RE material containing cement, expanded polystyrene(EPS), and phase change materials(PCM)...