جستجوی مقالات مرتبط با کلیدواژه "روش مونت کارلو" در نشریات گروه "برق"

The growing penetration of electric vehicles (EVs) in distribution networks (DNs) has posed many challenges for electricity distribution companies, such as: increasing the amount of voltage drop, network losses and the number of outages due to the overload. To overcome this, it is recommended to use coordinated charging methods. However, these methods require telecommunication, measurement and processing infrastructure with high costs and can only be implemented in smart grids. In this paper, a semi-intelligent method for charging EVs is presented that does not require complex infrastructure. This method, using a simple and inexpensive local automation system, charges EVs in the off-peak periods of the DN and thus improves its parameters. Since the EVs are charged at the low tariff time intervals, the proposed method will also benefit the EV owners. To achieve real results, four-wire DN is considered to model the effect of neutral conductor. To confirm the effectiveness of the proposed method, it is compared with different uncontrolled charging methods. A standard 19 bus test system is used for simulations.

Inappropriate design of transmission line towers in areas with high lightning density increases the outage rate of the line due to direct lightning strikes. In this paper, The lightning activities of areas covered by western regional electricity company during five recent years were collected from weather stations. Based on collected datasets, the Isokeraunic level and the lightning density of different areas have been computed. This information were further used to investigate and predict the outage rate of double circuit 230 kV transmission lines with one shield wire (existing plan) due to direct lightning strikes. Due to high density of lightning activities in some areas, the calculation results show high outage rate in these areas, which has been confirmed by actual experiences. In order to overcome this problem, a tower design with two shield wires was proposed for new developments. The outage rate of the transmission line with the two shield wire design with extracted lightning densities were compared with the existing tower installed. The results show high degree of improvement in outage rates. In order to modify the existing transmission line outage rates, installation of surge arresters and their capabilities were studied. Due to statistic nature of lightning, Monte Carlo method along with EMTP simulations were used in investigations. Simulations results show placement of surge arresters on two upper phases can reduce the shielding failure outage rates in the transmission line, significantly. The pros and cons of surge arrester installations in transmission line to compensate inappropriate tower design are discussed. Results of this study can be used for further transmission line developments in these areas.

In recent years, evaluation of reliability analysis of structures has become a straightforward and interesting topic among structural researchers. In the field of civil engineering, estimation of structural failure probability is highly investigated, considering probabilistic uncertainties of resistance and load parameters during modeling and designing of structures. To obtain an accurate failure probability, researchers often perform Monte Carlo simulation (MCS) that requires numerous modeling and cost. In the present study, based on MCS, an enhanced technique is developed that efficiently reduces number of structural modeling. The approach works by employing the concept of First Order Reliability Methods (FORMs) to determine closest point to the mean of random variables in failure region. Afterward, by presenting sub-intervals in various layers, to group generated samples in MCS, the possibility of reducing number of structural modeling with well-disciplined error and acceptable accuracy is achieved. In order to investigate the efficiency and robustness of the method, various numerical and engineering examples with complex limit state functions were attempted and the obtained results were compared with those based on the conventional reliability methods in the literature. Results show the high accuracy of proposed approach while the number of requires structural modeling were substantially reduced.

Sounds detection in the water is one of the main challenges of researchers in the sonar field. This challenge will become more complex when the depth of the sea is low or published sound is negligible. Usually Target detection in sonar system is performed with a fix defined threshold that it will increase the detection error. The purpose of this paper is to present a new target detection method in passive sonar using adaptive threshold. In the proposed method, adaptive threshold due to the statistical analysis and Bayesian classifier applied in both time and frequency domains. Particle Filter is used to calculate prior pdf in Bayesian classifier. Finally target detection point is calculated after fusion detection points in time and frequency domains by adaptive filter. The results indicate that the proposed method has better performance (23%) than recent methods in passive sonar target detection issue.

Continuous increase in fuel prices and its variations together with the emerged environmental pollutions cause to tendency to the renewable energy sources. However, the variable and uncertain natures of these generations as well as the market pressure due to the electricity market background threat the network security. Therefore, the recognition of the security index states in different operation conditions and considering the preventive and corrective actions are vital. Employment of the expected value of the uncertain variables for the power system security analysis would result in unrealistic outcomes and threatening of the power system security. Conventional approaches relying on the analysis of the large sum of scenarios such as Monte Carlo method are not efficient in the realistic large scale power systems due to the high computational burden and required time. This paper, in order to analysis the power system security, uses a point estimation method which consider the uncertainty while still has the satisfactory computational burden and time. The proposed method is examined on several power system test cases and its ability to effective uncertainty modeling in acceptable time is shown.

Security constrained unit commitment (SCUC) is a difficult optimization problem by which the generators optimal output are scheduled over the whole dispatch period. Here, different constraints such as demand and generation equality, generators limits and transmission flow limit should be considered. This paper presents a new structure for SCUC in the presence of wind and load uncertainties. Here, demand responsive loads are called for alleviating the aforementioned uncertainties as well as minimizing the operation cost. Wind speed uncertainty is modeled by Wiebull probability distribution function as a probabilistic variable. Moreover Z_number is applied to model the demand uncertainty as a possibilistic variable. Then, demand is converted form Z_number model to fuzzy one. Demand bidding programs are also implemented to reduce demand at peak hours. Load reduction payment is modeled by a quadratic function of the reduced power. In this paper, α-cut and monte carlo methods are mixed together to solve the SCUC problem considering the abovementioned uncertainties. In order to evaluate the proposed framework, numerical simulations has been conducted over the modified IEEE-24 bus system.

This paper presents a new method¡ based on analytical relations and Monte Carlo simulation for calculating the lightning performance of overhead lines caused by direct strokes. The aim of the work is to reduce the computing time together with retaining enough accuracy to estimate the line lightning performance and performing the risk analysis of power networks. In the proposed method¡ some modified equations based on the calculation methods have been derived. Thereafter¡ to calculate the lightning overvoltages and lightning performance¡ Monte Carlo simulation has been applied to the derived equations. Considering the results of ATP simulation¡ in addition to significantly high speed calculation¡ the insulation risk of failure calculated by the proposed method is acceptable and valid for risk analysis of overhead lines. Also¡ the lightning performance can be predicted with good accuracy. However¡ all the stages of the proposed method are coded in MATLAB and no software simulating is required

In restructured power systems and in a wholesale power market, a distribution company as a market player intends to maximize its profit by utilizing its options. Hence determining an optimal energy acquisition strategy for a distribution company is vital, for attaining to this goal. However an important challenge for determining these strategies is forecasting other competitors and Generation companie's strategies and competitor's incomplete information must be considered as uncertainties in the problem. In this paper, an energy acquisition model for a distribution company with considering distributed generations, interruptible loads and information's uncertainties in a day-ahead electricity market has been presented. In the proposed method, distribution company energy acquisition strategy has been modeled as a two-level multi-objective optimization problem and has been solved by using nonlinear complementarities and L-P metric methods and then, the uncertainties in the competitor's information, has been applied to the model by using Monte Carlo method. An 8-bus system is employed to illustrate the proposed model and algorithm.