Sharif Digital Repository

This Paper presents a model for optimal locating and sizing of Distributed Generation (DG) for congestion management in deregulated electricity market. For reducing the solution space a priority list of candidate buses is formed and then optimal placement and sizing of DG in potential buses is discussed. In order to incorporate stochastic nature of power system in this study, Monte-Carlo method is used to simulate the effect of uncertainty of loads and system on the optimal location and size of the DGs in the network. The proposed method is applied to IEEE Reliability Test System (RTS). The impacts of load uncertainty on optimum DG size and location are studied  

This paper presents a stochastic framework to properly involve the uncertainties associated with demand in distribution system restoration (DSR) problem. To reach this goal, these uncertainties are represented as probabilistic scenarios corresponding to different load levels. Subsequently, the associated stochastic optimization problem is formulated such that it can be readily solved using dynamic programming approach. Moreover, a clustering technique is presented that enables the dynamic programming approach to find near-optimal solutions for the stochastic load restoration problem with reasonable computational effort. The proposed framework is implemented on a real-world test system, and... 

This study introduces a novel Bayesian framework for online and real-time vibration control of beam type structures, which represent a comprehensive control system associated with input-state algorithms. Control design systems typically require knowledge of system states, which in structures are displacements and velocities at some degrees of freedom. Currently, full-field measurements of displacements and velocities in large structural systems are not feasible. Also, properties of the moving inertial loads as key parameters in control designs are assumed known; however, in practice, measuring their characteristics is a challenging issue. As a remedy, an observer is required to estimate... 

Background: Asymmetric lifting activities are associated with low back pain. Methods: A finite element biomechanical model is used to estimate spinal loads during one- and two-handed asymmetric static lifting activities. Model input variables are thorax flexion angle, load magnitude as well as load sagittal and lateral positions while response variables are L4-L5 and L5-S1 disc compression and shear forces. A number of levels are considered for each input variable and all their possible combinations are introduced into the model. Robust yet user-friendly predictive equations that relate model responses to its inputs are established. Findings: Predictive equations with adequate...