Amirkabir University of Technology

About: Amirkabir University of Technology is a education organization based out in Tehran, Iran. It is known for research contribution in the topics: Nonlinear system & Finite element method. The organization has 15254 authors who have published 31165 publications receiving 487551 citations. The organization is also known as: Tehran Polytechnic & Tehran Polytechnic University.

Distributed Fault Detection and Isolation Filter Design for a Network of Heterogeneous Multiagent Systems

Abstract: In this brief a distributed fault detection and isolation (FDI) methodology for a network of heterogeneous multiagent systems with different dynamics and order from one another is proposed. An FDI filter is designed such that the effects of disturbances and control inputs on the residual signals are minimized (for accomplishing the fault detection task) subject to the constraint that the transfer matrix function from the faults to the residuals is equal to a preassigned diagonal transfer matrix (for accomplishing the fault isolation task). Moreover, by utilizing the proposed methodology, isolation of simultaneous occurring faults can also be handled. Sufficient conditions for solvability of the problem are obtained in terms of linear matrix inequality (LMI) feasibility conditions. The extended LMI characterization is then used to reduce the conservativeness of the solution by eliminating the couplings between the Lyapunov matrices and the agents' matrices. Simulation results presented demonstrate the effectiveness and capabilities of our proposed design methodology.

A Novel Policy for Locational Marginal Price Calculation in Distribution Systems Based on Loss Reduction Allocation Using Game Theory

Abstract: In this paper, a novel locational marginal price (LMP) policy for distribution system with significant penetration of distribution generation (DG) in competitive electricity market is presented. This new LMP method is based on remunerating DG units for their participation in reduced amount of energy losses in distribution systems brought about by participation of all DG units in supplying demand. Also, this method is combined with an iterative solution. This approach provides an efficient tool for distribution companies (DISCOs) to estimate the state of the system in the next step which other existing approaches of LMP fail to provide this system state estimation. Finally, in order to expand LMP method and provide effective prediction method for DISCOs to estimate the day-ahead state of the system, ANN tool is employed to predict the market price and demand for the next 24 h. This LMP prediction is a powerful operational tool for DISCO to exert its control over private DG units. However, prediction methods contain error. Therefore, uncertainty modeling is implemented for modeling the effect of error in prediction on the LMP calculation for the next day.