List of Articles بهینه‌سازی سیستم صفحات شیب‌دار

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  1 - Stochastic Planning of Resilience Enhancement for Electric Power Distribution Systems against Extreme Dust Storms
  M. Haghshenas R. Hooshmand M. Gholipour
  Resilience in power systems refers to the system's ability to withstand severe disturbances with a low probability of occurrence. Because in recent years extreme dust storms have caused severe damage to Iran's electricity industry, especially in the south and southwest, More

  Resilience in power systems refers to the system's ability to withstand severe disturbances with a low probability of occurrence. Because in recent years extreme dust storms have caused severe damage to Iran's electricity industry, especially in the south and southwest, in this paper proposed a new scenario-based stochastic planning model for enhancement of power distribution systems resilience against extreme dust storms. In proposed model, in the first stage, the investment costs to improve the distribution system resilience against extreme dust storms are minimized due to the financial constraints, and in the second stage, the expected operating costs in dust storm conditions are minimized due to the operating constraints. Because network's insulation equipment are major cause of distribution system vulnerabilities in the dust storms, measures in the planning stage include replacement of porcelain insulators with silicon-rubber type, installation of automatic tie switches and installation of emergency generators. In the second stage, the measures are divided into preventive actions and corrective actions, and coordination between stages 1 and 2 is implemented in such a way that the results of each stage depend on the decision variables of the other stage. The simulation results for IEEE 33-bus test system and a 209 bus radial distribution network located in Khuzestan province, Iran, confirm the efficiency of the proposed model in different financial conditions. Manuscript profile
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  2 - Novel AI-Based Metaheuristic Optimization Approaches for Designing INS Navigation Systems
  علی محمدی Farid Sheikholeslam Mehdi  Emami
  Soft computing techniques in engineering sciences have covered a large amount of research. Among them is the design and optimization of navigation systems for use in land, sea, and air transportation systems. Therefore, in this paper, an attempt is made to take advantag More

  Soft computing techniques in engineering sciences have covered a large amount of research. Among them is the design and optimization of navigation systems for use in land, sea, and air transportation systems. Therefore, in this paper, an attempt is made to take advantage of novel approaches of intelligent metaheuristic optimization for designing integrated navigation systems. For this purpose, the inclined planes system optimization algorithm with several modified and new versions have been used along with two well-known methods of genetic algorithm and particle swarm optimization. Considerations are made on an INS/GNSS problem with IMU MEMS inertia measurement modules. Process and measurement noise covariance matrices are considered as design variables and the sum of mean-squares-error as an objective function in the form of a single-objective minimization problem. Outputs are presented in terms of statistical and performance indicators such as runtime, fitness, convergences, angular-velocity accuracy, latitude, longitude, altitude, roll, pitch, yaw, and routing along with the ranking of algorithms. The overall assessment indicated the correctness of the performance and the relative superiority of the IPO and IIPO over the competitors and competitive performance of the assumed algorithms in comparison with the volume of considerations and calculations of the base problem. Manuscript profile