فهرس المقالات Sarang Ezazi


  • المقاله

    1 - Performance Optimization of Double Absorption Heat Transformers Using Genetic Algorithm in Order to Minimize Physical Exergy Destruction
    journal of Artificial Intelligence in Electrical Engineering , العدد 1 , السنة 9 , بهار 2021
    In the present study, double absorption heat transformers that are known as a desirable technology for the reuse of medium level waste heat energy are investigated. The main parameter that is considered as well as others is physical exergy destruction. Through an optimi أکثر
    In the present study, double absorption heat transformers that are known as a desirable technology for the reuse of medium level waste heat energy are investigated. The main parameter that is considered as well as others is physical exergy destruction. Through an optimization process by the Genetic algorithm, it is found that the new configuration has 14.3% and 3.36% higher distilled water and the COP compared to those parameters for common third type DAHT. When it comes to the total exergy destruction, it is 5.7% higher in comparison to the third type DAHT. Thermodynamic analysis and optimization are performed through EES. تفاصيل المقالة

  • المقاله

    2 - A Risk-Averse Energy Management in Micro-grids on Information Gap Decision Theory Using the Genetic Algorithm
    journal of Artificial Intelligence in Electrical Engineering , العدد 4 , السنة 10 , پاییز 2021
    In this paper, energy management in a Micro-grid connected to the distribution network has been done with the aim of reducing the cost of operating the Micro-grids and reducing the environmental pollution index. The Genetic Algorithm method is used to optimize the objec أکثر
    In this paper, energy management in a Micro-grid connected to the distribution network has been done with the aim of reducing the cost of operating the Micro-grids and reducing the environmental pollution index. The Genetic Algorithm method is used to optimize the objective function and find Pareto solutions. The Information Gap Decision-making Method has been used to select the appropriate answers from Pareto's set of answers. In the meanwhile, the participation rate of each of the distributed generator sources and the charge and discharge planning of the energy storage system to provide the Micro-grids load has been calculated. In addition, the interaction between the Micro-grids and the distribution network is important. To analyze the proposed method, a planning problem using multi-priced electricity tariffs is presented as an advantage of the energy storage system. To demonstrate the effectiveness of the multivariate optimization method presented in this thesis, modeling and simulation of diesel generators and energy storage in a Micro-grid have been performed. Mathematical models based on probability density functions, renewable energy sources and consumer load have been investigated. Minimizing the cost of fuel to generate power in the Micro-grids, uncertainty related to renewable sources and Micro-grids load consumption has been modeled using the Information Gap Decision-making Method of maximum uncertainty radius for renewable units and load consumption. The results of the Information Gap Decision Method are compared with conventional methods based on probabilistic function analysis such as the scenario tree method. The results presented in this dissertation show the advantages of the proposed method to improve the overall performance of independent and connected Micro-grids to the distribution network. تفاصيل المقالة