فهرس المقالات Noradin Ghadimi


  • المقاله

    1 - Optimal Controller for Single Phase Island Photovoltaic Systems
    journal of Artificial Intelligence in Electrical Engineering , العدد 2 , السنة 3 , تابستان 2014
    Increasing of word demand load caused a new Distributed Generation (DG) to enter to powersystem. One of the most renewable energy is the Photovoltaic System. It is beneficial to use thissystem in both separately as well as connected to power system using power electroni أکثر
    Increasing of word demand load caused a new Distributed Generation (DG) to enter to powersystem. One of the most renewable energy is the Photovoltaic System. It is beneficial to use thissystem in both separately as well as connected to power system using power electronics interface.In this paper an optimal PID controller for Photovoltaic System systems has been developed. Theoptimization technique is applied to PID optimal controller in order to control the voltage ofPhotovoltaic System against load variation, is presents. Nonlinear characteristics of loadvariations as plant input, Photovoltaic System operational behavior demand for high qualityoptimal controller to ensure both stability and safe performance. Thus, Honey Bee MatingOptimization (HBMO) is used for optimal tuning of PID coefficients in order to enhance closedloop system performance. In order to use this algorithm, at first, problem is written as anoptimization problem which includes the objective function and constraints, and then to achievethe most desirable controller, HBMO algorithm is applied to solve the problem. In this study, theproposed controller is applied to the closed loop photovoltaic system behavior. Simulation resultsare done for various loads in time domain, and the results show the efficiency of the proposedcontroller in contrast to the previous controllers. تفاصيل المقالة

  • المقاله

    2 - Reinforcement Learning Based PID Control of Wind Energy Conversion Systems
    journal of Artificial Intelligence in Electrical Engineering , العدد 4 , السنة 3 , پاییز 2014
    In this paper an adaptive PID controller for Wind Energy Conversion Systems (WECS) has been developed. Theadaptation technique applied to this controller is based on Reinforcement Learning (RL) theory. Nonlinearcharacteristics of wind variations as plant input, wind tur أکثر
    In this paper an adaptive PID controller for Wind Energy Conversion Systems (WECS) has been developed. Theadaptation technique applied to this controller is based on Reinforcement Learning (RL) theory. Nonlinearcharacteristics of wind variations as plant input, wind turbine structure and generator operational behaviordemand for high quality adaptive controller to ensure both robust stability and safe performance. Thus, areinforcement learning algorithm is used for online tuning of PID coefficients in order to enhance closed loopsystem performance. In this study, at start the proposed controller is applied to two pure mathematical plants,and then the closed loop WECS behavior is discussed in the presence of a major disturbance. تفاصيل المقالة