fuel cell voltage control for load variations using neural networks
نویسندگان
چکیده
in the near future the use of distributed generation systems will play a big role in the production ofelectrical energy. one of the most common types of dg technologies , fuel cells , which can be connectedto the national grid by power electronic converters or work alone studies the dynamic behavior andstability of the power grid is of crucial importance. these studies need to know the exact model of dynamicelements. in this paper, a new method based on a neural network algorithm for controlling the fuel cellvoltage is provided. the effects of load change the output voltage characteristic of the fuel cell unit ischecked simulations in matlab / simulink. the results show that the prosecution is conducted in anappropriate manner voltage stabilization time.
منابع مشابه
Fuel Cell Voltage Control for Load Variations Using Neural Networks
In the near future the use of distributed generation systems will play a big role in the production ofelectrical energy. One of the most common types of DG technologies , fuel cells , which can be connectedto the national grid by power electronic converters or work alone Studies the dynamic behavior andstability of the power grid is of crucial importance. These studies need to know the exact mo...
متن کاملrodbar dam slope stability analysis using neural networks
در این تحقیق شبکه عصبی مصنوعی برای پیش بینی مقادیر ضریب اطمینان و فاکتور ایمنی بحرانی سدهای خاکی ناهمگن ضمن در نظر گرفتن تاثیر نیروی اینرسی زلزله ارائه شده است. ورودی های مدل شامل ارتفاع سد و زاویه شیب بالا دست، ضریب زلزله، ارتفاع آب، پارامترهای مقاومتی هسته و پوسته و خروجی های آن شامل ضریب اطمینان می شود. مهمترین پارامتر مورد نظر در تحلیل پایداری شیب، بدست آوردن فاکتور ایمنی است. در این تحقیق ...
Efficient Short-Term Electricity Load Forecasting Using Recurrent Neural Networks
Short term load forecasting (STLF) plays an important role in the economic and reliable operation ofpower systems. Electric load demand has a complex profile with many multivariable and nonlineardependencies. In this study, recurrent neural network (RNN) architecture is presented for STLF. Theproposed model is capable of forecasting next 24-hour load profile. The main feature in this networkis ...
متن کاملA Combined Voltage Control Strategy for Fuel Cell
Li Sun 1 ID , Qingsong Hua 2, Jiong Shen 1,*, Yali Xue 3, Donghai Li 3 and Kwang Y. Lee 4 1 Key Lab of Energy Thermal Conversion and Control of Ministry of Education, Southeast University, Nanjing 210096, China; [email protected] 2 School of Mechanical and Electrical Engineering, Qingdao University, Ningxia Road 308, Qingdao 266071, China; [email protected] 3 State Key Lab for Power Systems, Tsi...
متن کاملDynamic Sliding Mode Control of Nonlinear Systems Using Neural Networks
Dynamic sliding mode control (DSMC) of nonlinear systems using neural networks is proposed. In DSMC the chattering is removed due to the integrator which is placed before the input control signal of the plant. However, in DSMC the augmented system is one dimension bigger than the actual system i.e. the states number of augmented system is more than the actual system and then to control of such ...
متن کاملneural classifier ensemble using error-correcting output codes: access control application
abstract biometric access control is an automatic system that intelligently provides the access of special actions to predefined individuals. it may use one or more unique features of humans, like fingerprint, iris, gesture, 2d and 3d face images. 2d face image is one of the important features with useful and reliable information for recognition of individuals and systems based on this ...
منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
journal of artificial intelligence in electrical engineeringناشر: ahar branch,islamic azad university, ahar,iran
ISSN 2345-4652
دوره 3
شماره 10 2014
میزبانی شده توسط پلتفرم ابری doprax.com
copyright © 2015-2023