شبیه‌سازی عملکرد انرژی، اقتصادی و زیست‌محیطی یک سیستم میکروژنراتوری مجتمع ترکیبی با کنترل پیش‌بینی شبکه عصبی

شبیه‌سازی عملکرد انرژی، اقتصادی و زیست‌محیطی یک سیستم میکروژنراتوری مجتمع ترکیبی با کنترل پیش‌بینی شبکه عصبی

Energy, economic and environmental performance simulation of a hybrid renewable microgeneration system with neural network predictive control

سال نشر:

2016

نویسندگان:

Evgueniy Entchev Sergio Sibilio , Libing Yang, Mohamed Ghorab, Antonio Rosato

تعداد صفحه فارسی/انگلیسی:

19

کلمات کلیدی:

Hybrid microgeneration system; Ground source heat pump; Photovoltaic thermal; Artificial neural network; Predictive control; Energy saving

دانشگاه

Alexandria University

نشریه

Alexandria Engineering Journal

چکیده مقاله

ABSTRACT

Abstract The use of artificial neural networks (ANNs) in various applications has grown significantly over the years. This paper compares an ANN based approach with a conventional on-off control applied to the operation of a ground source heat pump/photovoltaic thermal system serving a single house located in Ottawa (Canada) for heating and cooling purposes. The hybrid renewable microgeneration system was investigated using the dynamic simulation software TRNSYS. A controller for predicting the future room temperature was developed in the MATLAB environment and six ANN control logics were analyzed The comparison was performed in terms of ability to maintain the desired indoor comfort level sprimary energy consumption, operating costs and carbon dioxide equivalent emissions during a week of the heating period and a week of the cooling period. The results showed that the AN approach is potentially able to alleviate the intensity of thermal discomfort associated with overheating/over cool in phenomena, but it could cause an increase in unmet comfort hours. The analysis(up to around 36%), the operating costs (up to around 81%) as well as the carbon dioxide equivalent(up to around 36%), the operating costs (up to around 81%) as well as the carbon dioxide equivalent emissions (up to around 36%).

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