بهینه سازی مصرف انرژی در بخش ساختمان با استفاده از شبکه عصبی و الگوریتم PSO (مطالعه موردی شهرستان بندرعباس)

محورهای موضوعی : آلودگی هوا

فخری اله یاری ¹ ( دانشجوی دکتری گروه محیط زیست، دانشکده کشاورزی و علوم پایه دانشگاه آزاد اسلامی واحد رودهن، رودهن، ایران. )
آزیتا بهبهانی نیا ² ( استادیار گروه محیط زیست، دانشکده کشاورزی و علوم پایه دانشگاه آزاد اسلامی واحد رودهن، رودهن، ایران. *(مسوول مکاتبات) )
حسین رحامی ³ ( دانشیار دانشکده علوم مهندسی پردیس دانشکده های فنی دانشگاه تهران، تهران، ایران. )
مریم فراهانی ⁴ ( استادیار گروه محیط زیست، دانشکده کشاورزی و علوم پایه، دانشگاه آزاد اسلامی واحد رودهن، رودهن، ایران. )
سمیرا خدیوی ⁵ ( استادیار گروه محیط زیست، دانشکده کشاورزی و علوم پایه، دانشگاه آزاد اسلامی واحد رودهن، رودهن، ایران. )

تاریخ دریافت : 1399/04/04 تاریخ پذیرش : 1399/08/06 تاریخ انتشار : 1400/10/01

کلید واژه: نرم افزار Design Builder, بهینه سازی, انرژی, ساختمان, الگوریتم PSO, شبکه عصبی,

چکیده مقاله :

زمینه و هدف: مصرف انرژی در ساختمان ها یک سوم مصرف انرژی سالانه کشور را تشکیل می دهد، بنابراین ارائه راهکارهایی که بتواند مصرف انرژی را در این بخش کاهش دهد، حائز اهمیت است.روش بررسی: با استفاده از پرسشنامه و نظرات کارشناسان، پارامترهای موثر در بهینه سازی انرژی در سازمان نظام مهندسی ساختمان بندرعباس شناسایی شد. متغیرهایی مانند جنس مواد دیوار و سقف، مساحت و نوع پنجره ها، ضخامت عایق دیوار و سقف انتخاب شدند. حالت های مختلف با نرم افزار Design Builder بررسی شد. با آموزش دو شبکه عصبی مجزا نحوه اتصال ورودی ها به دو خروجی مهم یعنی میزان انرژی و دی اکسید کربن بدست آمد. و بهینه سازی با استفاده از الگوریتم PSO انجام شد.یافته ها: در مدل به دست آمده دیوار آجری با ضخامت عایق 5 سانتی متر، سقف تیرچه با ضخامت عایق 5 سانتی متر، شیشه سه جداره، نسبت پنجره های شمالی و شرقی به دیوار در یک جهت 70 درصد، نسبت پنجره جنوبی به دیوار جنوبی بین 41 به 43 است. درصد و نسبت پنجره غربی به دیوار غربی بین 65 تا 67 درصد است که در آن میزان انرژی و دی اکسید کربن حداقل است.بحث و نتیجه گیری: اگر انرژی به عنوان تابع هدف انتخاب شود، نتایج به‌دست‌آمده از PSO کاملاً با نتایج بهینه‌سازی برای زمانی که تابع هدف مقدار دی اکسید کربن است، مطابقت دارد. این دو تابع با یکدیگر همسو هستند و بهینه سازی یکی منجر به بهینه سازی دیگری می شود.

چکیده انگلیسی:

Background and Objective: Energy consumption in buildings accounts for one third of the country's annual energy consumption, so it is important to provide solutions that can reduce energy consumption in this sector.Material and Methodology: Using questionnaires and experts’ opinions, effective parameters in energy optimization in Construction Engineering Organization of Bandar Abbas were identified. Variables such as wall and ceiling material, area and type of windows, wall and ceiling insulation thickness were selected. Different modes were investigated with Design Builder software. By training two separate neural networks, how the inputs are connected to two important outputs, which is the amount of energy and carbon dioxide, was obtained. And optimization was performed using the PSO algorithm.Findings: In the obtained model, brick wall with insulation thickness of 5cm, beam roof with insulation thickness of 5cm, triple glazing, ratio of north and east windows to wall in the same direction 70%, ratio of south window to south wall between 41 to 43 percent and the ratio of the west window to the west wall is between 65 to 67 percent, in which the amount of energy and carbon dioxide is the minimum.Discussion and Conclusion: If the energy is selected as target function, the results obtained from the PSO are closely consistent with the optimization results for when the target function is the amount of carbon dioxide. These two functions are in line with each other, and optimizing one will lead to optimizing the other.

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