Binalarda Güneş Kontrol Yöntemlerinin Optimizasyon Temelli Performans Değerlendirilmesi

Year 2017, Volume: 5 Issue: 3, 71 - 87, 15.09.2017

İpek Gürsel Dino

Abstract

Bu çalışmada, binalarda farklı güneş kontrol yöntemlerinin karşıtlaştırmalı analizini, bir genetik optimizasyon algoritması ile destekleyen bir tasarım aracı ve yöntem, önerilmektedir. Çalışmada ilk olarak farklı cam alternatifleri ve sıklıkla kullanılan bazı standart gölgeleme yöntemlerinin oluşturduğu sekiz senaryo geliştirilmiştir. Ardından bu senaryolar, örnek bir bina tasarımı üstünde uygulanarak genetik optimizasyon algoritması uygulanmıştır. Algoritma, pencere büyüklüklerini ve gölgelik boyut parametrelerini değişken olarak alarak, enerji tüketimini ve günışığı aydınlatmasını optimize etmektedir. Bu algoritma kullanılarak, her senaryo için binanın Pareto çözümleri hesaplanmıştır. Bu Pareto çözümler kullanılarak, farklı güneş kontrol senaryolarının birbirleriyle olan karşılaştırmalı analizi yapılmıştır. Çalışmada elde edilen sonuçlara göre optimal güneş kontrol yöntemleri ile, bir binanın günışığı aydınlatma performansını azaltmadan %25’e kadar enerji tasarrufu sağlanabilmekte, pencere büyüklükleri ise 123% oranında arttırılabilmektedir. Daha genel bir açıdan bakıldığında ise, önerilen optimizasyon temelli analiz yöntemi, tasarım süreçlerinde farklı güneş kontrol alternatiflerinin sayısal karşılaştırmalı değerlendirilmesini destekleyebilmektedir.

Keywords

Bina güneş kontrolü, Bina enerji tüketimi, Bina günışığı aydınlatması, Çok-objektifli genetik optimizasyon, Pareto-temelli tasarım analizi

The Performance Evaluation of Solar Control Methods in Buildings: A Multi-Objective Approach

Abstract

In this study, a tool and method that support the analysis of different solar control methods in buildings through a genetic optimization algorithm are proposed. First, eight scenarios of different glazing alternatives and standard shading methods were developed. These scenarios were implemented on a sample building design and the genetic optimization algorithm was run. The algorithm optimizes energy consumption and daylight illumination using an existing energy simulation tool, taking window sizes and shading parameters as variables. Using this algorithm, the building's Pareto solutions are calculated for each scenario. Using these Pareto solutions, a comparative analysis of the different solar control scenarios was made. According to the results obtained in the study, it is possible to achieve energy savings up to 25% and to increase the window size by 123% with optimal solar control methods, without decreasing the daylighting performance of a building. The proposed optimization-based analysis method can support numerical comparative evaluation of different solar control alternatives in the design process.

Keywords

Building solar control, Building energy use, Building daylighting, Multi-objective genetic optimization, Pareto-based design analysis

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