Soğuk Hava Depolarında Talep Kontrollü Buz Çözme (Defrost) Uygulamaları

Soğuk depolarda evaporatörler donma noktasının altındaki sıcaklıklarda çalışırken, yüzeylerinde kar birikerek soğutma kapasitesini ve etkinliğini azaltır. Karlanmayı gidermek, kapasite ve verimliliği geri kazanmak için evaporatördeki bu kar evaporatöre çeşitli yöntemler ile ısı ekleyerek çözülür. Bu ısıtma işleminde, evaporatöre verilen ısının ancak %25 ila %35 oranındaki kısmı karın erimesine, kalan diğer %65 ila %75’lik kısmı ise iç ortama verilir. Ayrıca buz çözme işlemi zamana bağlı olarak yapıldığında çoğunlukla yüzeylerde yeterli kar birikimi olmadan sistem buz çözme döngüsüne geçer. Bu da iç ortamda istenmeyen sıcaklık artışlarına ve enerji kayıplarına yol açar. Günümüzde mevcut buz çözme yöntemleri çok fazla değişmemekle birlikte kontrol stratejileri çok gelişmiş olup talep kontrollü, adaptif, yapay zekâ destekli buz çözme kontrol yöntemleri geliştirilmiştir. Bu kontrol stratejilerinin temelinde kar birikimini doğrudan ve dolaylı olarak ölçen ve dolayısıyla buz çözme talebini algılayan teknolojiler bulunmaktadır. Bu çalışmada evaporatörlerde karlanma nedenleri açıklanmış, geleneksel buz çözme yöntemleri üzerinde ayrıntılı durulmuştur. Son bölümde talep kontrollü buz çözme kontrol stratejileri ayrıntılı olarak incelemiştir

Demand Controlled Defrost Applications inCold Rooms

While evaporators are operating at temperatures below freezing in cold storages, frost accumulates on their surfaces , reducing the cooling capacity and efficiency. To remove the frost and restore capacity and efficiency, this frost in the evaporators is solved by adding heat to the evaporator with various methods. In this heating process, only 25% to 35% of the heat given to the evaporator is given to the ice to melt and the remaining 65% to 75% is given to the indoor environment. In addition, when the defrosting process is carried out depending on the time, the system often goes into a defrost cycle without sufficient frost accumulation on the surfaces. This leads to undesirable temperature increases and energy losses in the indoor environment, although the current defrosting methods do not change much, control strategies are very advanced and demand-controlled, adaptive, artificial intelligence-assisted defrosting control methods have been developed. At the heart of these control strategies are technologies that directly and indirectly measure ice build-up and thus perceive defrost demand. In this study, the reasons for icing in evaporators are explained and traditional defrosting methods are discussed in detail. In the last section, demand controlled defrosting control strategies are examined in detail.

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