Development, Validation, and Application of Building Energy Simulation Models for Livestock Houses: A Systematic Review

Abstract

The need to improve the sustainability of intensive livestock farming has led to an increasing adoption of Building Energy Simulation (BES) models for livestock houses. However, a consolidated body of knowledge specifically dedicated to these models is lacking in literature. This gap represents a significant obstacle to their widespread application and scalability in research and industry. The aim of this work is to pave the way for scaling the adoption of BES models for livestock houses by providing a comprehensive analysis of their application, development, and validation. For this aim, a systematic review of 42 papers—selected from over 795 results from the initial database query—is carried out. The findings underscored a growing body of research that involves BES models for different purposes. However, a common approach in both model development and validation is still lacking. This issue could hinder their scalability as a standard practice, especially in industry, also considering the limitations of BES models highlighted in this work. This review could represent a solid background for future research since provides an up-to-date framework on BES models for livestock houses and identifies future research opportunities. Moreover, it contributes to increasing the reliability of BES models for livestock houses by providing some recommendations for their validation.

Alternative Heating, Ventilation, and Air Conditioning (HVAC) System Considerations for Reducing Energy Use and Emissions in Egg Industries in Temperate and Continental Climates: A Systematic Review of Current Systems, Insights, and Future Directions

“…The implemented simulation model is a lumped-parameter model based on the perfect-mixing assumption (i.e., uniform indoor air temperature). This simulation approach is widely adopted for energy analyses of livestock houses, as highlighted in a specific literature review focused on the topic [44]. Additionally, the robustness of the 5R1C method [40] is also demonstrated by its adoption in other contexts, such as pig houses [45], greenhouses [46], and residential buildings [47].…”