A Conceptual Model for Simulation-Based Optimization of HVAC Systems Using Heat Flow Analytics

• Author(s): Enoch Oluwadunmininu Ogunnowo ; Musa Adekunle Adewoyin ; Joyce Efekpogua Fiemotongha ; Thompson Odion Igunma ; Adeniyi K. Adeleke
• Paper ID: 1708637
• Page: 206-221
• Published Date: 31-08-2021
• Published In: Iconic Research And Engineering Journals
• Publisher: IRE Journals
• e-ISSN: 2456-8880
• Volume/Issue: Volume 5 Issue 2 August-2021

Abstract

Heating, Ventilation, and Air Conditioning (HVAC) systems account for a substantial portion of energy consumption in residential, commercial, and industrial buildings. This paper presents a conceptual model for simulation-based optimization of HVAC systems using heat flow analytics, aimed at enhancing energy efficiency, indoor comfort, and environmental sustainability. The model integrates thermodynamic principles, computational fluid dynamics (CFD), and data-driven algorithms to simulate real-time heat flow behaviors and identify optimal configurations for HVAC operations under varying climatic and occupancy conditions. The proposed framework is structured around three core components: dynamic thermal modeling, real-time heat transfer analytics, and optimization algorithms. Dynamic thermal modeling captures the transient response of building zones to HVAC interventions, leveraging heat balance equations and thermal resistance-capacitance networks. Heat flow analytics employs high-resolution sensors and IoT-enabled data acquisition systems to monitor temperature gradients, airflow distribution, and energy loads. This data is then processed using simulation software to validate the thermal performance of HVAC subsystems. Optimization is achieved using multi-objective algorithms that consider variables such as energy consumption, occupant comfort indices (e.g., PMV/PPD), operational cost, and carbon emissions. The model allows iterative simulations to evaluate system performance across different control strategies—such as variable air volume (VAV), chilled beam systems, or demand-controlled ventilation (DCV). Additionally, the integration of weather forecast data and occupancy prediction enhances the model’s responsiveness to external and internal conditions. A case study of a mid-sized office building demonstrates the model’s ability to reduce HVAC energy consumption by up to 27% while maintaining thermal comfort within acceptable limits. The study highlights the significance of incorporating spatial and temporal heat flow dynamics into HVAC system design and management. The conceptual model serves as a blueprint for developing advanced decision-support systems that can guide engineers, architects, and facility managers in implementing sustainable HVAC solutions. By bridging simulation, optimization, and real-time data analytics, this model contributes to the development of intelligent building systems that support national goals in energy conservation and emissions reduction.

Keywords

HVAC Optimization, Heat Flow Analytics, Simulation-Based Design, Thermal Modeling, Energy Efficiency, CFD, Smart Buildings, Building Performance Simulation.

Citations

IRE Journals:
Enoch Oluwadunmininu Ogunnowo , Musa Adekunle Adewoyin , Joyce Efekpogua Fiemotongha , Thompson Odion Igunma , Adeniyi K. Adeleke "A Conceptual Model for Simulation-Based Optimization of HVAC Systems Using Heat Flow Analytics" Iconic Research And Engineering Journals Volume 5 Issue 2 2021 Page 206-221

IEEE:
Enoch Oluwadunmininu Ogunnowo , Musa Adekunle Adewoyin , Joyce Efekpogua Fiemotongha , Thompson Odion Igunma , Adeniyi K. Adeleke "A Conceptual Model for Simulation-Based Optimization of HVAC Systems Using Heat Flow Analytics" Iconic Research And Engineering Journals, 5(2)