Optimal Operation of Ventilation Systems with an Evolutionary Computation Algorithm during a Fire

Ventilation is a critical element while managing fire events in closed spaces which involves the expulsion of heat and smoke from a fire building. HVAC systems are one of the most vital components for managing fire situation by reducing environment temperature and replacing oxygen to dilute weather. In this paper, a hierarchical control is developed to control the operation of HVAC system in case of fire. For a friendly environment behavior of fire management system, an intelligent optimizer is embedded to coordinate each HVAC unit for achieving high energy efficiency as well as control the condition. The proposed optimizer utilizes swarm intelligence to find the optimal solution that fulfills the control objectives. In order to determine the suitable control variables of the optimizer and find their impact on managing fire and energy consumption, the thermal and ventilation model of building environment as well as the energy model of HVAC system is built. For the purpose of controlling temperature and 𝐂𝐎𝟐 concentration as the fire parameters, we present a comprehensive model based on ventilation system and fire parameters. Since temperature and 𝐂𝐎𝟐 concentration are the most important parameters in any fire event, the model examines the effect of various airflow rates of mechanical ventilation on wall and ceiling temperatures, Heat Release Rate, carbon dioxide rates when smoke/fire is detected. The objective of this paper is to propose a friendly environment fire management system to control the temperature, and gas rates in the room, as well as reducing the power consumption, until fire fighters have control of the situation. The simulation is done in MATLAB to show the advantage of this work comparison to conventional methods.