Optimization of energy consumption and thermal comfort for intelligent building management system using genetic algorithm

Abstract

This paper presents a design, simulation and performance evaluation of an optimized model for the Heating, Ventilation and Air-Conditioning (HVAC) systems using intelligent control algorithm. Fanger’s comfort method and genetic algorithms were used to obtain the optimal and initial values. The heat transmission coefficient between internal and external environments were determined depending on several inputs and factors acquired via supervisory control and data acquisition (SCADA) system sensors. The main feature of the real-time model is the prediction of the internal buildings environment, in order to control HVAC system for indoor environment and to utilize the optimum power consumed depending on optimized air temperature value. The predicted air temperature value and Predictive Mean Vote (PMV) value was applied using intelligent algorithm to obtain an optimal comfort level of the air temperature. The optimized air temperature value can be used in HVAC system controller to ensure that the temperature of indoor can reach a specific value after a known period of time. The use of genetic algorithm (GE) ensures that the used power is well below its peak value and maintains the comfort of the user’s environment.

[Retracted] Optimization of IoT‐Based Motion Intelligence Monitoring System

“…In the future, telemedicine and health monitoring can rely on the advantages of the physiological collection sensor device and wireless connection technology provided by the Internet of ings to be well developed. e IoT technology-based sport intelligence monitoring device integrates a variety of sensors to monitor whether the user has an accident and the user's heart rate, the environmental parameters, etc., and transmits the data collected by the sensing layer sensor devices back to the One NET IoT open platform through the NB module, and the system will automatically trigger the platform end trigger after detecting the abnormal phenomenon, which will promptly notify the preset [10]. e system will automatically trigger the trigger at the platform after detecting anomalies, and the trigger will promptly notify the predefined emergency contact.…”

Machine Learning Algorithms for Predicting Energy Consumption in Educational Buildings

“…These integrated mechanisms are commonly referred to as hybrid networks. For example, Mohammed et al [19] focus on the application of an intelligent control algorithm in HVAC systems to enhance energy efficiency and thermal comfort. The authors propose integrating SCADA systems with an intelligent building management system to optimize heat transmission coefficients and air temperature values.…”

“…Genetic algorithms are employed to maintain user comfort while minimizing energy consumption. Similar to [19], Aurna et al [20] compare the performance of ARIMA and Holt-Winters models in predicting energy consumption data in Ohio and Kentucky. The study finds that the Holt-Winters model is more accurate and effective for long-term forecasting.…”

Studies enhancement of transient stability by single machine infinite bus system and setting purpose genetic algorithm

“…This method can be applied in an intrusion detection system to identify the attack and enhance the security features of a computer network [20], [21]. GA was exercised to procure the values to improve heating, ventilation and air conditioning (HVAC) model [22]. GA was used to improve the parameters of the based Thyristor controlled series compensator (TCSC) controller to improve stability.…”