The Energy Savings and Environmental Benefits for Small and Medium Enterprises by Cloud Energy Management System

Abstract

Small and medium enterprises (SMES) play an important role in Taiwan's economy. The reduction of energy costs and carbon dioxide (CO 2 ) emissions are critical to preserving the environment. This paper uses the experimental results from 65 sites, gathered over two years since 2012, to determine how the integration of Internet communication, cloud computing technologies and a cloud energy management service (cloud EMS) can reduce energy consumption by cost-effective means. The EMS has three levels: infrastructure as a service (IaaS), platform as a service (PaaS) and software as a service (SaaS). Working jointly with ChungHwa Telecom, Taiwan's leading telecom service provider, data from detection devices, control devices, air-conditioning and lighting systems are all uploaded to a cloud EMS platform, to give a so called intelligent energy management network application service platform (IEN-ASP). Various energy saving management functions are developed using this platform: (1) air conditioning optimization; (2) lighting system optimization; (3) scheduling control; (4) power billing control and (5) occupancy detection and timing control. Using the international performance measurement and verification protocol (IPMVP), the energy used at the test sites, before and after the use of the IEN-ASP, are compared to calculate the energy saved. The experimental results show that there is an average energy saving of 5724 kWh per year, which represents a saving ratio of 5.84%. This translates to a total reduction in CO 2 emissions of 9,926,829 kg per year. Using the data collected, a regression model is used to demonstrate the correlation between the power that is consumed, the energy that is saved and the area of the sites. Another interesting result is that, if the experimental sites are maintained by experienced electricians or other personnel and EMS protocols are followed, the energy saving can be as great as 6.59%.

A Visualization Review of Cloud Computing Algorithms in the Last Decade

“…Khanghahi and Ravanmehr [40] also listed some specific cloud computing performance indicators such as average response time per unit time, network capacity per second, average waiting time per unit time, and percentage of CPU utilization. Nevertheless, only the energy efficiency is detected in our work, which reveals that more and more attention is paid to energy saving and environmental friendliness in the research of cloud computing algorithms, as stated by Tseng et al [20].…”

“…In the literature, various aspects on cloud computing have been reported, such as service availability [5,6,16], computing schemes and algorithms [17,18], data security [10][11][12]19], and energy management [9,20]. Among these aspects, advanced algorithms are the key to conducting the computing across various clouds, which have drawn special attention.…”

Artificial intelligence implementation framework development for building energy saving

“…The Microsoft Azure Platform and MATLAB Simulink are both cloud services as discussed in previous section. [105][106][107][108][109] Distributed AI is employed to transfer commands from the cloud service to local equipment. The MAS was developed.…”

Evaluation and Utilization of Thermal Environment Associated with Policy: A Case Study of Daegu Metropolitan City in South Korea

“…In addition, the total area that reflects and absorbs sunlight has expanded owing to the high heat capacity of building materials, such as concrete. Higher heat absorption of buildings and lower radiation cooling have led to high building temperatures, which then increases air conditioning usage and artificial exhaust airflow [4][5][6][7][8][9]. As the pavement surface area has expanded because of artificial materials such as asphalt, the green belt and water surface areas have shrunk.…”