An online electricity cost budgeting algorithm for maximizing green energy usage across data centers

2017 ◽  
Vol 11 (4) ◽  
pp. 661-674 ◽  
Author(s):  
Hui Dou ◽  
Yong Qi
Keyword(s):  
Data Centers ◽  
Green Energy ◽  
Energy Usage ◽  
Electricity Cost

scholarly journals Optimized Energy Cost and Carbon Emission-Aware Virtual Machine Allocation in Sustainable Data Centers

2020 ◽  
Vol 12 (16) ◽  
pp. 6383
Author(s):  
T. Renugadevi ◽  
K. Geetha ◽  
K. Muthukumar ◽  
Zong Woo Geem
Keyword(s):  
Virtual Machine ◽  
Carbon Emission ◽  
Data Centers ◽  
Carbon Tax ◽  
Operating Cost ◽  
Green Energy ◽  
Energy Usage ◽  
Electricity Cost ◽  
Machine Allocation ◽  
The Impact

Cloud data center’s total operating cost is conquered by electricity cost and carbon tax incurred due to energy consumption from the grid and its associated carbon emission. In this work, we consider geo-distributed sustainable datacenter’s with varying on-site green energy generation, electricity prices, carbon intensity and carbon tax. The objective function is devised to reduce the operating cost including electricity cost and carbon cost incurred on the power consumption of servers and cooling devices. We propose renewable-aware algorithms to schedule the workload to the data centers with an aim to maximize the green energy usage. Due to the uncertainty and time variant nature of renewable energy availability, an investigation is performed to identify the impact of carbon footprint, carbon tax and electricity cost in data center selection on total operating cost reduction. In addition, on-demand dynamic optimal frequency-based load distribution within the cluster nodes is performed to eliminate hot spots due to high processor utilization. The work suggests optimal virtual machine placement decision to maximize green energy usage with reduced operating cost and carbon emission.

scholarly journals Minimal Green Energy Consumption and Workload Management for Data Centers on Smart City Platforms

2020 ◽  
Vol 12 (8) ◽  
pp. 3140 ◽  
Author(s):  
Pei Pei ◽  
Zongjie Huo ◽  
Oscar Sanjuán Martínez ◽  
Rubén González Crespo
Keyword(s):  
Energy Consumption ◽  
Smart City ◽  
Energy Use ◽  
Data Centers ◽  
Renewable Energy Sources ◽  
Global Market ◽  
Green Energy ◽  
Workload Management ◽  
Multi Objective Genetic Algorithm ◽  
Delay Tolerant

Presently, energy is considered a significant resource that grows scarce with high demand and population in the global market. Therefore, a survey suggested that renewable energy sources are required to avoid scarcity. Hence, in this paper, a smart, sustainable probability distribution hybridized genetic approach (SSPD-HG) has been proposed to decrease energy consumption and minimize the total completion time for a single machine in smart city machine interface platforms. Further, the estimated set of non-dominated alternative using a multi-objective genetic algorithm has been hybridized to address the problem, which is mathematically computed in this research. This paper discusses the need to promote the integration of green energy to reduce energy use costs by balancing regional loads. Further, the timely production of delay-tolerant working loads and the management of thermal storage at data centers has been analyzed in this research. In addition, differences in bandwidth rates between users and data centers are taken into account and analyzed at a lab scale using SSPD-HG for energy-saving costs and managing a balanced workload.

scholarly journals The Numerical Simulation of the Airflow Distribution and Energy Efficiency in Data Centers with Three Types of Aisle Layout

2019 ◽  
Vol 11 (18) ◽  
pp. 4937 ◽  
Author(s):  
Jing Ni ◽  
Bowen Jin ◽  
Shanglei Ning ◽  
Xiaowei Wang
Keyword(s):  
Energy Efficiency ◽  
Power Consumption ◽  
Air Conditioning ◽  
Data Centers ◽  
Simulation Method ◽  
Cooling Capacity ◽  
Energy Utilization ◽  
Improve Energy Efficiency ◽  
Electricity Cost ◽  
Airflow Distribution

The energy consumption of fast-growing data centers is drawing attentions from not only energy organizations and institutions all over the world, but also charity groups, such as Greenpeace, and research shows that the power consumption of air conditioning makes up a large proportion of the electricity cost in data centers. Therefore, more detailed investigations of air conditioning power consumption are warranted. Three types of airflow distributions with different aisle layouts (the open aisle, the closed cold aisle, and the closed hot aisle) were investigated with Computational Fluid Dynamics (CFD) methods in a typical data center of four rows of racks in this study. To evaluate the results of thermal and bypass phenomenon, the temperature increase index (β) and the energy utilization index (ηr) were used. The simulations show that there is a better trend of the β index and ηr index both closed cold aisle and closed hot aisle compared with free open aisle. Especially with high air flow rate, the β index decreases and the ηr index increases considerably. Moreover, the results prove the closed aisles (both closed cold aisle and closed hot aisle) can not only significantly improve the airflow distribution, but also reduce the mixture of cold and heat flow, and therefore improve energy efficiency. In addition, it proves the design of the closed aisles can meet the increasing density of installations and our simulation method could evaluate the cooling capacity easily.

scholarly journals New Data Center Performance Index: Perfect Design Data Center—PDD

Climate ◽  
2020 ◽  
Vol 8 (10) ◽  
pp. 110
Author(s):  
Alexandre F. Santos ◽  
Pedro D. Gaspar ◽  
Heraldo J. L. de Souza
Keyword(s):  
Data Center ◽  
Air Conditioning ◽  
Data Centers ◽  
Current Method ◽  
Energy Usage ◽  
Design Data ◽  
The Difference ◽  
Power Usage Effectiveness ◽  
Approximate Result ◽  
Classification Table

Data Centers (DC) are specific buildings that require large infrastructures to store all the information needed by companies. All data transmitted over the network is stored on CDs. By the end of 2020, Data Centers will grow 53% worldwide. There are methodologies that measure the efficiency of energy consumption. The most used metric is the Power Usage Effectiveness (PUE) index, but it does not fully reflect efficiency. Three DC’s located at the cities of Curitiba, Londrina and Iguaçu Falls (Brazil) with close PUE values, are evaluated in this article using the Energy Usage Effectiveness Design (EUED) index as an alternative to the current method. EUED uses energy as a comparative element in the design phase. Infrastructure consumption is the sum of energy with Heating, Ventilating and Air conditioning (HVAC) equipment, equipment, lighting and others. The EUED values obtained were 1.245 (kWh/yr)/(kWh/yr), 1.313 (kWh/yr)/(kWh/yr) and 1.316 (kWh/yr)/(kWh/yr) to Curitiba, Londrina and Iguaçu Falls, respectively. The difference between the EUED and the PUE Constant External Air Temperature (COA) is 16.87% for Curitiba, 13.33% for Londrina and 13.30% for Iguaçu Falls. The new Perfect Design Data center (PDD) index prioritizes efficiency in increasing order is an easy index to interpret. It is a redefinition of EUED, given by a linear equation, which provides an approximate result and uses a classification table. It is a decision support index for the location of a Data Center in the project phase.

Carbon-Aware Electricity Cost Minimization for Sustainable Data Centers

2017 ◽  
Vol 2 (2) ◽  
pp. 211-223 ◽  
Author(s):  
Hui Dou ◽  
Yong Qi ◽  
Wei Wei ◽  
Houbing Song
Keyword(s):  
Data Centers ◽  
Cost Minimization ◽  
Electricity Cost

Utilizing green energy prediction to schedule mixed batch and service jobs in data centers

2012 ◽  
Vol 45 (3) ◽  
pp. 53-57 ◽  
Author(s):  
Baris Aksanli ◽  
Jagannathan Venkatesh ◽  
Liuyi Zhang ◽  
Tajana Rosing
Keyword(s):  
Data Centers ◽  
Green Energy ◽  
Energy Prediction ◽  
Service Jobs ◽  
Mixed Batch

Effective Thermal Management of Data Centers Using Efficient Cabinet Designs

2009 ◽  
Author(s):  
Veerendra Mulay ◽  
Dereje Agonafer ◽  
Gary Irwin ◽  
Darshan Patell
Keyword(s):  
Thermal Management ◽  
Environmental Protection Agency ◽  
Data Center ◽  
Energy Use ◽  
Data Centers ◽  
Energy Usage ◽  
Protection Agency ◽  
Cold Air ◽  
New Concepts ◽  
Entire Nation

Rising heat load trends in data center facilities have raised concerns over energy usage. The environmental protection agency has reported that the energy used in 2006 by data center industry was 1.5% of the total energy usage by entire nation. The experts agree that by year 2010, this usage will approach 2% of the annual energy use nationwide. Although many new concepts such as airside economizers and cogeneration are gaining traction, many data center facilities spend considerable energy in cooling. In this study, various cabinet designs are discussed. Isolating the supplied cold air from hot exhaust air is always a challenge in thermal management of data center facilities. A cabinet design that employs chimney to aid the isolation of hot and cold air is discussed. A computational model of representative data center is created to study the effectiveness of design under various supply air fractions.

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