Strategies for improving the sustainability of data centers via energy mix, energy conservation, and circular energy

Information and communication technologies (ICT) are increasingly permeating our daily life and we ever more commit our data to the cloud. Events like the COVID-19 pandemic put an exceptional burden upon ICT. This involves increasing implementation and use of data centers, which increased energy use and environmental impact. The scope of this work is to summarize the present situation on data centers as to environmental impact and opportunities for improvement. First, we introduce the topic, presenting estimated energy use and emissions. Then, we review proposed strategies for energy efficiency and conservation in data centers. Energy uses pertain to power distribution, ICT, and non-ICT equipment (e.g., cooling). Existing and prospected strategies and initiatives in these sectors are identified. Among key elements are innovative cooling techniques, natural resources, automation, low-power electronics, and equipment with extended thermal limits. Research perspectives are identified and estimates of improvement opportunities are mentioned. Finally, we present an overview on existing metrics, regulatory framework, and bodies concerned

Thermal Energy Storage Optimization in Shopping Center Buildings

In this research, cooling system optimization using thermal energy storage (TES) in shopping center buildings was investigated. Cooling systems in commercial buildings account for up to 50% of their total energy consumption. This incurs high electricity costs related to the tariffs determined by the Indonesian government with the price during peak hours up to twice higher than during off-peak hours. Considering the problem, shifting the use of electrical load away from peak hours is desirable. This may be achieved by using a cooling system with TES. In a TES system, a chiller produces cold water to provide the required cooling load and saves it to a storage tank. Heat loss in the storage tank has to be considered because greater heat loss requires additional chiller capacity and investment costs. Optimization of the cooling system was done by minimizing the combination of chiller capacity, cooling load and heat loss using simplex linear programming. The results showed that up to 20% electricity cost savings can be achieved for a standalone shopping center building

UC Berkeley's Cory Hall: Evaluation of Challenges and Potential Applications of Building-to-Grid Implementation

From September 2009 through June 2010, a team of researchers developed, installed, and tested instrumentation on the energy flows in Cory Hall on the UC Berkeley campus to create a Building-to-Grid testbed. The UC Berkeley team was headed by Professor David Culler, and assisted by members from EnerNex, Lawrence Berkeley National Laboratory, California State University Sacramento, and the California Institute for Energy & Environment. While the Berkeley team mapped the load tree of the building, EnerNex researched types of meters, submeters, monitors, and sensors to be used (Task 1). Next the UC Berkeley team analyzed building needs and designed the network of metering components and data storage/visualization software (Task 2). After meeting with vendors in January, the UCB team procured and installed the components starting in late March (Task 3). Next, the UCB team tested and demonstrated the system (Task 4). Meanwhile, the CSUS team documented the methodology and steps necessary to implement a testbed (Task 5) and Harold Galicer developed a roadmap for the CSUS Smart Grid Center with results from the testbed (Task 5a) and evaluated the Cory Hall implementation process (Task 5b). The CSUS team also worked with local utilities to develop an approach to the energy information communication link between buildings and the utility (Task 6). The UC Berkeley team then prepared a roadmap to outline necessary technology development for Building-to-Grid, and presented the results of the project in early July (Task 7). Finally, CIEE evaluated the implementation, noting challenges and potential applications of Building-to-Grid (Task 8). These deliverables are available at the i4Energy site: http://i4energy.org/

A Data-Driven Approach for Enhancing the Efficiency in Chiller Plants: A Hospital Case Study

This article belongs to the Special Issue Energy Performance and Indoor Climate Analysis in Buildings)[EN] Large buildings cause more than 20% of the global energy consumption in advanced countries. In buildings such as hospitals, cooling loads represent an important percentage of the overall energy demand (up to 44%) due to the intensive use of heating, ventilation and air conditioning (HVAC) systems among other key factors, so their study should be considered. In this paper, we propose a data-driven analysis for improving the efficiency in multiple-chiller plants. Coefficient of performance (COP) is used as energy efficiency indicator. Data analysis, based on aggregation operations, filtering and data projection, allows us to obtain knowledge from chillers and the whole plant, in order to define and tune management rules. The plant manager software (PMS) that implements those rules establishes when a chiller should be staged up/down and which chiller should be started/stopped according different efficiency criteria. This approach has been applied on the chiller plant at the Hospital of León.SIThis research was funded by the Spanish Ministerio de Ciencia e Innovación and the European FEDER under project CICYT DPI2015-69891-C2-1-R/2-R

Thermal Energy Storage Optimization in Shopping Center Buildings

In this research, cooling system optimization using thermal energy storage (TES) in shopping center buildings was investigated. Cooling systems in commercial buildings account for up to 50% of their total energy consumption. This incurs high electricity costs related to the tariffs determined by the Indonesian government with the price during peak hours up to twice higher than during off-peak hours. Considering the problem, shifting the use of electrical load away from peak hours is desirable. This may be achieved by using a cooling system with TES. In a TES system, a chiller produces cold water to provide the required cooling load and saves it to a storage tank. Heat loss in the storage tank has to be considered because greater heat loss requires additional chiller capacity and investment costs. Optimization of the cooling system was done by minimizing the combination of chiller capacity, cooling load and heat loss using simplex linear programming. The results showed that up to 20% electricity cost savings can be achieved for a standalone shopping center building

Data Driven Chiller Plant Energy Optimization with Domain Knowledge

Refrigeration and chiller optimization is an important and well studied topic in mechanical engineering, mostly taking advantage of physical models, designed on top of over-simplified assumptions, over the equipments. Conventional optimization techniques using physical models make decisions of online parameter tuning, based on very limited information of hardware specifications and external conditions, e.g., outdoor weather. In recent years, new generation of sensors is becoming essential part of new chiller plants, for the first time allowing the system administrators to continuously monitor the running status of all equipments in a timely and accurate way. The explosive growth of data flowing to databases, driven by the increasing analytical power by machine learning and data mining, unveils new possibilities of data-driven approaches for real-time chiller plant optimization. This paper presents our research and industrial experience on the adoption of data models and optimizations on chiller plant and discusses the lessons learnt from our practice on real world plants. Instead of employing complex machine learning models, we emphasize the incorporation of appropriate domain knowledge into data analysis tools, which turns out to be the key performance improver over state-of-the-art deep learning techniques by a significant margin. Our empirical evaluation on a real world chiller plant achieves savings by more than 7% on daily power consumption.Comment: CIKM2017. Proceedings of the 26th ACM International Conference on Information and Knowledge Management. 201