Toward sustainable data centers: a comprehensive energy management strategy

Data centers are major contributors to the emission of carbon dioxide to the atmosphere, and this contribution is expected to increase in the following years. This has encouraged the development of techniques to reduce the energy consumption and the environmental footprint of data centers. Whereas some of these techniques have succeeded to reduce the energy consumption of the hardware equipment of data centers (including IT, cooling, and power supply systems), we claim that sustainable data centers will be only possible if the problem is faced by means of a holistic approach that includes not only the aforementioned techniques but also intelligent and unifying solutions that enable a synergistic and energy-aware management of data centers. In this paper, we propose a comprehensive strategy to reduce the carbon footprint of data centers that uses the energy as a driver of their management procedures. In addition, we present a holistic management architecture for sustainable data centers that implements the aforementioned strategy, and we propose design guidelines to accomplish each step of the proposed strategy, referring to related achievements and enumerating the main challenges that must be still solved.Peer ReviewedPostprint (author's final draft

Carbon-profit-aware job scheduling and load balancing in geographically distributed cloud for HPC and web applications

This thesis introduces two carbon-profit-aware control mechanisms that can be used to improve performance of job scheduling and load balancing in an interconnected system of geographically distributed data centers for HPC and web applications. These control mechanisms consist of three primary components that perform: 1) measurement and modeling, 2) job planning, and 3) plan execution. The measurement and modeling component provide information on energy consumption and carbon footprint as well as utilization, weather, and pricing information. The job planning component uses this information to suggest the best arrangement of applications as a possible configuration to the plan execution component to perform it on the system. For reporting and decision making purposes, some metrics need to be modeled based on directly measured inputs. There are two challenges in accurately modeling of these necessary metrics: 1) feature selection and 2) curve fitting (regression). First, to improve the accuracy of power consumption models of the underutilized servers, advanced fitting methodologies were used on the selected server features. The resulting model is then evaluated on real servers and is used as part of load balancing mechanism for web applications. We also provide an inclusive model for cooling system in data centers to optimize the power consumption of cooling system, which in turn is used by the planning component. Furthermore, we introduce another model to calculate the profit of the system based on the price of electricity, carbon tax, operational costs, sales tax, and corporation taxes. This model is used for optimized scheduling of HPC jobs. For position allocation of web applications, a new heuristic algorithm is introduced for load balancing of virtual machines in a geographically distributed system in order to improve its carbon awareness. This new heuristic algorithm is based on genetic algorithm and is specifically tailored for optimization problems of interconnected system of distributed data centers. A simple version of this heuristic algorithm has been implemented in the GSN project, as a carbon-aware controller. Similarly, for scheduling of HPC jobs on servers, two new metrics are introduced: 1) profitper-core-hour-GHz and 2) virtual carbon tax. In the HPC job scheduler, these new metrics are used to maximize profit and minimize the carbon footprint of the system, respectively. Once the application execution plan is determined, plan execution component will attempt to implement it on the system. Plan execution component immediately uses the hypervisors on physical servers to create, remove, and migrate virtual machines. It also executes and controls the HPC jobs or web applications on the virtual machines. For validating systems designed using the proposed modeling and planning components, a simulation platform using real system data was developed, and new methodologies were compared with the state-of-the-art methods considering various scenarios. The experimental results show improvement in power modeling of servers, significant carbon reduction in load balancing of web applications, and significant profit-carbon improvement in HPC job scheduling

Feasibility Study of Economics and Performance of Solar Photovoltaics at the TechCity East Campus Resource Conservation and Recovery Act Site in Kingston, New York. A Study Prepared in Partnership with the Environmental Protection Agency for the RE-Powering America's Land Initiative: Siting Renewable Energy on Potentially Contaminated Land and Mine Sites

The U.S. Environmental Protection Agency (EPA), in accordance with the RE-Powering America's Land initiative, selected the TechCity East Campus site in Kingston, New York, for a feasibility study of renewable energy production. The National Renewable Energy Laboratory (NREL) provided technical assistance for this project. The purpose of this study is to assess the site for a possible photovoltaic (PV) system installation and estimate the cost, performance, and site impacts of different PV options. In addition, the report recommends financing options that could assist in the implementation of a PV system at the site

Characteristics features, economical aspects and environmental impacts of gen-4 nuclear power for developing countries

The growing demand of energy has delicate the requirement of alternative sources of energies other than fossil fuels. Though renewable energy resources like solar, biomass, hydro and geothermal energy appear as environment friendly, replenishing sources of energy, a comprehensive solution appears far-fetched as far as large scale production and wide-spread dissemination is concerned when long term cost factors are taken into consideration. In this paper, discussions on the advanced fourth generation nuclear power on the basis of environmental contamination, energy security, cost of fossil fuels and electricity generation and have philosophy to the prospects of nuclear power as the ultimate future energy option for the developing countries are done. This study proposes that gen-4 nuclear appears to be a long term environment favorable panacea to the much discoursed problem of energy crisis by maintaining energy security and long term cost concern in developing countries as well as in the whole world. Keywords: Gen-4 nuclear, reactor, kinetics, neutron, delayed neutron, transient

Solar Decathlon Competition 2021

This report is intended to outline all relevant background information, decisions, and design direction for our senior project at California Polytechnic State University, San Luis Obispo. We will be designing net-zero, affordable housing to compete in the attached housing division of the 2021 Department of Energy Solar Decathlon. With the increased urgency of climate change and focus on sustainability in construction, the importance of designing a net-zero structure is very apparent. Because there is a great need for affordable and sustainable housing in Watts, CA, we will be tailoring our design to meet this community’s needs. Details of the Solar Decathlon competition, the need for sustainable, affordable housing, and the various mechanical systems such as, plumbing, HVAC, and power systems are detailed below in the body of the report. Additionally, the process of creating the initial concept design is outlined as well

Demand response model development for smart households using time of use tariffs and optimal control - the Isle of Wight energy autonomous community case study

Residential variable energy price schemes can be made more effective with the use of a demand response (DR) strategy along with smart appliances. Using DR, the electricity bill of participating customers/households can be minimised, while pursuing other aims such as demand-shifting and maximising consumption of locally generated renewable-electricity. In this article, a two-stage optimization method is used to implement a price-based implicit DR scheme. The model considers a range of novel smart devices/technologies/schemes, connected to smart-meters and a local DR-Controller. A case study with various decarbonisation scenarios is used to analyse the effects of deploying the proposed DR-scheme in households located in the west area of the Isle of Wight (Southern United Kingdom). There are approximately 15,000 households, of which 3000 are not connected to the gas-network. Using a distribution network model along with a load flow software-tool, the secondary voltages and apparent-power through transformers at the relevant substations are computed. The results show that in summer, participating households could export up to 6.4 MW of power, which is 10% of installed large-scale photovoltaics (PV) capacity on the island. Average carbon dioxide equivalent (CO2e) reductions of 7.1 ktons/annum and a reduction in combined energy/transport fuel-bills of 60%/annum could be achieved by participating households

Enhancing solar energy generation potential in the villages of Rovaniemi, Lapland

Abstract. This master’s thesis investigated the solar energy potential of future plots in three different village groups in Lapland using existing provisional master plans. The investigation was conducted as part of the SINNI project. The project explores the potential of virtual power plants in the villages of Lapland. The target area of this research was three village groups in the Rovaniemi region around Sinetta, Vikajärvi and Vanttauskoski. The village groups were selected because the buildings form relatively cohesive groups from the point of view of energy generation, and the proximity of the areas to power lines and main roads. The project aims to characterize “SINNI villages”, which are to be defined by indicators such as their energy production potential, as well as geographical features such as location, land use patterns, and suitability of building stock. The expectation is that when defining the economic feasibility of solar power generation in SINNI villages, these criteria could be used as a basis to assess the techno-economic feasibility of similar sites in the future. The solar energy potential was first assessed considering future buildings on the best oriented building plots in the master plans. The hypothetical range of 120–180° from the true north was selected for the analysis as potentially feasible orientations for solar energy generation. The estimated solar energy potential for the future plots in the three village groups, considering this range of azimuths were 1.07GWh/year for Sinetta, 0.57GWh/year for Vikajärvi and 1.04GWh/year for Vanttauskoski. Secondly, the solar energy potential of all building plots in the 3 village groups were calculated to observe the difference in output. It was found that the solar energy potential of all future plots in the three Village Groups were 1.20GWh/year, 0.71GWh/year,1.47GWh/year respectively. The small differences observed were due to the fact that the majority of the future buildings in the master plans were adjusted well enough to support solar energy generation. Due to the Northern location of the villages, the issue of snow on the panels were also investigated, to ascertain missed solar energy generation potential attributed to snow covering the panels. The results show that 28.3% of the solar energy generation in Spring could be lost due to snow, if effective mitigation strategies are not implemented. The profitability of the solar investments was also analysed using Finsolar Profitability Calculator, from the perspective of homeowners. The results of this research indicate that deploying rooftop solar panels makes economic sense, if the roofs are in the 120–210° azimuth range, as this would provide a relatively fair payback period in the range of 19–23 years. Azimuths out of this range typically result in significantly higher payback period. The use of self-generated energy was also assessed and the consumption profiles for the village groups were analysed in juxtaposition with the self-produced energy under the framework of energy communities. The results show that solar power investments could be economically profitable even in Lapland, if the houses and roofs are sited optimally. The research also indicates that the energy community concept which have been brought into limelight in recent EU directives could potentially enhance the profitability of solar investments by facilitating energy sharing within the community which maximises the value of solar energy produced. They also potentially enhance customer participation, energy security, independence, efficiency, and sustainability which could be regarded as some of the most crucial goals in the energy sector for EU Member States