| 1. |
- Ehnberg, Jimmy, 1976, et al.
(författare)
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Reliability of a small power system using solar power and hydro
- 2005
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Ingår i: Electric Power Systems Research. - : Elsevier BV. - 0378-7796 .- 1873-2046. ; 74:1, s. 119-127
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Tidskriftsartikel (refereegranskat)abstract
- This paper studies the availability of the electricity supply when the sources consist of a combination of solar energy and a small hydro installation. Instead of flow-of-river, a small reservoir is used. By not using the hydro energy during sunny periods, the natural flow-of-river fills up the reservoir for later use. A model for global solar radiation is proposed with an astronomical part (deterministic) and a meteorological part (stochastic). The meteorological part is based on a Markov model of the cloud coverage. The solar model does not require solar radiation measurements, just cloud observations. A case study has been performed for Timbuktu (16.75degreesN, 0.07degreesW) in which generation availability is simulated for four different cases: solar power only; solar power with storage; solar and hydro power and solar and hydro, power with storage. To be able to use exclusively renewable energy sources, a combination of sources is needed to secure the reliability of the supply. Using solar cells in combination with a small reservoir is favorable. Even with a weak flow the affect of the flow on the day time reliability is minor, but great benefits can be found for reliability during low load hours (night time).
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| 2. |
- Ehnberg, Jimmy, 1976, et al.
(författare)
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Simulation of global solar radiation based on cloud observations
- 2005
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Ingår i: Solar Energy. - : Elsevier BV. - 0038-092X .- 1471-1257. ; 78:1, s. 157-162
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Tidskriftsartikel (refereegranskat)abstract
- A stochastic model for simulating global solar radiation on a horizontal surface has been developed for use in power systems reliability calculations. The importance of an appropriate model for global solar radiation has increased with the increased use of photovoltaic power generation. The global solar radiation shows not only regular yearly and daily variations but also a random behaviour. The yearly and daily variations can be described in a deterministic way while the random behaviour has a high correlation with the state of the atmosphere. The astronomic effects can easily be described mathematical with only some minor simplifications but the atmospheric effects are more complicated to describe. The transmittivity of solar radiation in the atmosphere depends on various factors, e.g. humidity, air pressure and cloud type. By using cloud observations as input for the simulations, the local meteorological conditions can be accounted for. The model is usable for any geographical location if cloud observations are available at the location or at locations with similar climatological conditions. This is especially useful for development countries where long-term solar radiation measurement can be hard to obtain. Cloud observations can be performed without any expensive equipment and have been a standard parameter for many years throughout the world. Standard observations are done according to the Oktas-scale. It is the interval between observations that sets the resolution of the simulation: the observations are normally only every hour or every third hour. The model can easily be combined with cloud coverage simulations, has been proposed, for a more general model. For some calculations higher resolution may be needed. This can be obtained by including a stochastic model for the short-term variations and simple model has been proposed. Errors and limitations of the model are estimated and discussed.
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| 3. |
- Ahmed, Kazi Main Uddin, 1989-, et al.
(författare)
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A Novel Reliability Index to Assess the Computational Resource Adequacy in Data Centers
- 2021
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Ingår i: IEEE Access. - NY : IEEE. - 2169-3536. ; 9, s. 54530-54541
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Tidskriftsartikel (refereegranskat)abstract
- The energy demand of data centers is increasing globally with the increasing demand for computational resources to ensure the quality of services. It is important to quantify the required resources to comply with the computational workloads at the rack-level. In this paper, a novel reliability index called loss of workload probability is presented to quantify the rack-level computational resource adequacy. The index defines the right-sizing of the rack-level computational resources that comply with the computational workloads, and the desired reliability level of the data center investor. The outage probability of the power supply units and the workload duration curve of servers are analyzed to define the loss of workload probability. The workload duration curve of the rack, hence, the power consumption of the servers is modeled as a function of server workloads. The server workloads are taken from a publicly available data set published by Google. The power consumption models of the major components of the internal power supply system are also presented which shows the power loss of the power distribution unit is the highest compared to the other components in the internal power supply system. The proposed reliability index and the power loss analysis could be used for rack-level computational resources expansion planning and ensures energy-efficient operation of the data center.
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| 4. |
- Ahmed, Kazi Main Uddin, 1989-, et al.
(författare)
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A Review of Data Centers Energy Consumption And Reliability Modeling
- 2021
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Ingår i: IEEE Access. - : IEEE. - 2169-3536. ; 9
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Forskningsöversikt (refereegranskat)abstract
- Enhancing the efficiency and the reliability of the data center are the technical challenges for maintaining the quality of services for the end-users in the data center operation. The energy consumption models of the data center components are pivotal for ensuring the optimal design of the internal facilities and limiting the energy consumption of the data center. The reliability modeling of the data center is also important since the end-user’s satisfaction depends on the availability of the data center services. In this review, the state-of-the-art and the research gaps of data center energy consumption and reliability modeling are identified, which could be beneficial for future research on data center design, planning, and operation. The energy consumption models of the data center components in major load sections i.e., information technology (IT), internal power conditioning system (IPCS), and cooling load section are systematically reviewed and classified, which reveals the advantages and disadvantages of the models for different applications. Based on this analysis and related findings it is concluded that the availability of the model parameters and variables are more important than the accuracy, and the energy consumption models are often necessary for data center reliability studies. Additionally, the lack of research on the IPCS consumption modeling is identified, while the IPCS power losses could cause reliability issues and should be considered with importance for designing the data center. The absence of a review on data center reliability analysis is identified that leads this paper to review the data center reliability assessment aspects, which is needed for ensuring the adaptation of new technologies and equipment in the data center. The state-of-the-art of the reliability indices, reliability models, and methodologies are systematically reviewed in this paper for the first time, where the methodologies are divided into two groups i.e., analytical and simulation-based approaches. There is a lack of research on the data center cooling section reliability analysis and the data center components’ failure data, which are identified as research gaps. In addition, the dependency of different load sections for reliability analysis of the data center is also included that shows the service reliability of the data center is impacted by the IPCS and the cooling section.
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| 5. |
- Ahmed, Kazi Main Uddin, 1989-, et al.
(författare)
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Characterizing Failure and Repair Time of Servers in a Hyper-scale Data Center
- 2020
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Ingår i: Proceedings of 2020 IEEE PES Innovative Smart Grid Technologies Europe (ISGT-Europe) 26-28 October, 2020. - : IEEE. ; , s. 660-664
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Konferensbidrag (refereegranskat)abstract
- Hyper-scale data centers are used to host cloud computing interfaces to support the increasing demand for storage and computational resources. For achieving specific service level agreements (SLA), this infrastructure demands highly available cloud computing systems. It is necessary to analyze the server failure incidents to determine the way of improving the reliability of the system since the computational interruption causes financial losses for the data center owners. Regarding the reliability analysis, it is important to characterize the time to failure and time to repair of the servers. In this paper, a publicly available data set from Google cloud-cluster data center will be analyzed to find the distribution function for the time to failure and the time to repair for the servers in a cloud based data centers.
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| 6. |
- Ahmed, Kazi Main Uddin, 1989-, et al.
(författare)
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Reliability Analysis of Internal Power Supply Architecture of Data Centers in Terms of Power Losses
- 2021
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Ingår i: Electric power systems research. - : Elsevier. - 0378-7796 .- 1873-2046. ; 193
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Tidskriftsartikel (refereegranskat)abstract
- The number of data centers and the energy demand are increasing globally with the development of information and communication technology (ICT). The data center operators are facing challenges to limit the internal power losses and the unexpected outages of the computational resources or servers. The power losses of the internal power supply system (IPSS) increase with the increasing number of servers that causes power supply capacity shortage for the devices in IPSS. The aim of this paper is to address the outage probability of the computational resources or servers due to the power supply capacity shortage of the power distribution units (PDUs) in the IPSS. The servers outage probability at rack-level defines the service availability of the data center since the servers are the main computational resource of it. The overall availability of the IPSS and the power consumption models of the IPSS devices are also presented in this paper. Quantitative studies are performed to show the impacts of the power losses on the service availability and the overall availability of the IPSS for two different IPSS architectures, which are equivalent to the Tier I and Tier IV models of the data center.
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| 7. |
- Ahmed, Kazi Main Uddin, 1989-, et al.
(författare)
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The Impacts of Voltage Disturbances Due to Faults In the Power Supply System of A Data Center
- 2022
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Ingår i: 2022 20th International Conference on Harmonics & Quality of Power (ICHQP) Proceedings. - : IEEE.
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Konferensbidrag (refereegranskat)abstract
- The internal power condition system (IPCS) in data centers is prone to have cable faults that cause voltage dips and swells. The voltage dips and swells impact the power supply units (PSUs) with the servers. The servers connected with the PUSs restart or turn-off when the input voltage comes out of the voltage-tolerance range. This paper analyses the impact of such voltage disturbances on server outages due to a single-phase fault in the IPCS. The voltage-tolerance range of the PSUs is considered according to the guideline of the Information Technology Industry Council (ITIC). The voltage dip propagates to the healthy load sections from the fault location, while voltage swells are also observed due to sudden load reduction. Moreover, the current limitation mode of the inverter in the uninterrupted power supply (UPS) is identified as a cause of voltage dip to almost zero experienced by the PSUs. The reliability of the data center considering the outage probability of the servers are finally quantified to show the impacts of the voltage dips and swells in the IPCS.
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| 8. |
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| 9. |
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| 10. |
- Axelberg, Peter G.V. 1959, et al.
(författare)
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AUTOMATIC CLASSIFICATION OF VOLTAGE EVENTS USING THE SUPPORT VECTOR MACHINE METHOD
- 2007
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Ingår i: 19th International Conference on Electricity Distribution (SIRED 2007) , Vienna, Austria, 21-24 May, 2007.
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Konferensbidrag (refereegranskat)abstract
- Statistically based classification systems need to be trained on a large number of training data in order to classify unseen data accurately. However, it is difficult to gather enough voltage events for the training purpose from real recordings. Therefore, a classification system trained to accurately classify real voltage events, but based on synthetic training data is highly in demand. This paper therefore proposes the design of a statistically based classification system trained on synthetic data. The paper gives also the results of conducted performance tests when the proposed classification system was trained to classify seven common types of voltage events. The experiments showed an overall detection rate of 81.6%, 91.9% and 99.5% respectively.
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