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Mousavi, M. & Alvarez, M. (2023). A contract-based trading of power flexibility between a variable renewable energy producer and an electricity retailer. Sustainable Energy, Grids and Networks, 34, Article ID 101067.
Open this publication in new window or tab >>A contract-based trading of power flexibility between a variable renewable energy producer and an electricity retailer
2023 (English)In: Sustainable Energy, Grids and Networks, ISSN 2352-4677, Vol. 34, article id 101067Article in journal (Refereed) Published
Abstract [en]

Variable renewable energy producers and electricity retailers encounter several uncertainties in their decision-making problems, such as intermittency of renewable energy sources, variability of consumption, and market price volatility. To cope with these uncertainties, this paper presents a new contract-based trading mechanism of power flexibility (FlexCon) between two parties, a variable renewable energy producer and an electricity retailer. The proposed mechanism is managed by a new entity, named FlexCon operator, to oversee the energy and financial trades through the contract and coordinate the transactions with the system operator. Through the FlexCon, the parties are able to exchange their energy imbalances as a source of power flexibility to alleviate the negative impacts of uncertainties in their decision-making problems. To this end, two two-stage stochastic linear problems are introduced from each party’s point of view. In the first stage, the variable renewable energy producer and the electricity retailer submit their bids to sell and purchase in the day-ahead market, respectively. Following the day-ahead market clearing, closer to the delivery time, the parties submit their decisions on the contract to the introduced FlexCon operator. The operator allocates possible power flexibility transactions based on the surpluses or shortages of the parties. Assuming that the imbalances are not completely resolved with the FlexCon, the remaining deviations are settled in the balancing market. The parties’ decisions related to the balancing market and the FlexCon are modeled in the second stage of the stochastic problem. The uncertainties associated with prices, renewable generation, electricity consumption, and the maximum exchangeable power flexibility through the FlexCon are considered via scenarios. Meanwhile, the profit risk is considered by the Conditional Value at Risk measure. The numerical results show that FlexCon effectively diminishes the impacts of uncertainties on the parties’ profit.

Place, publisher, year, edition, pages
Elsevier, 2023
Keywords
Contract-based trading, Electricity retailer, Power flexibility, Stochastic programming, Variable renewable energy producer
National Category
Energy Systems
Research subject
Electric Power Engineering
Identifiers
urn:nbn:se:ltu:diva-97402 (URN)10.1016/j.segan.2023.101067 (DOI)001042984300001 ()2-s2.0-85160021749 (Scopus ID)
Note

Validerad;2023;Nivå 2;2023-06-30 (joosat);

Licens fulltext: CC BY License

Available from: 2023-05-24 Created: 2023-05-24 Last updated: 2024-03-07Bibliographically approved
Mousavi, M., Alvarez, M. & Zhong, J. (2023). A review on local flexibility market advancements: practices in Nordic countries. In: 27th International Conference on Electricity Distribution (CIRED 2023): . Paper presented at 27th International Conference and Exhibition on Electricity Distribution (CIRED 2023), Rome, Italy, June 12-15, 2023 (pp. 3816-3820). Institution of Engineering and Technology, Article ID 1394.
Open this publication in new window or tab >>A review on local flexibility market advancements: practices in Nordic countries
2023 (English)In: 27th International Conference on Electricity Distribution (CIRED 2023), Institution of Engineering and Technology, 2023, p. 3816-3820, article id 1394Conference paper, Published paper (Refereed)
Abstract [en]

This paper surveys the most recent local flexibility markets (LFMs) initiatives in three Nordic countries: Finland, Norway, and Sweden. First, the significant distinctions in flexibility needs in the region are identified and analyzed. Then, considering the recently practiced LFMs in these countries, a review of their aims, description, and implementation is performed. Moreover, their key findings and future research directions are discussed. The LFM platforms evaluated in this review are EU-SysFlex, INTERRFACE, NODES, DRES2Market, CoordiNet, SthlmFlex, and InterFlex. The analyses assert that the new LFM models express a promising technical and economic vision for increasing flexibility from the costumers' and aggregators' side by delivering grid and system services for both transmission system operators (TSOs) and distribution system operators (DSOs) in a coordinated context.

Place, publisher, year, edition, pages
Institution of Engineering and Technology, 2023
National Category
Energy Systems
Research subject
Electric Power Engineering
Identifiers
urn:nbn:se:ltu:diva-101582 (URN)10.1049/icp.2023.0566 (DOI)2-s2.0-85181539868 (Scopus ID)
Conference
27th International Conference and Exhibition on Electricity Distribution (CIRED 2023), Rome, Italy, June 12-15, 2023
Note

ISBN for host publication: 978-1-83953-855-1 (electronic)

Available from: 2023-10-05 Created: 2023-10-05 Last updated: 2024-04-23Bibliographically approved
Uddin Ahmed, K. M., Bollen, M. H. J. & Alvarez, M. (2023). A Stochastic Approach to Determine the Optimal Number of Servers for Reliable and Energy Efficient Operation of Data Centers. IEEE Transactions on Sustainable Computing, 8(2), 153-164
Open this publication in new window or tab >>A Stochastic Approach to Determine the Optimal Number of Servers for Reliable and Energy Efficient Operation of Data Centers
2023 (English)In: IEEE Transactions on Sustainable Computing, E-ISSN 2377-3782, Vol. 8, no 2, p. 153-164Article in journal (Refereed) Published
Abstract [en]

The increasing demand of the data center's computational capacity in recent years has introduced new data center operational challenges among others to maintain the service level agreements (SLA) and quality of services (QoS), while at the same time limiting energy consumption. In this paper, a stochastic operational risk assessment approach is presented that estimates the required number of spare servers in a data center considering the risk of servers' failure in operation since servers define the computational capability of a data center. A reliability index called “risk of computational resource commitment (RCRC)” is introduced that quantifies the probability of having insufficient spare servers due to failures during the operational lead time, and the complement of the RCRC shows the ability of the resources to maintain SLA of a data center. The failure rates of the servers are obtained using a Monte Carlo Simulation with the failure data, published by Google in 2019. The analysis shows that the RCRC reduces with the increasing number of spare servers, while it also stresses the energy efficiency of the data center. The RCRC index could be used in data center operation to avoid overprovisioning of the servers and to limit the number of spare servers in the data center, while creating a suitable balance between QoS and energy consumption of the data centers.

Place, publisher, year, edition, pages
IEEE, 2023
Keywords
data center operation, Monte Carlo simulation, risk assessment, stochastic modeling, server failure
National Category
Other Civil Engineering Energy Systems
Research subject
Electric Power Engineering
Identifiers
urn:nbn:se:ltu:diva-94241 (URN)10.1109/tsusc.2022.3216350 (DOI)001005680900001 ()2-s2.0-85163183639 (Scopus ID)
Funder
Swedish Energy Agency, 43090-2Norrbotten County Council
Note

Validerad;2023;Nivå 2;2023-07-12 (sofila);

Funder: Cloudberry Datacenters project

Available from: 2022-11-23 Created: 2022-11-23 Last updated: 2023-09-05Bibliographically approved
Avila-Rojas, A. E., De Oliveira-De Jesus, P. M. & Alvarez, M. (2022). Distribution network electric vehicle hosting capacity enhancement using an optimal power flow formulation. Electrical engineering (Berlin. Print), 104(3), 1337-1348
Open this publication in new window or tab >>Distribution network electric vehicle hosting capacity enhancement using an optimal power flow formulation
2022 (English)In: Electrical engineering (Berlin. Print), ISSN 0948-7921, E-ISSN 1432-0487, Vol. 104, no 3, p. 1337-1348Article in journal (Refereed) Published
Abstract [en]

This paper presents a method based on an optimal power flow (OPF) procedure to determine the maximum Hosting Capacity (HC) of Electric Vehicles (EV) that can be supported by a distribution network. With a focus on the injection control of reactive power, it is possible to maximize the penetration of EV. The presented method is based on linearized power flow equations, allowing a significant reduction in the computational processing times. Two comparisons are presented. The first one is between a nonlinear and a linear OPF method. Second one, it is comparative analysis between legacy iterative (non-optimized) method of HC and the proposed method. The method is applied on the IEEE 13 node test feeder circuit showing its effectiveness and acceptable performance. Results demonstrate that the implemented method enhances the HC measured against a legacy HC method and decrease the computational time measures against nonlinear optimization methods. 

Place, publisher, year, edition, pages
Springer, 2022
Keywords
Hosting capacity, Electric vehicle integration, Radial distribution network, Optimal power flow, Linear power flow, Overvoltage, Undervoltage
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Electric Power Engineering
Identifiers
urn:nbn:se:ltu:diva-87203 (URN)10.1007/s00202-021-01374-7 (DOI)000696487400001 ()2-s2.0-85115055914 (Scopus ID)
Note

Validerad;2022;Nivå 2;2022-05-31 (johcin)

Available from: 2021-09-24 Created: 2021-09-24 Last updated: 2023-09-05Bibliographically approved
Ahmed, K. M., Bollen, M. H. J., Alvarez, M. & Letha, S. S. (2022). The Impacts of Voltage Disturbances Due to Faults In the Power Supply System of A Data Center. In: 2022 20th International Conference on Harmonics & Quality of Power (ICHQP) Proceedings: “Power Quality in the Energy Transition”. Paper presented at 20th International Conference on Harmonics & Quality of Power (ICHQP 2022), Naples, Italy, May 29 - June 1, 2022. IEEE
Open this publication in new window or tab >>The Impacts of Voltage Disturbances Due to Faults In the Power Supply System of A Data Center
2022 (English)In: 2022 20th International Conference on Harmonics & Quality of Power (ICHQP) Proceedings: “Power Quality in the Energy Transition”, IEEE, 2022Conference paper, Published paper (Refereed)
Abstract [en]

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.

Place, publisher, year, edition, pages
IEEE, 2022
Series
International Conference on Harmonics and Quality of Power, ISSN 1540-6008, E-ISSN 2164-0610
Keywords
data center reliability, power supply unit, server outages, UPS current limitation, voltage dips
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering Control Engineering
Research subject
Electric Power Engineering
Identifiers
urn:nbn:se:ltu:diva-92109 (URN)10.1109/ICHQP53011.2022.9808804 (DOI)000844604500111 ()2-s2.0-85133750124 (Scopus ID)
Conference
20th International Conference on Harmonics & Quality of Power (ICHQP 2022), Naples, Italy, May 29 - June 1, 2022
Funder
Swedish Energy Agency, 43090-2Norrbotten County Council
Note

ISBN för värdpublikation: 978-1-6654-1639-9

Available from: 2022-07-07 Created: 2022-07-07 Last updated: 2023-09-05Bibliographically approved
Bakhtiari, H., Zhong, J. & Alvarez, M. (2022). Uncertainty modeling methods for risk-averse planning and operation of stand-alone renewable energy-based microgrids. Renewable energy, 199, 866-880
Open this publication in new window or tab >>Uncertainty modeling methods for risk-averse planning and operation of stand-alone renewable energy-based microgrids
2022 (English)In: Renewable energy, ISSN 0960-1481, E-ISSN 1879-0682, Vol. 199, p. 866-880Article in journal (Refereed) Published
Abstract [en]

The accuracy of models to capture the uncertainty of renewables significantly affects the planning and operation of renewable energy-based stand-alone (REB-SA) microgrids. This paper aims to first study different stochastic and deterministic models for renewables, then evaluate the performance of an REB-SA microgrid planning problem and provide qualitative and quantitative comparisons. A modified Metropolis-coupled Markov chain Monte Carlo simulation is considered for the first time in the planning of an REB-SA microgrid to predict the behavior of renewables with minimum iterations. The modified model is benchmarked against two prevalent models including the retrospective model with worst-case scenarios and the Monte Carlo simulation. The operations of three designed microgrids (by these three methods) are evaluated using the last three-year historical data of a city in northern Sweden including solar radiation, wind speed, the water flow of a river, and load consumption. The impacts of the considered methods on using PV panels and hydrogen systems are investigated. The results verify that the modified model decreases the risk of planning and operation of an REB-SA microgrid from the energy and power shortage viewpoints. Moreover, the designed microgrid with the modified model can cope with all possible scenarios from economic, technical, and environmental viewpoints.

Place, publisher, year, edition, pages
Elsevier, 2022
Keywords
Stochastic planning, Renewable energy-based microgrids, Uncertainty modeling, Metropolis-coupled Markov chain Monte Carlo, Data classification method
National Category
Probability Theory and Statistics Other Mechanical Engineering
Research subject
Electric Power Engineering
Identifiers
urn:nbn:se:ltu:diva-93047 (URN)10.1016/j.renene.2022.09.040 (DOI)000888849300002 ()2-s2.0-85138595384 (Scopus ID)
Note

Validerad;2022;Nivå 2;2022-11-29 (joosat);

Available from: 2022-09-15 Created: 2022-09-15 Last updated: 2024-04-23Bibliographically approved
Ahmed, K. M., Alvarez, M. & Bollen, M. H. J. (2021). A Novel Reliability Index to Assess the Computational Resource Adequacy in Data Centers. IEEE Access, 9, 54530-54541
Open this publication in new window or tab >>A Novel Reliability Index to Assess the Computational Resource Adequacy in Data Centers
2021 (English)In: IEEE Access, E-ISSN 2169-3536, Vol. 9, p. 54530-54541Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
NY: IEEE, 2021
Keywords
adequacy, data center, energy losses, internal power supply system, reliability
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Electric Power Engineering
Identifiers
urn:nbn:se:ltu:diva-83504 (URN)10.1109/ACCESS.2021.3070915 (DOI)000641002300001 ()2-s2.0-85103881668 (Scopus ID)
Funder
Swedish Energy Agency, 43090-2
Note

Validerad;2021;Nivå 2;2021-04-15 (alebob)

Available from: 2021-04-07 Created: 2021-04-07 Last updated: 2023-09-05Bibliographically approved
Ahmed, K. M., Bollen, M. H. . & Alvarez, M. (2021). A Review of Data Centers Energy Consumption And Reliability Modeling. IEEE Access, 9, Article ID 152536.
Open this publication in new window or tab >>A Review of Data Centers Energy Consumption And Reliability Modeling
2021 (English)In: IEEE Access, E-ISSN 2169-3536, Vol. 9, article id 152536Article, review/survey (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
IEEE, 2021
Keywords
data center, data center design, planning and operation, energy consumption modeling, data center reliability, reliability modeling
National Category
Energy Engineering
Research subject
Electric Power Engineering
Identifiers
urn:nbn:se:ltu:diva-87757 (URN)10.1109/access.2021.3125092 (DOI)000720508900001 ()2-s2.0-85118672485 (Scopus ID)
Funder
Swedish Energy Agency, 43090-2
Note

Validerad;2021;Nivå 2;2021-11-29 (johcin)

Available from: 2021-11-04 Created: 2021-11-04 Last updated: 2023-09-05Bibliographically approved
Bakhtiari, H., Zhong, J. & Alvarez, M. (2021). Predicting the stochastic behavior of uncertainty sources in planning a stand-alone renewable energy-based microgrid using Metropolis–coupled Markov chain Monte Carlo simulation. Applied Energy, 290, Article ID 116719.
Open this publication in new window or tab >>Predicting the stochastic behavior of uncertainty sources in planning a stand-alone renewable energy-based microgrid using Metropolis–coupled Markov chain Monte Carlo simulation
2021 (English)In: Applied Energy, ISSN 0306-2619, E-ISSN 1872-9118, Vol. 290, article id 116719Article in journal (Refereed) Published
Abstract [en]

Due to the lack of available flexibility sources to cope with different uncertainties in the real-time operation of stand-alone renewable energy-based microgrids, the stochastic behavior of uncertainty sources needs to be included in the planning stage. Since there is a high association between some of the uncertainty sources, defining a proper time series to represent the behavior of each source of uncertainty is a challenging issue. Consequently, uncertainty sources should be modeled in such a way that the designed microgrid be able to cope with all scenarios from probability and impact viewpoints. This paper proposes a modified Metropolis–coupled Markov chain Monte Carlo (MC)3 simulation to predict the stochastic behavior of different uncertainty sources in the planning of a stand-alone renewable energy-based microgrid. Solar radiation, wind speed, the water flow of a river, load consumption, and electricity price have been considered as primary sources of uncertainty. A novel data classification method is introduced within the (MC)3 simulation to model the time-dependency and the association between different uncertainty sources. Moreover, a novel curve-fitting approach is proposed to improve the accuracy of representing the multimodal distribution functions, modeling the Markov chain states, and the long-term probability of uncertainty sources. The predicted representative time series with the proposed modified (MC)3 model is benchmarked against the retrospective model, the long-term historical data, and the simple Monte Carlo simulation model to capture the stochastic behavior of uncertainty sources. The results show that the proposed model represents the probability distribution function of each source of uncertainty, the continuity of samples, time dependency, the association between different uncertainty sources, short-term and long-term trends, and the seasonality of uncertainty sources. Finally, results confirm that the proposed modified (MC)3 can appropriately predict all scenarios with high probability and impact.

Place, publisher, year, edition, pages
Elsevier, 2021
Keywords
Uncertainty modeling, Metropolis–coupled Markov chain Monte Carlo simulation, Data classification method, Curve-fitting approach
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Electric Power Engineering
Identifiers
urn:nbn:se:ltu:diva-83263 (URN)10.1016/j.apenergy.2021.116719 (DOI)000639137400005 ()2-s2.0-85102060004 (Scopus ID)
Note

Validerad;2021;Nivå 2;2021-03-15 (alebob)

Available from: 2021-03-15 Created: 2021-03-15 Last updated: 2024-04-23Bibliographically approved
Ahmed, K. M., Alvarez, M. & Bollen, M. H. .. (2021). Reliability Analysis of Internal Power Supply Architecture of Data Centers in Terms of Power Losses. Electric power systems research, 193, Article ID 107025.
Open this publication in new window or tab >>Reliability Analysis of Internal Power Supply Architecture of Data Centers in Terms of Power Losses
2021 (English)In: Electric power systems research, ISSN 0378-7796, E-ISSN 1873-2046, Vol. 193, article id 107025Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
Elsevier, 2021
Keywords
availability, data center, internal power supply system, power losses, reliability
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Electric Power Engineering
Identifiers
urn:nbn:se:ltu:diva-82716 (URN)10.1016/j.epsr.2021.107025 (DOI)000632342800006 ()2-s2.0-85099786563 (Scopus ID)
Funder
Swedish Energy Agency, 43090-2Norrbotten County Council
Note

Validerad;2021;Nivå 2;2021-01-29 (alebob)

Available from: 2021-01-29 Created: 2021-01-29 Last updated: 2023-09-05Bibliographically approved
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ORCID iD: ORCID iD iconorcid.org/0000-0003-4443-7653

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