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Publications (10 of 349) Show all publications
Herre, L., Matusevičius, T., Olauson, J. & Söder, L. (2019). Exploring Wind Power Prognosis Data on Nord Pool: The Case of Sweden and Denmark. IET Renewable Power Generation
Open this publication in new window or tab >>Exploring Wind Power Prognosis Data on Nord Pool: The Case of Sweden and Denmark
2019 (English)In: IET Renewable Power Generation, ISSN 1752-1416, E-ISSN 1752-1424, ISSN 1752-1416Article in journal (Refereed) Published
Abstract [en]

A good understanding of forecast errors is imperative for greater penetration of wind power, as it can facilitate planning and operation tasks. Oftentimes, public data is used for system studies without questioning or verifying its origin. In this paper, we propose a methodology to verify public data with the example of wind power prognosis published by Nord Pool. We focus on Swedish data and identify a significant bias that increases over the forecast horizon. In order to explore the origin of this bias, we first compare against Danish forecast and then describe the underlying structure behind the submission processes of this data. Based on the balance settlement structure, we reveal that Swedish "wind power prognoses" on Nord Pool are in fact rather wind production plans than technical forecasts. We conclude with the recommendation for improved communication and transparency with respect to terminology of public data on Nord Pool. We stress the importance for the research community to check publicly available input data before further use. Furthermore, the root-mean-square error and the spatio-temporal correlation between the errors in the bidding areas at different horizons is presented. Even with this compromised data, a stronger correlation is identified in neighbouring areas.

Keywords
wind power forecasts, forecast anaylsis, vindkraftspognoser, analys av vindkraftsprognoser
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering Energy Systems
Research subject
Electrical Engineering
Identifiers
urn:nbn:se:kth:diva-241639 (URN)10.1049/iet-rpg.2018.5086 (DOI)
Note

QC 20190124

Available from: 2019-01-24 Created: 2019-01-24 Last updated: 2019-02-19Bibliographically approved
Divshali, P. H. & Söder, L. (2019). Improving PV Dynamic Hosting Capacity Using Adaptive Controller for STATCOMs. IEEE transactions on energy conversion, 34(1), 415-425
Open this publication in new window or tab >>Improving PV Dynamic Hosting Capacity Using Adaptive Controller for STATCOMs
2019 (English)In: IEEE transactions on energy conversion, ISSN 0885-8969, E-ISSN 1558-0059, Vol. 34, no 1, p. 415-425Article in journal (Refereed) Published
Abstract [en]

High penetrations of renewable energy sources (RES) in distribution grids lead to new challenges in voltage regulation. These challenges are not just limited to the steady-state voltage rise, but they are extended to rapid voltage changes due to wind speed variations and moving clouds, casting shadows on photovoltaic panels. According to EN50160 in low-voltage (LV) grids, the steady-state voltage should not exceed 1.1 pu (static characteristic), and rapid voltage changes should be kept less than 0.05 pu (dynamic characteristic). These two characteristics may limit the maximum amount of RES that can be installed in LV grids, called, respectively, the static hosting capacity (SHC) and dynamic hosting capacity (DHC). Although existing research just evaluated SHC in distribution grids, high-penetrated RES grids can be faced with such large voltage changes, which cause a smaller DHC than the SHC. This paper studies both SHC and DHC in distribution grids and proposes an adaptive controller for static synchronous compensators to regulate the steady-state and dynamic voltage while avoiding the unnecessary increase in the reactive power. The simulation results in some German distribution grids show considerable effects of the proposed adaptive controller on improving both SHC and DHC.

Place, publisher, year, edition, pages
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2019
Keywords
Distribution grids, dynamic voltage regulation, hosting capacity, reactive power, renewable energy sources (RESs)
National Category
Environmental Engineering
Identifiers
urn:nbn:se:kth:diva-247822 (URN)10.1109/TEC.2018.2873057 (DOI)000460332600041 ()
Note

QC 20190327

Available from: 2019-03-27 Created: 2019-03-27 Last updated: 2019-03-27Bibliographically approved
Nilsson, M., Söder, L., Olauson, J., Eriksson, R., Nordström, L. & Ericsson, G. N. (2018). A Machine Learning Method Creating Network Models Based on Measurements. In: 2018 POWER SYSTEMS COMPUTATION CONFERENCE (PSCC): . Paper presented at 2018 POWER SYSTEMS COMPUTATION CONFERENCE (PSCC). IEEE
Open this publication in new window or tab >>A Machine Learning Method Creating Network Models Based on Measurements
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2018 (English)In: 2018 POWER SYSTEMS COMPUTATION CONFERENCE (PSCC), IEEE , 2018Conference paper, Published paper (Refereed)
Abstract [en]

Network models are essential to perform power flow analyses. In this paper a supervised regression method creating simplified network models using measurements is presented. It is an iterative method creating a network model by minimizing the difference between measurements and obtained power flow using measured net-exchanges for each node. The method is tested in a case study for the Nordic Synchronous Area considering each bidding zone as a node. The simplified network model is created using a training set and is validated using various validation methods. The obtained reactances are not correct in absolute terms; however results indicate that the obtained power flows using the created network model are accurate enough for several different applications.

Place, publisher, year, edition, pages
IEEE, 2018
Keywords
Machine learning, Nordic Power System, power flow analyses, simplified network model
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-238578 (URN)000447282400121 ()
Conference
2018 POWER SYSTEMS COMPUTATION CONFERENCE (PSCC)
Note

QC 20181105

Available from: 2018-11-05 Created: 2018-11-05 Last updated: 2018-11-05Bibliographically approved
Nilsson, M., Söder, L., Olauson, J., Eriksson, R., Nordström, L. & Ericsson, G. N. (2018). A Machine Learning Method Creating Network Models Based on Measurements. In: 2018 POWER SYSTEMS COMPUTATION CONFERENCE (PSCC): . Paper presented at 2018 POWER SYSTEMS COMPUTATION CONFERENCE (PSCC). IEEE
Open this publication in new window or tab >>A Machine Learning Method Creating Network Models Based on Measurements
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2018 (English)In: 2018 POWER SYSTEMS COMPUTATION CONFERENCE (PSCC), IEEE , 2018Conference paper, Published paper (Refereed)
Abstract [en]

Network models are essential to perform power flow analyses. In this paper a supervised regression method creating simplified network models using measurements is presented. It is an iterative method creating a network model by minimizing the difference between measurements and obtained power flow using measured net-exchanges for each node. The method is tested in a case study for the Nordic Synchronous Area considering each bidding zone as a node. The simplified network model is created using a training set and is validated using various validation methods. The obtained reactances are not correct in absolute terms; however results indicate that the obtained power flows using the created network model are accurate enough for several different applications.

Place, publisher, year, edition, pages
IEEE, 2018
Keywords
Machine learning, Nordic Power System, power flow analyses, simplified network model
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-238162 (URN)10.23919/PSCC.2018.8442822 (DOI)000447282400121 ()2-s2.0-85054003071 (Scopus ID)
Conference
2018 POWER SYSTEMS COMPUTATION CONFERENCE (PSCC)
Note

QC 20181107

Available from: 2018-11-07 Created: 2018-11-07 Last updated: 2018-11-07Bibliographically approved
Söder, L., Lund, P. D., Koduvere, H., Bolkesjø, T. F., Rossebø, G. H., Rosenlund-Soysal, E., . . . Blumberga, D. (2018). A review of demand side flexibility potential in Northern Europe. Renewable & sustainable energy reviews, 91, 654-664
Open this publication in new window or tab >>A review of demand side flexibility potential in Northern Europe
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2018 (English)In: Renewable & sustainable energy reviews, ISSN 1364-0321, E-ISSN 1879-0690, Vol. 91, p. 654-664Article, review/survey (Refereed) Published
Abstract [en]

The number of regional and national power systems with a high share of wind and solar power in the world is quickly increasing. The background for this development is improved technology, decreasing costs, and increased concern regarding environmental problems of competing technologies such as fossil fuels. For the future there are large possibilities for increasing the renewable electricity share. However, variable renewable power production has to be balanced. Demand side flexibility offers an interesting approach to the balancing issues. The aim of this paper is to compare flexibility potentials and how they were estimated in seven Northern European countries in order to compare general challenges and results as well as the connection between used method and results. The total flexibility is estimated to 12–23 GW in a system with a total peak load of 77 GW.

Place, publisher, year, edition, pages
Elsevier, 2018
Keywords
Balancing, Demand side management, Flexibility, Solar power, Wind power
National Category
Energy Systems
Identifiers
urn:nbn:se:kth:diva-227514 (URN)10.1016/j.rser.2018.03.104 (DOI)000434919600045 ()2-s2.0-85045627732 (Scopus ID)
Note

QC 20180516

Available from: 2018-05-16 Created: 2018-05-16 Last updated: 2018-07-02Bibliographically approved
Ren, G., Wan, J., Liu, J., Yu, D. & Söder, L. (2018). Analysis of wind power intermittency based on historical wind power data. Energy, 150, 482-492
Open this publication in new window or tab >>Analysis of wind power intermittency based on historical wind power data
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2018 (English)In: Energy, ISSN 0360-5442, E-ISSN 1873-6785, Vol. 150, p. 482-492Article in journal (Refereed) Published
Abstract [en]

As wind power provides an increasingly larger share of electricity supply, the challenges caused by wind power intermittency have become more and more prominent. A better understanding of wind power intermittency would contribute to mitigate it effectively. In the present study, the definition of wind power intermittency is given firstly. Based on the definition, wind power intermittency is quantified by duty ratio of wind power ramp (DRWPR). This index provides system operators quantitative insights into wind power intermittency. Furthermore, some characteristics of wind power intermittency can be extracted by the index, such as the differences between wind speed intermittency and wind power intermittency, the differences of wind power intermittency between different scales and so on. The wind power intermittency of a Chinese wind farm is studied in detail based on the proposed index and historical data.

Place, publisher, year, edition, pages
Elsevier, 2018
Keywords
Characteristics, Duty ratio, Forecasting, Intermittency, Ramp event, wind power
National Category
Energy Systems
Identifiers
urn:nbn:se:kth:diva-227592 (URN)10.1016/j.energy.2018.02.142 (DOI)000431748400038 ()2-s2.0-85042848108 (Scopus ID)
Note

QC 20180518

Available from: 2018-05-18 Created: 2018-05-18 Last updated: 2018-05-31Bibliographically approved
Stankovic, S. & Söder, L. (2018). Analytical Estimation of Reactive Power Capability of a Radial Distribution System. IEEE Transactions on Power Systems
Open this publication in new window or tab >>Analytical Estimation of Reactive Power Capability of a Radial Distribution System
2018 (English)In: IEEE Transactions on Power Systems, ISSN 0885-8950, E-ISSN 1558-0679Article in journal (Refereed) Published
Abstract [en]

The control of reactive power exchange between grids of different voltage levels has always been a concern for system operators. With production moving from the transmission to the distribution level, its importance increases. This paper proposes a novel approach to estimate reactive power capability of the grid as a whole. A linearized analytical model for an estimation of available reactive power exchange at the interface between two grids has been developed. The maximum estimation error for the scenarios we tested was only 2%. The model gives the relation between important grid parameters and the supported reactive power. The conclusions drawn from the model are confirmed on typical Swedish distribution network with scattered wind power and small industry consumers. Common scenarios in development of distribution grids are applied to show relevant parameters influence. One studied scenario is replacement of overhead lines with cables. It is shown that this particular change enhances the reactive power capability of the grid which is directly seen from the analytical analysis without running any optimal power flow. The analytical model proposed in this paper gives fundamental understanding of the reactive power capability of radial distribution grids.

Keywords
distribution grid, reactive power capability, reactive power management, voltage control, wind power
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Electrical Engineering
Identifiers
urn:nbn:se:kth:diva-231395 (URN)
Projects
Volatile
Note

QC 20180627

Available from: 2018-06-27 Created: 2018-06-27 Last updated: 2018-10-19Bibliographically approved
Nilsson, M., Söder, L. & Ericsson, G. (2018). Balancing Strategies Evaluation Framework Using Available Multi-Area Data. In: 2018 IEEE POWER & ENERGY SOCIETY GENERAL MEETING (PESGM): . Paper presented at IEEE-Power-and-Energy-Society General Meeting (PESGM), AUG 05-10, 2018, Portland, OR. IEEE
Open this publication in new window or tab >>Balancing Strategies Evaluation Framework Using Available Multi-Area Data
2018 (English)In: 2018 IEEE POWER & ENERGY SOCIETY GENERAL MEETING (PESGM), IEEE , 2018Conference paper, Published paper (Refereed)
Place, publisher, year, edition, pages
IEEE, 2018
Series
IEEE Power and Energy Society General Meeting PESGM, ISSN 1944-9925
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-244566 (URN)000457893902050 ()978-1-5386-7703-2 (ISBN)
Conference
IEEE-Power-and-Energy-Society General Meeting (PESGM), AUG 05-10, 2018, Portland, OR
Note

QC 20190312

Available from: 2019-03-12 Created: 2019-03-12 Last updated: 2019-03-12Bibliographically approved
Tomasson, E. & Söder, L. (2018). Generation Adequacy Analysis of Multi-Area Power Systems With a High Share of Wind Power. IEEE Transactions on Power Systems, 33(4), 3854-3862
Open this publication in new window or tab >>Generation Adequacy Analysis of Multi-Area Power Systems With a High Share of Wind Power
2018 (English)In: IEEE Transactions on Power Systems, ISSN 0885-8950, E-ISSN 1558-0679, Vol. 33, no 4, p. 3854-3862Article in journal (Refereed) Published
Abstract [en]

There is growing concern regarding generation adequacy within the power system industry. The ever-increasing injection of intermittent renewable resources makes it harder than before to estimate the reliability of modern power systems using traditional approaches. This paper develops a framework for estimating the reliability of modern power systems that have considerable levels of wind power generation. Monte Carlo simulation is applied using a very efficient importance sampling technique based on the cross-entropy method as well as the Copula theory. Tailor-made importance sampling functions for conventional generation, load, and wind power generation drastically reduce the number of samples required to estimate reliability parameters of interest. The methodology enables simulation of multi-area power systems with considerable amount of correlated wind power generation in each of the different areas. Simulation results confirm the efficiency as well as the accuracy of the proposed method and show that it is orders of magnitude faster than crude Monte Carlo simulation.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2018
Keywords
Monte Carlo simulation, cross-entropy (CE) method, power system reliability, Copula theory, wind power, importance sampling, correlation, loss of load probability (LOLP), expected power not served (EPNS)
National Category
Energy Systems
Identifiers
urn:nbn:se:kth:diva-240222 (URN)10.1109/TPWRS.2017.2769840 (DOI)000436009500033 ()2-s2.0-85034237938 (Scopus ID)
Note

QC 20181214

Available from: 2018-12-14 Created: 2018-12-14 Last updated: 2018-12-14Bibliographically approved
Hasanpor Divshali, P. & Söder, L. (2018). Improving PV Hosting Capacity of Distribution Grids Considering Dynamic Voltage Characteristic. In: 2018 POWER SYSTEMS COMPUTATION CONFERENCE (PSCC): . Paper presented at 2018 POWER SYSTEMS COMPUTATION CONFERENCE (PSCC). IEEE
Open this publication in new window or tab >>Improving PV Hosting Capacity of Distribution Grids Considering Dynamic Voltage Characteristic
2018 (English)In: 2018 POWER SYSTEMS COMPUTATION CONFERENCE (PSCC), IEEE , 2018Conference paper, Published paper (Refereed)
Abstract [en]

Since the penetration of renewable energy sources is rapidly increasing in distribution grids, the hosting capacity (HC) of distribution systems becomes the main concern. According to EN 50160, in LV grids, the mean value of voltage cannot exceed 1.1 pu (static characteristic) and voltage rapid changes should be kept less than 0.05 pu (dynamic characteristic). Existing researches evaluated the HC of distribution grids just based on the static characteristic. However, wind speed variations and rapid moving cloud, casting shadow on solar panels, can cause rapid voltage changes in LV grids. This paper studies the rapid voltage change by modeling the moving cloud shadow and compares the HC from perspective of both dynamic and static characteristic, which is not done before. Since voltage dynamic characteristic could be more restrictive than the static characteristic, as shown in a German distribution grid, a static synchronous compensator (STATCOM) is proposed and controlled to regulate dynamic voltage profile and to improve the HC.

Place, publisher, year, edition, pages
IEEE, 2018
Keywords
Distribution grids, Dynamic voltage regulation, Hosting capacity, reactive power control, renewable energy sources
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-238159 (URN)10.23919/PSCC.2018.8442517 (DOI)000447282400034 ()2-s2.0-85054006080 (Scopus ID)
Conference
2018 POWER SYSTEMS COMPUTATION CONFERENCE (PSCC)
Funder
Swedish Energy Agency
Note

QC 20181107

Available from: 2018-11-07 Created: 2018-11-07 Last updated: 2018-11-26Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-8189-2420

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