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Publications (10 of 29) Show all publications
Babazadeh, D., Hohn, F., Wu, Y. & Nordström, L. (2017). Distributed Two-stage Network Topology Processor for HVDC Grid Operation. In: 2017 IEEE Manchester PowerTech, Powertech 2017: . Paper presented at 12th IEEE PES PowerTech Conference, Towards and Beyond Sustainable Energy Systems, juni 18-22, Manchester, UK. IEEE, Article ID 7980841.
Open this publication in new window or tab >>Distributed Two-stage Network Topology Processor for HVDC Grid Operation
2017 (English)In: 2017 IEEE Manchester PowerTech, Powertech 2017, IEEE, 2017, article id 7980841Conference paper, Published paper (Refereed)
Abstract [en]

This paper presents the results of an analysis of distributed two-stage coordination of network topology processor for HVDC grids. In the first stage of the two-stage processor, the substation topology is analyzed locally using an automated graph-based algorithm. Thereafter, a distributed algorithm is proposed to used the neighboring information to realize the grid connectivity. For distributed islanding detection, the connectivity problem is formulated as a set of linear equations and solved iteratively using successive-over-relaxation method. The performance of the proposed methods versus conventional one-stage method has been tested in an islanding scenario for a 5-terminal HVDC grid.

Place, publisher, year, edition, pages
IEEE, 2017
Keywords
distributed coordination, HVDC grid, topology processor
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-202752 (URN)10.1109/PTC.2017.7980841 (DOI)000411142500054 ()2-s2.0-85034774933 (Scopus ID)9781509042371 (ISBN)
Conference
12th IEEE PES PowerTech Conference, Towards and Beyond Sustainable Energy Systems, juni 18-22, Manchester, UK
Funder
SweGRIDS - Swedish Centre for Smart Grids and Energy Storage
Note

QC 20170627

Available from: 2017-03-05 Created: 2017-03-05 Last updated: 2018-02-26Bibliographically approved
Babazadeh, D., Hohn, F., Wu, Y. & Nordström, L. (2017). Distributed Two-stage Network Topology Processor for HVDC Grid Operation. In: 2017 IEEE POWER & ENERGY SOCIETY GENERAL MEETING: . Paper presented at 2017 IEEE Power & Energy Society General Meeting, JUL 16-20, 2017, Chicago, IL. IEEE
Open this publication in new window or tab >>Distributed Two-stage Network Topology Processor for HVDC Grid Operation
2017 (English)In: 2017 IEEE POWER & ENERGY SOCIETY GENERAL MEETING, IEEE , 2017Conference paper, Published paper (Refereed)
Abstract [en]

This paper presents the results of an analysis of distributed two-stage coordination of network topology processor for HVDC grids. In the first stage of the two-stage processor, the substation topology is analyzed locally using an automated graph based algorithm. Thereafter, a distributed algorithm is proposed to used the neighboring information to realize the grid connectivity. For distributed islanding detection, the connectivity problem is formulated as a set of linear equations and solved iteratively using successive-over-relaxation method. The performance of the proposed methods versus conventional one-stage method has been tested in an islandinv, scenario for a 5-terminal HVDC grid.

Place, publisher, year, edition, pages
IEEE, 2017
Series
IEEE Power and Energy Society General Meeting PESGM, ISSN 1944-9925
Keywords
distributed coordination, HVDC grid, topology processor
National Category
Computational Mathematics
Identifiers
urn:nbn:se:kth:diva-228181 (URN)10.1109/PESGM.2017.8274088 (DOI)000426921801072 ()2-s2.0-85046345247 (Scopus ID)978-1-5386-2212-4 (ISBN)
Conference
2017 IEEE Power & Energy Society General Meeting, JUL 16-20, 2017, Chicago, IL
Note

QC 20180521

Available from: 2018-05-21 Created: 2018-05-21 Last updated: 2018-11-19Bibliographically approved
Armendariz, M., Babazadeh, D., Brodén, D. & Nordström, L. (2017). Strategies to improve the voltage quality in active low-voltage distribution networks using DSO's assets. IET Generation, Transmission & Distribution, 11(1), 73-81
Open this publication in new window or tab >>Strategies to improve the voltage quality in active low-voltage distribution networks using DSO's assets
2017 (English)In: IET Generation, Transmission & Distribution, ISSN 1751-8687, E-ISSN 1751-8695, Vol. 11, no 1, p. 73-81Article in journal (Refereed) Published
Abstract [en]

This study addresses the problem of voltage variations in active low-voltage distribution networks caused by distributed photovoltaic (PV) generation. Three strategies based on model predictive control (MPC) are introduced to flatten the voltage profile in a cost-optimal way. The compared strategies are the business as usual approach that manipulates a controllable on-load tap changer at the primary substation, the problematic feeder control strategy (CS) that adds an additional degree of freedom by controlling the critical secondary substations (SSs), and finally the compensation strategy, which controls the primary substation and compensates the non-critical SSs. A sensitivity analysis on the CSs has been conducted comparing the voltage variation reduction and the asset utilization with regard to the accuracy of the prediction models and the forecasted disturbance data. The results show that better (and more costly) characterisation of these parameters only provide a marginal improvement in the reduction of the voltage variations due to the restriction caused by the heavy tap change penalisation. Moreover, the tested case-study shows that the problematic feeder CS outperforms the compensation strategy in terms of larger voltage variation reduction for similar asset utilisation.

Place, publisher, year, edition, pages
IEEE, 2017
Keywords
power distribution control, power supply quality, voltage control, photovoltaic power systems, distributed power generation, predictive control, cost optimal control, substations, sensitivity analysis, asset management, compensation, voltage quality improvement, active low-voltage distribution networks, DSO assets, distributed photovoltaic generation, distributed PV generation, model predictive control, MPC, controllable on-load tap changer, primary substation, feeder control strategy, feeder CS, critical secondary substation control, noncritical SS compensation, voltage variation reduction, asset utilisation, prediction models, distribution system operator
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-203837 (URN)10.1049/iet-gtd.2016.0428 (DOI)000393751800009 ()2-s2.0-85009412455 (Scopus ID)
Note

QC 20170320

Available from: 2017-03-20 Created: 2017-03-20 Last updated: 2017-11-29Bibliographically approved
Armendariz, M., Babazadeh, D., Nordström, L. & Barchiesi, M. (2016). A Method to Place Meters in Active Low Voltage Distribution Networks using BPSO Algorithm. In: : . Paper presented at 19th Power Systems Computational Conference, PSCC, June 2016 in Genova, Italy..
Open this publication in new window or tab >>A Method to Place Meters in Active Low Voltage Distribution Networks using BPSO Algorithm
2016 (English)Conference paper, Published paper (Refereed)
Abstract [en]

This paper proposes a method to be used by a DSOto optimally place sensors at MV/LV substation and some lowvoltage cable distribution cabinets. This method aims to improvethe estimation of the grid states at low voltage distributionnetworks. This method formulates a multi-objective optimizationproblem to determine the optimal meter placementconfiguration. This formulation minimizes the low voltage stateestimation error and the cost associated to a particular meterdeployment configuration. The method uses Binary ParticleSwarm Optimization (BPSO) to solve the optimization problemand it has been tested on a network based on the Cigré LVbenchmark grid. The simulation results show that the methodcan be applied to both situations where smart metermeasurements are available and situations where they are not. Inthe latter situation the measurements are replaced by pseudomeasurements,which represent meter readings by using smartmeter historical data and prediction models.

Keywords
Active Low Voltage Distribution Networks, BPSO, Meter Placement Problem, Multi-objective Optimization, Observability Analysis, State Estimation
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-180710 (URN)000382485600061 ()2-s2.0-84986588599 (Scopus ID)
Conference
19th Power Systems Computational Conference, PSCC, June 2016 in Genova, Italy.
Note

QC 20161017

Available from: 2016-01-21 Created: 2016-01-21 Last updated: 2017-11-06Bibliographically approved
Khan, M. T., Habib, M. Z., Karlsson, E., Babazadeh, D. & Nordström, L. (2016). Distributed Secondary Frequency Control Considering Rapid Start Units Using Alternating Direction Method of Multipliers. In: 2016 Workshop on Modeling and Simulation of Cyber-Physical Energy Systems, MSCPES 2016 - Held as Part of CPS Week, Proceedings: . Paper presented at Workshop on Modeling and Simulation of Cyber-Physical Energy Systems, MSCPES 2016, Hofburg PalaceJosefsplatz 3Vienna, Austria, 11 April 2016 through. Institute of Electrical and Electronics Engineers (IEEE), Article ID 07480223.
Open this publication in new window or tab >>Distributed Secondary Frequency Control Considering Rapid Start Units Using Alternating Direction Method of Multipliers
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2016 (English)In: 2016 Workshop on Modeling and Simulation of Cyber-Physical Energy Systems, MSCPES 2016 - Held as Part of CPS Week, Proceedings, Institute of Electrical and Electronics Engineers (IEEE), 2016, article id 07480223Conference paper, Published paper (Refereed)
Abstract [en]

Secondary frequency control plays a vital role inpower systems and has therefore been the focus of muchresearch. Recent focus is being targeted towards developingdistributed solutions. This paper proposes a fast converging,distributed solution for secondary frequency control on the basisof the Alternating Direction Method of Multipliers (ADMM).For economic benefits the proposed solution integrates the useof rapid start units. Rapid start units are fast response and highramp offline units, which can provide the reserve power in caseof need. The proposed control scheme is a distributed solution tocombine secondary frequency control, economic dispatch and theRS start up process. Finally, the developed algorithm is tested fora power system model on a real-time co-simulation platform. Theresults show a fast converging algorithm that provides secondaryfrequency control compliant with ENTSO-E requirements, andthe economical benefits of the inclusion of a rapid start unit.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2016
Keywords
ADMM, AGC, Rapid start unit, Economic dispatch
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-183269 (URN)10.1109/MSCPES.2016.7480223 (DOI)000389021900006 ()2-s2.0-84978919518 (Scopus ID)9781509011582 (ISBN)
Conference
Workshop on Modeling and Simulation of Cyber-Physical Energy Systems, MSCPES 2016, Hofburg PalaceJosefsplatz 3Vienna, Austria, 11 April 2016 through
Note

QC 20161031

Available from: 2016-03-03 Created: 2016-03-03 Last updated: 2017-03-15Bibliographically approved
Yiming, W., Babazadeh, D. & Nordström, L. (2016). Modeling of Communication Infrastructure Compatible to Nordic 32 Power System. In: IEEE-Power-and-Energy-Society General Meeting 2016: . Paper presented at IEEE PES GM 2016. IEEE
Open this publication in new window or tab >>Modeling of Communication Infrastructure Compatible to Nordic 32 Power System
2016 (English)In: IEEE-Power-and-Energy-Society General Meeting 2016, IEEE, 2016Conference paper, Published paper (Refereed)
Abstract [en]

Smart Grid integrates communication and computationtechnologies into power systems. Research on interdisciplinarytopics between power system and communicationsystems requires models for both systems. There are severalpower system models available representing standard powersystems and real power systems. However, lacking of theircorresponding communication infrastructure information leadsthe difficulty of communication system modeling. In this paper,a communication infrastructure model compatible to Nordic 32power system model has been developed and presented. In thismodel, Wide Area Monitoring System (WAMS) is incorporatedwith Supervisor Control and Data Acquisition system. Theparameters of this model are based on the data from a Nordicelectric power utility. Validation of the model is performedthrough comparison of results from simulation and a previousempirical data study performed on the same utility network. Inadditional, this model is simulated by using different Qualityof Service (QoS) mechanism. The obtained results show thatcongestion management mechanisms introduce additional delayto the highest priority traffic slightly. But traffics with lowerpriority can be benefit from congestion management mechanisms.The proposed model can be widely used for other research onNordic 32 power system.

Place, publisher, year, edition, pages
IEEE, 2016
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-178167 (URN)10.1109/PESGM.2016.7741521 (DOI)000399937901161 ()2-s2.0-85001959389 (Scopus ID)
Conference
IEEE PES GM 2016
Note

QC 20170313

Available from: 2015-12-07 Created: 2015-12-07 Last updated: 2017-06-15Bibliographically approved
Babazadeh, D., Muthukrishnan, A., Mitra, P., Larsson, T. & Nordström, L. (2016). Real-Time Estimation of AC-Grid Short Circuit Capacity for HVDC Control Application. IET Generation, Transmission & Distribution
Open this publication in new window or tab >>Real-Time Estimation of AC-Grid Short Circuit Capacity for HVDC Control Application
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2016 (English)In: IET Generation, Transmission & Distribution, ISSN 1751-8687, E-ISSN 1751-8695Article in journal (Refereed) Published
Abstract [en]

Being able to estimate the AC grid strength using Short Circuit Capacity (SCC) fromthe perspective of a connected HVDC station allows adjustment of converter control parameters orto select the converter’s operational control mode. The short circuit capacity can be calculated byestimation of the grid’s impedance and its equivalent voltage. This paper presents the operationaland practical challenges in real-time implementation of the grid estimation algorithms especiallyfor HVDC applications. This paper shows that the Recursive Least Square (RLS) algorithm can bevery efficiently used for the real-time estimation of SCC. This technique forms a regression prob-lem using algebraic complex equations with an objective to minimize the error between estimatedand measured parameters. The algorithm has been reformulated and simplified to make it non-complex without the use of matrices, in order to facilitate further implementation on an industrialreal-time controller. The performance of the real-time implementation has been evaluated usinga HIL platform. A sensitivity analysis has been also carriedout to study the impact of differentparameters and operational conditions on the performance of the estimation algorithm. Finally, theactual application of real-time SCC estimation for the HVDCsystems has been demonstrated.

Place, publisher, year, edition, pages
IET, 2016
Keywords
estimation, HVDC, real-time, recursive least square, short circuit capacity
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-180714 (URN)10.1049/iet-gtd.2016.0465 (DOI)
Funder
SweGRIDS - Swedish Centre for Smart Grids and Energy Storage
Note

QC 20160901

Available from: 2016-01-21 Created: 2016-01-21 Last updated: 2017-11-30Bibliographically approved
Babazadeh, D., Muthukrishnan, A., Mitra, P., Larsson, T. & Nordström, L. (2016). Selection of DC Voltage Controlling Station in an HVDC Grid. Electric power systems research, 144, 224-232
Open this publication in new window or tab >>Selection of DC Voltage Controlling Station in an HVDC Grid
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2016 (English)In: Electric power systems research, ISSN 0378-7796, E-ISSN 1873-2046, Vol. 144, p. 224-232Article in journal (Refereed) Published
Abstract [en]

This paper proposes a real-time quantitative evaluation of HVDC converters’ in an HVDC grid to select the suitable DC slack converter. This real-time evaluation considers the strength of connecting AC grid and the converter's on-line capacity margin as selection metrics. The strength of AC grid is evaluated in real-time by the estimation of grid short circuit capacity using recursive lease square algorithm. Given these selection metrics, the credibility of HVDC stations in controlling the DC voltage can be offered to the system operator in real-time for further operational decisions. This paper also studies the practical aspect of the estimation algorithm regarding selection of the operating points. As major contribution, it suggests to intelligently use a naturally occurring droop response in HVDC grids as a second operating point in the estimation algorithm to calculate the short circuit capacity. The method has been tested through set of scenarios using a real-time co-simulation platform. This platform includes real-time power system simulator to model AC/DC grid, industrial HVDC controllers and corresponding ICT systems. The results show that the proper selection of DC slack station can improve the AC system response and DC voltage drops during disturbances.

Place, publisher, year, edition, pages
Elsevier, 2016
Keywords
HVDC grid, Short circuit capacity, Slack bus selection, Voltage control
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-180715 (URN)10.1016/j.epsr.2016.12.008 (DOI)000392889700024 ()2-s2.0-85006978465 (Scopus ID)
Funder
SweGRIDS - Swedish Centre for Smart Grids and Energy Storage
Note

QC 20160901

Available from: 2016-01-21 Created: 2016-01-21 Last updated: 2017-11-30Bibliographically approved
Babazadeh, D., Muthukrishnan, A., Nordström, L., Mitra, P. & Larsson, T. (2016). Short Circuit Capacity Estimation for HVDC Control Application. In: Power Systems Computation Conference (PSCC), 2016: . Paper presented at Power Systems Computation Conference, 2016, 20-24 June 2016. IEEE conference proceedings
Open this publication in new window or tab >>Short Circuit Capacity Estimation for HVDC Control Application
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2016 (English)In: Power Systems Computation Conference (PSCC), 2016, IEEE conference proceedings, 2016Conference paper, Published paper (Refereed)
Abstract [en]

This paper studies various operational aspects ofrecursive least square algorithm as a potential solution for theestimation of short circuit capacity in HVDC application. Inthis work, low computational requirement, minor operationalcomplication and acceptable accuracy of the estimated gridparameters have been considered as the performance metricsfor the selection of the suitable estimation algorithm. The chosenalgorithm forms a regression problem using at least two algebraiccomplex equations based on two different operating points. Theappropriate selection of the second operating point which fulfillsthe minimum required accuracy and convergence rate is of greatimportance, particularly in the practical implementation. Thispaper proposes and analyzes several choices of providing thesecond operating point for the estimation algorithm adopted toHVDC application. Furthermore, a sensitivity analysis has beencarried out to assess the impact of different parameters andoperational conditions such as execution time on the performanceof the estimation algorithm for the HVDC control purposes.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2016
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-178163 (URN)10.1109/PSCC.2016.7540875 (DOI)000382485600063 ()2-s2.0-84986593853 (Scopus ID)
Conference
Power Systems Computation Conference, 2016, 20-24 June 2016
Note

QC 20160901

Available from: 2015-12-07 Created: 2015-12-07 Last updated: 2016-10-17Bibliographically approved
Babazadeh, D., Van Hertem, D. & Nordström, L. (2016). Study of Centralized and Distributed Coordination of Power Injection in Multi-TSO HVDC Grid with Large Off-shore Wind Integration. Electric power systems research, 136, 281-288
Open this publication in new window or tab >>Study of Centralized and Distributed Coordination of Power Injection in Multi-TSO HVDC Grid with Large Off-shore Wind Integration
2016 (English)In: Electric power systems research, ISSN 0378-7796, E-ISSN 1873-2046, Vol. 136, p. 281-288Article in journal (Refereed) Published
Abstract [en]

This paper studies centralized and distributed schemes for the coordinationof power injection in an HVDC grid connected to large wind generation.This coordination of power injection aims to keep the power balanced withinthe HVDC grid especially during large wind disturbances. Furthermore, thecoordination tries to follow the converters’ schedules set by the connectingAC-TSOs every 15−minutes. This schedule comes from an overall combinedAC/DC economic dispatch calculation with lower resolution compared to thiscoordination. In this paper, the coordination of power injection has been formulatedas a non-linear constrained optimization problem for the centralizedarchitecture. Next, the centralized optimization problem is decomposed tosub-problems using the Auxiliary Problem Principle (APP) method for thedistributed architecture. This distributed optimization problem is solved byexchanging the required information between the AC TSOs. These two differentapproaches have been evaluated for a 5-terminal HVDC grid. Furthermore,a sensitivity analysis has been carried out to find the optimal updatingrate of power injection set-points. The result shows that the more frequentupdating of power injection coordination in the centralized architecture improvesthe generation reserves in each AC area.

Place, publisher, year, edition, pages
Elsevier, 2016
Keywords
Distributed optimization, HVDC grid, Optimal power injection, Wind farm
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-178726 (URN)10.1016/j.epsr.2016.03.001 (DOI)000375505800028 ()2-s2.0-84960905190 (Scopus ID)
Note

QC 20160413

Available from: 2015-12-08 Created: 2015-12-08 Last updated: 2017-12-01Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0003-3946-7655

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