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Strategies to improve the voltage quality in active low-voltage distribution networks using DSO's assets
KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems.ORCID iD: 0000-0002-2014-0444
KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems.ORCID iD: 0000-0003-3946-7655
KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems.ORCID iD: 0000-0002-4140-4736
KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems.ORCID iD: 0000-0003-3014-5609
2017 (English)In: IET Generation, Transmission & Distribution, ISSN 1751-8687, E-ISSN 1751-8695, Vol. 11, no 1, 73-81 p.Article 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. Vol. 11, no 1, 73-81 p.
Keyword [en]
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: urn:nbn:se:kth:diva-203837DOI: 10.1049/iet-gtd.2016.0428ISI: 000393751800009Scopus ID: 2-s2.0-85009412455OAI: oai:DiVA.org:kth-203837DiVA: diva2:1083179
Note

QC 20170320

Available from: 2017-03-20 Created: 2017-03-20 Last updated: 2017-03-20Bibliographically approved

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Armendariz, MikelBabazadeh, DavoodBrodén, DanielNordström, Lars
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