Picture of athlete cycling

Open Access research with a real impact on health...

The Strathprints institutional repository is a digital archive of University of Strathclyde's Open Access research outputs. Strathprints provides access to thousands of Open Access research papers by Strathclyde researchers, including by researchers from the Physical Activity for Health Group based within the School of Psychological Sciences & Health. Research here seeks to better understand how and why physical activity improves health, gain a better understanding of the amount, intensity, and type of physical activity needed for health benefits, and evaluate the effect of interventions to promote physical activity.

Explore open research content by Physical Activity for Health...

Coordinated two-stage volt/var management in distribution networks

Mokgonyana, Lesiba and Zhang, Jiangfeng and Zhang, Lijun and Xia, Xiaohua (2016) Coordinated two-stage volt/var management in distribution networks. Electric Power Systems Research. ISSN 0378-7796 (In Press)

[img] Text (Mokgonyana-etal-EPSR2016-Coordinated-two-stage-volt-var-management-in-distribution-networks)
Mokgonyana_etal_EPSR2016_Coordinated_two_stage_volt_var_management_in_distribution_networks.pdf - Accepted Author Manuscript
Restricted to Repository staff only until 22 July 2017.
License: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 logo

Download (405kB) | Request a copy from the Strathclyde author

Abstract

This paper investigates daily volt/var control in distribution networks using feeder capacitors as well as substation capacitors paired with on-load tap changers. A twostage coordinated approach is proposed. Firstly, the feeder capacitor dispatch schedule is determined based on reactive power heuristics. Then, an optimisation model is applied to determine the dispatch schedule of the substation devices taking into account the control actions of the feeder capacitors. The reference voltage of the substation secondary bus and the tap position limits of transformers are modified such that the model adapts to varying load conditions. The optimisation model is solved with a modified particle swarm optimisation algorithm. Furthermore, the proposed method is compared with conventional volt/var control strategies using a distribution network case study. It is demonstrated that the proposed approach performs better than the conventional strategies in terms of voltage deviation and energy loss minimisation.