Assessment of distribution networks performance considering residential photovoltaic systems with demand response applications. Shamshiri, M., Gan, C., & Omar, R. Journal of Renewable and Sustainable Energy, 2017. doi abstract bibtex The large penetration of solar photovoltaic (PV) systems at low voltage (LV) networks has started to introduce new challenges to distribution network operators. With the emergence of smart grid technology, the demand response (DR) has been identified as one of the promising approaches for network operators to increase operational flexibility, particularly in the presence of renewable energy resources. Therefore, it is important to investigate how DR applications at a LV consumer level can help to improve network performance. However, so far, only a limited number of works have addressed the implications of DR at LV networks with a PV system. The parametric analysis of the benefits of DR has not been adequately addressed for LV networks with multiple DR-PV interaction scenarios. In this regard, three case studies have been considered in this work, namely, consumers who respond to their own demand profile, consumers who respond to the PV generation profile, and the optimized demand response from consumers. The fractal-based approach has been utilized to model a large number of urban LV networks. Subsequently, the particle swarm optimization technique is utilized to model individual consumers' optimized DR profiles. Comprehensive network case studies are performed considering 100 urban LV network samples under the influence of different DR-PV scenarios. The results suggest that with 100% PV penetration, DR applications at a residential consumer level can achieve 32% peak reduction, reduce network losses by 42%, and achieve 12% load factor increment for the optimized demand response case. © 2017 Author(s).
@article{shamshiri_assessment_2017,
title = {Assessment of distribution networks performance considering residential photovoltaic systems with demand response applications},
volume = {9},
doi = {10.1063/1.4993048},
abstract = {The large penetration of solar photovoltaic (PV) systems at low voltage (LV) networks has started to introduce new challenges to distribution network operators. With the emergence of smart grid technology, the demand response (DR) has been identified as one of the promising approaches for network operators to increase operational flexibility, particularly in the presence of renewable energy resources. Therefore, it is important to investigate how DR applications at a LV consumer level can help to improve network performance. However, so far, only a limited number of works have addressed the implications of DR at LV networks with a PV system. The parametric analysis of the benefits of DR has not been adequately addressed for LV networks with multiple DR-PV interaction scenarios. In this regard, three case studies have been considered in this work, namely, consumers who respond to their own demand profile, consumers who respond to the PV generation profile, and the optimized demand response from consumers. The fractal-based approach has been utilized to model a large number of urban LV networks. Subsequently, the particle swarm optimization technique is utilized to model individual consumers' optimized DR profiles. Comprehensive network case studies are performed considering 100 urban LV network samples under the influence of different DR-PV scenarios. The results suggest that with 100\% PV penetration, DR applications at a residential consumer level can achieve 32\% peak reduction, reduce network losses by 42\%, and achieve 12\% load factor increment for the optimized demand response case. © 2017 Author(s).},
number = {4},
journal = {Journal of Renewable and Sustainable Energy},
author = {Shamshiri, M. and Gan, C.K. and Omar, R.},
year = {2017}
}
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Subsequently, the particle swarm optimization technique is utilized to model individual consumers' optimized DR profiles. Comprehensive network case studies are performed considering 100 urban LV network samples under the influence of different DR-PV scenarios. 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