Residential Demand Side Management Under High Penetration of Rooftop Photovoltaic Units

Yao E, Samadi P, Wong VWS, Schober R (2015)


Publication Language: English

Publication Type: Journal article

Publication year: 2015

Journal

Book Volume: 7

Pages Range: 1597 - 1608

Journal Issue: 3

DOI: 10.1109/TSG.2015.2472523

Abstract

In a residential area where many households have installed rooftop photovoltaic (PV) units, there is a reverse power flow from the households to the substation when the power generation from PV units is larger than the aggregate load of the households. This reverse power flow causes the voltage rise problem. In this paper, we study the use of demand side management to mitigate the voltage rise problem. We propose an autonomous energy consumption scheduling algorithm, which schedules the operation of deferrable loads to jointly shave the peak load and reduce the reverse power flow. The proposed algorithm shifts the operation of deferrable loads from peak consumption hours to hours with high-power generation from the PV units. We use stochastic programming to formulate an energy consumption scheduling problem, which takes into account the uncertainty related to the amount of power generation from PV units. The formulated cost function comprises a monetary cost for energy consumption, the revenue from energy export, and an external cost for the voltage rise. Numerical results show that our proposed algorithm can mitigate the voltage rise problem in areas with high penetration of PV units and reduce the peak-to-average ratio of the aggregate load.

Authors with CRIS profile

Involved external institutions

How to cite

APA:

Yao, E., Samadi, P., Wong, V.W.S., & Schober, R. (2015). Residential Demand Side Management Under High Penetration of Rooftop Photovoltaic Units. IEEE Transactions on Smart Grid, 7(3), 1597 - 1608. https://dx.doi.org/10.1109/TSG.2015.2472523

MLA:

Yao, Enxin, et al. "Residential Demand Side Management Under High Penetration of Rooftop Photovoltaic Units." IEEE Transactions on Smart Grid 7.3 (2015): 1597 - 1608.

BibTeX: Download