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Frequency analysis of solar pv power to enable optimal building load control

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7 Scopus citations

Abstract

In this paper, we present a flexibility estimation mechanism for buildings' thermostatically controlled loads (TCLs) to enable the distribution level consumption of the majority of solar photovoltaic (PV) generation by local building TCLs. The local consumption of PV generation provides several advantages to the grid operation as well as the consumers, such as reducing the stress on the distribution network, minimizing voltage fluctuations and two-way power flows in the distribution network, and reducing the required battery storage capacity for PV integration. This would result in increasing the solar PV generation penetration levels. The aims of this study are twofold. First, spectral (frequency) analyses of solar PV power generation together with the power consumption of multiple building TCLs (such as heating, ventilation, and air conditioning (HVAC) systems, water heaters, and refrigerators) are performed. These analyses define the bandwidth over which these TCLs can operate and also describe the PV generation frequency bandwidth. Such spectral analyses, in frequency domain, can help identify the flexible components of PV generation that can be consumed by the various TCLs through optimal building load utilization. Second, a quadratic optimization problem based on model predictive control is formulated to allow consuming most of the low and medium frequency content of the PV power locally by building TCLs, while maintaining occupants' comfort and TCLs' physical constraints. The solution to the proposed optimization problem is achieved using optimal control strategies. Numerical results show that most of the low and medium frequency content of the PV generation can be consumed locally by building TCLs. The remaining high-frequency content of the PV generation can then be stored/offset using energy storage systems.

Original languageEnglish
Article number4593
JournalEnergies
Volume13
Issue number18
DOIs
StatePublished - Sep 2020

Funding

This material is based upon work supported by the U.S. Department of Energy, Office of Energy Efficiency & Renewable Energy, the SunShot National Laboratory Multiyear Partnership (SuNLaMP) program. This manuscript has been authored by UT-Battelle, LLC under Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan). Funding: This material is based upon work supported by the U.S. Department of Energy, Office of Energy Efficiency & Renewable Energy, the SunShot National Laboratory Multiyear Partnership (SuNLaMP) program.

Keywords

  • Boxplot
  • Energy storage systems
  • Fourier transform
  • Model predictive control
  • Solar photovoltaic
  • Spectral analysis
  • Thermostatically controlled loads

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