Advanced search
1 file | 2.80 MB Add to list

Investigating the need for real time measurements in industrial wind power systems combined with battery storage

Vasileios Papadopoulos (UGent) , Jos Knockaert (UGent) , Chris Develder (UGent) and Jan Desmet (UGent)
(2019) APPLIED ENERGY. 247. p.559-571
Author
Organization
Abstract
In simulating renewable energy systems (RES), researchers tend to focus on the modeling methodology, but less on the impact of data on the obtained results and associated conclusions. Yet, results may be particularly dependent on the data resolution. RES studies on that impact of data resolution mostly consider households with PV systems, leaving industrial sites and wind power systems out of scope. In this paper, we consider a system comprising a medium-sized wind turbine, a high power battery and an industrial load, connected to a distribution grid. Wind and load power were measured concurrently in real time at 1 s resolution for 2 months in summer 2017, at two locations in Belgium. We performed two simulations, one using the real time data at 1 s resolution and the other using the same power data averaged over 10 min intervals. We compared both simulations to calculate three metrics: total self-sufficiency error, battery utilization error and instantaneous self-sufficiency error. We repeated the analysis using different settings in terms of battery capacity, battery C rate limit and load ratio. We conclude that: (i) total self-sufficiency, in all cases, is overestimated, ranging between 0.06 and 3.6%, with errors decreasing for higher battery capacity, (ii) battery utilization is always underestimated with errors ranging between 7.5 and 44.7%, primarily depending on the C rate limit, and (iii) there is a clear correlation between instantaneous self-sufficiency error and instantaneous ratio of the averaged load and wind power, with errors exceeding 100% when the ratio ranges in 0.5-2.
Keywords
Renewable energy, High resolution, Wind turbines, Battery storage, Lithium-ion, Self-sufficiency, ENERGY-STORAGE, SELF-CONSUMPTION, TEMPORAL RESOLUTION, OPTIMIZATION, GENERATION, TECHNOLOGIES, ALGORITHM, IMPACT, SIMULATION, RENEWABLES

Downloads

  • (...).pdf
    • full text
    • |
    • UGent only
    • |
    • PDF
    • |
    • 2.80 MB

Citation

Please use this url to cite or link to this publication:

MLA
Papadopoulos, Vasileios et al. “Investigating the Need for Real Time Measurements in Industrial Wind Power Systems Combined with Battery Storage.” APPLIED ENERGY 247 (2019): 559–571. Print.
APA
Papadopoulos, Vasileios, Knockaert, J., Develder, C., & Desmet, J. (2019). Investigating the need for real time measurements in industrial wind power systems combined with battery storage. APPLIED ENERGY, 247, 559–571.
Chicago author-date
Papadopoulos, Vasileios, Jos Knockaert, Chris Develder, and Jan Desmet. 2019. “Investigating the Need for Real Time Measurements in Industrial Wind Power Systems Combined with Battery Storage.” Applied Energy 247: 559–571.
Chicago author-date (all authors)
Papadopoulos, Vasileios, Jos Knockaert, Chris Develder, and Jan Desmet. 2019. “Investigating the Need for Real Time Measurements in Industrial Wind Power Systems Combined with Battery Storage.” Applied Energy 247: 559–571.
Vancouver
1.
Papadopoulos V, Knockaert J, Develder C, Desmet J. Investigating the need for real time measurements in industrial wind power systems combined with battery storage. APPLIED ENERGY. Elsevier ; 2019;247:559–71.
IEEE
[1]
V. Papadopoulos, J. Knockaert, C. Develder, and J. Desmet, “Investigating the need for real time measurements in industrial wind power systems combined with battery storage,” APPLIED ENERGY, vol. 247, pp. 559–571, 2019.
@article{8612733,
  abstract     = {In simulating renewable energy systems (RES), researchers tend to focus on the modeling methodology, but less on the impact of data on the obtained results and associated conclusions. Yet, results may be particularly dependent on the data resolution. RES studies on that impact of data resolution mostly consider households with PV systems, leaving industrial sites and wind power systems out of scope. In this paper, we consider a system comprising a medium-sized wind turbine, a high power battery and an industrial load, connected to a distribution grid. Wind and load power were measured concurrently in real time at 1 s resolution for 2 months in summer 2017, at two locations in Belgium. We performed two simulations, one using the real time data at 1 s resolution and the other using the same power data averaged over 10 min intervals. We compared both simulations to calculate three metrics: total self-sufficiency error, battery utilization error and instantaneous self-sufficiency error. We repeated the analysis using different settings in terms of battery capacity, battery C rate limit and load ratio. We conclude that: (i) total self-sufficiency, in all cases, is overestimated, ranging between 0.06 and 3.6%, with errors decreasing for higher battery capacity, (ii) battery utilization is always underestimated with errors ranging between 7.5 and 44.7%, primarily depending on the C rate limit, and (iii) there is a clear correlation between instantaneous self-sufficiency error and instantaneous ratio of the averaged load and wind power, with errors exceeding 100% when the ratio ranges in 0.5-2.},
  author       = {Papadopoulos, Vasileios and Knockaert, Jos and Develder, Chris and Desmet, Jan},
  issn         = {0306-2619},
  journal      = {APPLIED ENERGY},
  keywords     = {Renewable energy,High resolution,Wind turbines,Battery storage,Lithium-ion,Self-sufficiency,ENERGY-STORAGE,SELF-CONSUMPTION,TEMPORAL RESOLUTION,OPTIMIZATION,GENERATION,TECHNOLOGIES,ALGORITHM,IMPACT,SIMULATION,RENEWABLES},
  language     = {eng},
  pages        = {559--571},
  publisher    = {Elsevier },
  title        = {Investigating the need for real time measurements in industrial wind power systems combined with battery storage},
  url          = {http://dx.doi.org/10.1016/j.apenergy.2019.04.051},
  volume       = {247},
  year         = {2019},
}

Altmetric
View in Altmetric
Web of Science
Times cited: