.png){kind=icon}
.png){kind=icon}
Return
Using Multivariate Copulas to capture Forecasting Error and Optimize Flexibility Provision from a Local Energy Community
.png){kind=icon}
PRE
AI
T
T
M
P
S
DOI：10.1109/POWERTECH55446.2023.10202906.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
While forming a local energy community (LEC), flexibility provision is an emerging service along with the increase of distributed energy resources (DERs) to cope with the uncertainty of DERs and the forecasting error. This paper proposes a stochastic optimization model for day-ahead scheduling to decide on the flexibility provision of LEC taking into account all profile scenarios occurring due to forecasting errors. Considering the correlation between time steps, the profile scenarios and their probabilities are generated by using Multivariate Copulas based on the historical data. In comparison with forecast-based deterministic optimization, the results show that the flexibility provision based on the proposed model is conservatively optimized, avoiding penalties due to unavailability of flexibility. Additionally, generated profiles both in forecast-based deterministic and stochastic optimization do not violate the network constraints which are verified at Bunnik living lab in the Netherlands.
Keywords:
Battery energy storage system
flexibility provision
local energy community
multivariate copulas
stochastic optimization
Journal
I
IF:
0
Papers:
29
Citations:
0
Organization
Cited Papers