2021
DOI: 10.3390/electronics10222826
|View full text |Cite
|
Sign up to set email alerts
|

Uncertainty Costs Optimization of Residential Solar Generators Considering Intraday Markets

Abstract: The uncertainty of solar generation and the bull market are unavoidable in energy dispatch. The purpose of this research is to validate an uncertainty cost function of residential photovoltaic energy in a real microgrid by varying the number of auctions in intraday markets. Therefore, the following procedure is proposed. First, the variability of photovoltaic generation is quantified through Monte Carlo simulations. Second, a statistical function calculates the variability costs of photovoltaic generation. Thi… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1

Citation Types

0
3
0

Year Published

2022
2022
2023
2023

Publication Types

Select...
3

Relationship

0
3

Authors

Journals

citations
Cited by 3 publications
(3 citation statements)
references
References 37 publications
0
3
0
Order By: Relevance
“…Because the suggested P2P platform depends on the day-ahead market and intermittent nature of the PV resources, the performance of the presented trading strategies can be improved by introducing the intraday market to model the uncertainty of the PV source. However, this aspect of the suggested P2P platform has been left for future research [35].…”
Section: Sensitivity Towards Charge Rate Coefficientmentioning
confidence: 99%
“…Because the suggested P2P platform depends on the day-ahead market and intermittent nature of the PV resources, the performance of the presented trading strategies can be improved by introducing the intraday market to model the uncertainty of the PV source. However, this aspect of the suggested P2P platform has been left for future research [35].…”
Section: Sensitivity Towards Charge Rate Coefficientmentioning
confidence: 99%
“…It is able to address the above-mentioned challenges of incorporating non-convex operating features into the market clearing process. Using computational intelligence technology and co-simulation methods, it aims to model and solve complex optimization problems more realistically [17]. Reference [18] uses Q-learning to help electricity suppliers in strategic bidding, for higher profits.…”
Section: Introduction 1backgroundmentioning
confidence: 99%
“…In [4], the uncertainty in the scheduling of electricity distribution generation is presented considering the electricity market. The modeling and impact of different uncertainties (in the intensity of primary energy sources as well as in the energy price) at the intraday market level was developed and proposed here.…”
mentioning
confidence: 99%