Options
Efficient Cost-Minimization Schemes for Electrical Energy Demand Satisfaction by Prosumers in Microgrids with Battery Storage Capabilities
Citation Link: https://doi.org/10.15480/882.13195
Publikationstyp
Conference Paper
Date Issued
2024
Sprache
English
TORE-DOI
Citation
International Joint Conference on Artificial Intelligence (IJCAI 2024)
Contribution to Conference
International Joint Conference on Artificial Intelligence (IJCAI 2024)
Publisher DOI
Scopus ID
Publisher
IJCAI
ISBN
978-1-956792-04-1
We introduce and study various models of how prosumers in a microgrid can satisfy their demands of electrical energy while minimizing their costs over fixed time horizon. Prosumers have individual demands, which can vary
ay-by-day, and which they can satisfy by either consuming selfgenerating electrical energy locally (e.g., from operating PV panels) or from acquiring energy from other prosumers in the same microgrid.
Our models take into account two key aspects motivated by real-life scenarios: first, we consider a daily volatility of prices for buying and selling energy, and second, the possibility to store the selfgenerated
energy in a battery of finite capacity to be either self-consumed or sold to other prosumers in the future. We provide a thorough complexity analysis, as well as efficient algorithms, so that prosumers can minimize their overall cost over the entire time horizon. As a byproduct, we also solve a new temporal version of the classical KNAPSACK problem, which may be of independent interest. We complement our theoretical findings by extensive experimental evaluations on realistic data sets.
ay-by-day, and which they can satisfy by either consuming selfgenerating electrical energy locally (e.g., from operating PV panels) or from acquiring energy from other prosumers in the same microgrid.
Our models take into account two key aspects motivated by real-life scenarios: first, we consider a daily volatility of prices for buying and selling energy, and second, the possibility to store the selfgenerated
energy in a battery of finite capacity to be either self-consumed or sold to other prosumers in the future. We provide a thorough complexity analysis, as well as efficient algorithms, so that prosumers can minimize their overall cost over the entire time horizon. As a byproduct, we also solve a new temporal version of the classical KNAPSACK problem, which may be of independent interest. We complement our theoretical findings by extensive experimental evaluations on realistic data sets.
Subjects
Constraint Satisfaction and Optimization
Planning and Scheduling
Planning and Scheduling
Planning and Scheduling
DDC Class
510: Mathematics
Publication version
publishedVersion
Loading...
Name
ijcai.pdf
Size
323.62 KB
Format
Adobe PDF