Optimization of Electricity Resources on the Swedish Electricity Market
(2024)Department of Automatic Control
- Abstract
- The efficient allocation of flexible resources, such as grid batteries and wind parks, across multiple energy market auctions, is pivotal for maximizing socio-economic welfare, interpreted here as profits. This study explores various optimization methods, including Linear Programming, Integer Linear Programming, Robust Optimization with Linear Programming, and Robust Optimization with Integer Linear Programming, to determine their efficacy in different market conditions. Initially, under the assumption of perfect price information, Linear Programming and Integer Linear Programming methods were applied to optimize allocations for both wind parks and battery storage systems. The resulting optimization models, tested on two days with... (More)
- The efficient allocation of flexible resources, such as grid batteries and wind parks, across multiple energy market auctions, is pivotal for maximizing socio-economic welfare, interpreted here as profits. This study explores various optimization methods, including Linear Programming, Integer Linear Programming, Robust Optimization with Linear Programming, and Robust Optimization with Integer Linear Programming, to determine their efficacy in different market conditions. Initially, under the assumption of perfect price information, Linear Programming and Integer Linear Programming methods were applied to optimize allocations for both wind parks and battery storage systems. The resulting optimization models, tested on two days with different characteristics, demonstrated that optimized allocations across multiple markets significantly enhanced profitability, with the wind park achieving profits of approximately 80,000 EUR compared to 1,400 EUR when solely allocated to the spot market on 2024-04-10.
In conclusion, optimized allocation of flexible resources across multiple markets enhances profitability. LP emerges as a practical and efficient method for real-world applications, supporting traders in decisionmaking processes. However, integer linear programming and robust optimization methods present limitations under uncertainty and computational constraints, emphasizing the need for improved forecasting models and adaptive optimization strategies. Future research should focus on enhancing price forecasting accuracy and exploring alternative robust optimization approaches to further optimize profitability and efficiency in dynamic energy markets. (Less)
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/9177224
- author
- Åkesson, Noah Eric Johnny
- supervisor
-
- Johan Lindberg LU
- Max Nilsson LU
- Pontus Giselsson LU
- organization
- year
- 2024
- type
- H3 - Professional qualifications (4 Years - )
- subject
- report number
- TFRT-6261
- other publication id
- 0280-5316
- language
- English
- id
- 9177224
- date added to LUP
- 2025-02-04 15:04:44
- date last changed
- 2025-02-04 15:04:44
@misc{9177224,
abstract = {{The efficient allocation of flexible resources, such as grid batteries and wind parks, across multiple energy market auctions, is pivotal for maximizing socio-economic welfare, interpreted here as profits. This study explores various optimization methods, including Linear Programming, Integer Linear Programming, Robust Optimization with Linear Programming, and Robust Optimization with Integer Linear Programming, to determine their efficacy in different market conditions. Initially, under the assumption of perfect price information, Linear Programming and Integer Linear Programming methods were applied to optimize allocations for both wind parks and battery storage systems. The resulting optimization models, tested on two days with different characteristics, demonstrated that optimized allocations across multiple markets significantly enhanced profitability, with the wind park achieving profits of approximately 80,000 EUR compared to 1,400 EUR when solely allocated to the spot market on 2024-04-10.
In conclusion, optimized allocation of flexible resources across multiple markets enhances profitability. LP emerges as a practical and efficient method for real-world applications, supporting traders in decisionmaking processes. However, integer linear programming and robust optimization methods present limitations under uncertainty and computational constraints, emphasizing the need for improved forecasting models and adaptive optimization strategies. Future research should focus on enhancing price forecasting accuracy and exploring alternative robust optimization approaches to further optimize profitability and efficiency in dynamic energy markets.}},
author = {{Åkesson, Noah Eric Johnny}},
language = {{eng}},
note = {{Student Paper}},
title = {{Optimization of Electricity Resources on the Swedish Electricity Market}},
year = {{2024}},
}