A method for power suppliers’ optimal cooperative bidding strategies considering network losses

Sun, Guanghui; Wang, Xiaowei; Yang, Libo; Ma, Bin; He, Lin; Zhang, Rongquan

doi:10.1016/j.gloei.2020.10.010

Cited by 4 publications

(2 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The identified publications for electricity trading illustrate the range of existing nature-inspired algorithms. [46], [52], [10], [51], and [49] provide a NII approach to derive the best bidding strategy as an electricity supplier on a day-ahead market. [52] and [10] provide a Genetic Algorithm (GA).…”

Section: Overview Of Algorithmic Approaches For Electricity and Flexibility Tradingmentioning

confidence: 99%

See 1 more Smart Citation

How to trade electricity flexibility using artificial intelligence - An integrated algorithmic framework

Hanny¹,

Körner²,

Leinauer³

et al. 2022

Proceedings of the Annual Hawaii International Conference on System Sciences

View full text Add to dashboard Cite

In course of the energy transition, the growing share of Renewable Energy Sources (RES) makes electricity generation more decentralized and intermittent. This increases the relevance of exploiting flexibility potentials that help balancing intermittent RES supply and demand and, thus, contribute to overall system resilience. Digital technologies, in the form of automated trading algorithms, may considerably contribute to flexibility exploitation, as they enable faster and more accurate market interactions. In this paper, we develop an integrated algorithmic framework that finds an optimal trading strategy for flexibility on multiple markets. Hence, our work supports the trading of flexibility in a multi-market environment that results in enhanced market integration and harmonization of economically traded and physically delivered electricity, which finally promotes resilience in highly complex electricity systems.

show abstract

Section: Overview Of Algorithmic Approaches For Electricity and Flexibility Tradingmentioning

confidence: 99%

“…[49] combines a GA with a particle swarm algorithm. [46] further applies a GA based on a hybrid particle swarm optimization and an improved firefly algorithm. [51] evaluates various NII where a differential evolution and vortex search algorithm perform best.…”

Section: Overview Of Algorithmic Approaches For Electricity and Flexibility Tradingmentioning

confidence: 99%

How to trade electricity flexibility using artificial intelligence - An integrated algorithmic framework

Hanny¹,

Körner²,

Leinauer³

et al. 2022

Proceedings of the Annual Hawaii International Conference on System Sciences

View full text Add to dashboard Cite

show abstract

A comprehensive review of research works based on evolutionary game theory for sustainable energy development

et al. 2022

View full text Add to dashboard Cite

Multi-strategy-based adaptive sine cosine algorithm for engineering optimization problems

Wei,

Zhang,

2024

Expert Systems with Applications

View full text Add to dashboard Cite

A method for power suppliers’ optimal cooperative bidding strategies considering network losses

Cited by 4 publications

References 27 publications

How to trade electricity flexibility using artificial intelligence - An integrated algorithmic framework

How to trade electricity flexibility using artificial intelligence - An integrated algorithmic framework

A comprehensive review of research works based on evolutionary game theory for sustainable energy development

Multi-strategy-based adaptive sine cosine algorithm for engineering optimization problems

Contact Info

Product

Resources

About