E3S Web Conf.
Volume 239, 2021International Conference on Renewable Energy (ICREN 2020)
|Number of page(s)||11|
|Published online||10 February 2021|
Optimisation for Coalitions Formation Considering the Fairness in Flexibility Market Participation
GECAD Research Group, Polytechnic of Porto (ISEP/IPP), R. Dr. António Bernardino de Almeida 431, 4200-072 Porto, Portugal
2 Polytechnic of Porto (ISEP/IPP), R. Dr. António Bernardino de Almeida 431, 4200-072 Porto, Portugal
3 BISITE Research Group, University of Salamanca (US), Calle Espejo, 12, 37007 Salamanca, Spain
* Corresponding author: firstname.lastname@example.org
This paper proposes a coalitional game-theoretical model for consumers’ flexibility coalition formation, supported by an optimization model based on differential evolution. Traditionally, the participation in conventional electricity markets used to be limited to large producers and consumers. The final end-users contract their energy supply with retailers, since due to the smaller quantity available for trading, they cannot participate in electricity market transactions. Nowadays, the growing concept of local electricity market brings many advantages to the end-users. The flexibility negotiation considering local areas is an important procedure for network operators and it is incorporating a local electricity market opportunity. A coalition formation model to facilitate small players participation in the flexibility market proposed by the network operator is addressed in this work. The inclusion of Shapley value in the proposed model enables finding the best coalition structures considering the fairness of the coalitions in addition to the potential income achieved by the consumers when selling their flexibility. An optimization model based on differential evolution is also proposed as the way to find the optimal coalition structures based on the multi-criteria specifications.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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