TY - JOUR
T1 - Optimal coalition formation and maximum profit allocation for distributed energy resources in smart grids based on cooperative game theory
AU - Moafi, Milad
AU - Ardeshiri, Reza Rouhi
AU - Mudiyanselage, Manthila Wijesooriya
AU - Marzband, Mousa
AU - Abusorrah, Abdullah
AU - Rawa, Muhyaddin
AU - Guerrero, Josep M.
N1 - Funding Information:
The Authors acknowledge the support provided by King Abdullah City for Atomic and Renewable Energy (K.A.CARE) under K.A.CARE-King Abdulaziz University Collaboration Program. The authors are also thankful to Deanship of Scientific Research, King Abdulaziz University, Saudi Arabia for providing financial support vide grant number ( RG-37-135-42 ). In addition, this work was supported from DTE Network+ funded by EPSRC, UK grant reference EP/S032053/1 .
Publisher Copyright:
© 2022 Elsevier Ltd
PY - 2023/1
Y1 - 2023/1
N2 - Over the past decades, significant revolutions have occurred on electricity market to reduce the electricity cost and increase profits. In particular, the novel structures facilitate the electricity manufacturers to participate in the market and earn more profit by cooperate with other producers. This paper presents a three-level gameplay-based intelligent structure to evaluate individual and collaborative strategies of electricity manufacturers, considering network and physical constraints. At the Level I, the particle swarm optimization (PSO) algorithm is implemented to determine the optimum power of distributed energy resources (DERs) in the power grid, to maximize the profits. Further, the fuzzy logic algorithm is applied to model the intermittent nature of the renewable sources and implement load demand in the power grid. At the Level II, DERs are classified into two different fuzzy logic groups to secure the fairness between every participant. Finally, at the Level III, the DERs in each group are combined each other by cooperative game theory-based algorithms to increase the coalition profits. Thereafter, Shapley, Nucleolus, and merge/split methods are applied to allocate a fair profit allocation by coalition formation. Ultimately, the results verify the proposed model influence electric players to find effective collaborative strategies under different conditions and environments.
AB - Over the past decades, significant revolutions have occurred on electricity market to reduce the electricity cost and increase profits. In particular, the novel structures facilitate the electricity manufacturers to participate in the market and earn more profit by cooperate with other producers. This paper presents a three-level gameplay-based intelligent structure to evaluate individual and collaborative strategies of electricity manufacturers, considering network and physical constraints. At the Level I, the particle swarm optimization (PSO) algorithm is implemented to determine the optimum power of distributed energy resources (DERs) in the power grid, to maximize the profits. Further, the fuzzy logic algorithm is applied to model the intermittent nature of the renewable sources and implement load demand in the power grid. At the Level II, DERs are classified into two different fuzzy logic groups to secure the fairness between every participant. Finally, at the Level III, the DERs in each group are combined each other by cooperative game theory-based algorithms to increase the coalition profits. Thereafter, Shapley, Nucleolus, and merge/split methods are applied to allocate a fair profit allocation by coalition formation. Ultimately, the results verify the proposed model influence electric players to find effective collaborative strategies under different conditions and environments.
KW - Coalition formation and competition
KW - Cooperative game theory
KW - Electricity energy market
KW - Merge and split
KW - Nucleolus
KW - Profit allocation
KW - Shapley value
KW - Smart grid
UR - http://www.scopus.com/inward/record.url?scp=85135962628&partnerID=8YFLogxK
U2 - 10.1016/j.ijepes.2022.108492
DO - 10.1016/j.ijepes.2022.108492
M3 - Journal article
AN - SCOPUS:85135962628
SN - 0142-0615
VL - 144
JO - International Journal of Electrical Power and Energy Systems
JF - International Journal of Electrical Power and Energy Systems
M1 - 108492
ER -