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A task matching model of photovoltaic storage system under the energy blockchain environment - based on GA-CLOUD-GS algorithm.

Authors :
Liu, Jicheng
Lu, Yunyuan
Source :
Energy. Nov2023, Vol. 283, pN.PAG-N.PAG. 1p.
Publication Year :
2023

Abstract

Photovoltaic storage system (PVSS) has been spawned with the combined application of photovoltaic (PV), energy storage (ES) and energy blockchain (EB), which has also made important contributions to the energy structure adjustment, energy transaction security and ecological environment protection. The establishment of a reasonable task matching mechanism can further improve the operation efficiency and quality of the system under the EB environment, and this paper consequently constructs a task matching model of PVSS based on GA-CLOUD-GS algorithm. Firstly, the decision-making committee is set up and the index system is determined for the to-be-matched task. Secondly, the Genetic Algorithm (GA) comprehensive weighting method is introduced to integrate the subjective and objective weights to achieve the weight optimization. Thirdly, the cloud model is used to obtain the preference order and priority order of the to-be-matched subjects. Fourthly, the Gale-Shapley (GS) algorithm is used to obtain the task matching results. Finally, the operability, the stability and the effectiveness of the model are separately verified through numerical simulation, sensitivity analysis and comparative analysis. Corresponding suggestions for the task matching of PVSS in the EB environment are also put forward according to the research content. • The necessity, superiority, and application scenarios of collaborative development between PVSS and EB are clarified, and the importance of research on task matching mechanism is identified. • A task matching mechanism model based on the GA-CLOUD-GS algorithm is established, the feasibility, stability, and effectiveness of the established model were verified. • Relevant suggestions are provided for the development of PVSS in the EB environment. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
03605442
Volume :
283
Database :
Academic Search Index
Journal :
Energy
Publication Type :
Academic Journal
Accession number :
172977238
Full Text :
https://doi.org/10.1016/j.energy.2023.129066