Performance analysis of multi-energy sharing prosumers considering different load profiles

With the advancement of distributed energy systems, energy sharing has emerged as a crucial trading mechanism on the demand-side, enabling participants to share self-generated energy with their neighbors through contractual agreements. Nevertheless, a comprehensive analysis is needed to balance the benefits among energy prosumers, given their distinct characteristics. This paper proposes a multi-energy sharing framework with flexible demand-side management based on full cooperation. We evaluate the economic and environmental performance of sharing participants, considering the impacts of different operation modes and diverse demand profiles. Cooperative game theory is employed to maximize the social welfare of all participants, with the different allocation schemes are used to distribute the cooperative surplus among stakeholders. The fairness of these schemes is assessed to ensure the feasibility and equity of the proposed framework. The results indicate that the centralized multi-energy sharing framework yields win-win outcomes for both individual and collective interests. Specifically, the total cost and carbon dioxide emissions of prosumers in the shared scenario are reduced by 13% and 16%, respectively, compared to individual operation scenarios. Moreover, thermal energy management is critically important for energy sharing. Furthermore, varying combinations of building types significantly affect cost savings and emission reductions, influencing energy sharing patterns and quantities.

Authors

Institutions

Publication Details

Journal
Frontiers in Energy Research
Published
2024-11-22
DOI
https://doi.org/10.3389/fenrg.2024.1470769
Citations
1
Primary Topic
Smart Grid Energy Management
Type
article
Field-Weighted Citation Impact
0.21

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Performance analysis of multi-energy sharing prosumers considering different load profiles

Xi Liu, Shangheng Yao, Longxi Li, Gengsheng He et al.
1 citations
Frontiers in Energy Research
Smart Grid Energy Management
0.21
article

Performance analysis of multi-energy sharing prosumers considering different load profiles

Xi Liu, Shangheng Yao, Longxi Li, Gengsheng He, Minwei Liu, Peng Wang, Guori Huang, Qin Wang, Jincan Zeng
article en
1 citations

Abstract

With the advancement of distributed energy systems, energy sharing has emerged as a crucial trading mechanism on the demand-side, enabling participants to share self-generated energy with their neighbors through contractual agreements. Nevertheless, a comprehensive analysis is needed to balance the benefits among energy prosumers, given their distinct characteristics. This paper proposes a multi-energy sharing framework with flexible demand-side management based on full cooperation. We evaluate the economic and environmental performance of sharing participants, considering the impacts of different operation modes and diverse demand profiles. Cooperative game theory is employed to maximize the social welfare of all participants, with the different allocation schemes are used to distribute the cooperative surplus among stakeholders. The fairness of these schemes is assessed to ensure the feasibility and equity of the proposed framework. The results indicate that the centralized multi-energy sharing framework yields win-win outcomes for both individual and collective interests. Specifically, the total cost and carbon dioxide emissions of prosumers in the shared scenario are reduced by 13% and 16%, respectively, compared to individual operation scenarios. Moreover, thermal energy management is critically important for energy sharing. Furthermore, varying combinations of building types significantly affect cost savings and emission reductions, influencing energy sharing patterns and quantities.

Frontiers in Energy ResearchVol. 12
Chinese Academy of Sciences (CN), China University of Geosciences (CN), Guangzhou Institute of Energy Conversion (CN), China Southern Power Grid (China) (CN)
National Natural Science Foundation of China, China Southern Power Grid
Affordable and clean energy
Openalex Percentile: Top 46%
Smart Grid Energy Management
0.21
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.