ArticlePloS one2025
Day-ahead optimal dispatch considering demand response compensation and carbon trading under uncertain environment.
Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
4 authors.
Funding
Abstract
To fully explore the regulation resources on both sides of the source and load under uncertain environment and collaboratively achieve the energy saving and emission reduction goals, a low-carbon economic optimization dispatch model combining demand response and carbon trading mechanism is proposed in this paper. Firstly, the economic principle of demand response (DR) is analyzed, as well as the demand response compensation model is constructed for shiftable loads and curtailable loads respectively. Second, we describe the source-load synergistic low-carbon effect. The source side further reduces carbon emissions by establishing a reward-punishment laddered carbon trading model. Accordingly, the optimization model is constructed with the objective of minimizing the sum of DR compensation cost, carbon trading cost and system operation cost. The triangular fuzzy method is used to deal with the uncertainty problem of new energy and load forecasting. Finally, the economic and low-carbon nature of this proposed model is verified by simulation and example analysis.
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