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Science and Technology for Energy Transition
Article . 2025 . Peer-reviewed
License: CC BY
Data sources: Crossref
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Low-carbon and economic optimization of a source-load-storage system based on Stackelberg game and chance constraints

Authors: Xu Ke; Liu Chang; Xu Weiting; Zeng Jian; Shao Fan;

Low-carbon and economic optimization of a source-load-storage system based on Stackelberg game and chance constraints

Abstract

As energy demand grows and environmental pollution increases, low-carbon development has become a key focus in energy systems. To address the conflicting interests of the Source-Load-Storage System (SLSS), while also considering environmental benefits, this paper proposes an optimization model for the low-carbon economy of SLSS based on Stackelberg game theory and opportunity constraints. First, to ensure low carbon emissions and environmental protection, the carbon emissions of each entity in SLSS are constrained by a reward-penalty laddering carbon trading mechanism. Additionally, a demand response strategy is introduced on the user side, which accounts for both price and carbon compensation incentives. Next, considering the autonomy of the entities in SLSS, a decision-making model is developed based on the Stackelberg game. In this game-theoretic framework, the Power Management Operator acts as the leader, whereas the Power Generation Operator, Energy Storage Operator, and User serve as followers. This model also outlines the low-carbon interaction mechanisms among the various entities of SLSS. Finally, the model is solved using an improved particle swarm algorithm combined with the Gurobi optimization tool. Simulation results effectively validate the proposed model and method, showing that SLSS can rationally adjust its strategy within the low-carbon framework while balancing economic and environmental considerations.

Keywords

Technology, T, Science, Q, source-load-storage, the reward and penalty laddering-type carbon trading, chance constraint programming, low-carbon operation, stackelberg game

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Published in a Diamond OA journal