分布式层面供需资源协调的联合共享平台:有限理性下电碳流耦合

IF 10.1 1区 工程技术 Q1 ENERGY & FUELS
Xiaohui Yang , Longxi Li
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引用次数: 0

摘要

能源共享通过转移电力设备的使用权,协调供需双方的资源,有效解决了分布式能源大规模发展带来的供需不匹配问题,减少了资源浪费,促进了可再生能源的整合。然而,能源共享过程中的隐性碳流导致部分市场主体没有充分承担碳排放责任,影响了碳责任分配的公平性和合理性,从而限制了碳减排潜力。因此,需要在分布式层面建立合理有效的能源共享和碳责任分配框架,促进分布式能源系统的可持续发展。为此,本文基于安全、高效、灵活的共享经济商业模式,从能源共享和碳责任共享的角度构建共享平台。制定了一种动态定价策略,以协调供方分布式能源的管理和消费方需求响应资源的管理,耦合电力和碳流。利用前景理论和心理会计理论,建立了不确定条件下发电商和消费者的有限理性模型。考虑共享电价与共享电量之间的关系,结合粒子群优化算法的动态Kriging元模型解决了电力-碳市场中多利益相关者之间复杂的两层交互模型。模拟结果表明,该框架基于价值共同创造和碳责任分担原则,激励双方参与能源共享和碳责任分担,在经济、社会和环境可持续性和公平性方面表现出平衡的优势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A joint sharing-sharing platform for coordinating supply and demand resources at distributed level: Coupling electricity and carbon flows under bounded rationality
Energy sharing effectively addresses the supply–demand mismatches arising from the large-scale development of distributed energy by transferring usufruct of power equipment and coordinating resources on both the supply and demand sides, thereby reducing resource waste and facilitating renewable energy integration. However, implicit carbon flow during the energy-sharing process leads to certain market entities not fully assuming their carbon emissions responsibility, affecting the fairness and rationality of carbon responsibility allocation, thereby limiting the carbon reduction potential. Therefore, a rational and effective energy-sharing and carbon responsibility allocation framework is needed at the distributed level to promote the sustainable development of distributed energy systems. To this end, this paper establishes a sharing platform from the perspective of energy sharing and carbon responsibility sharing, based on a secure, efficient, and flexible sharing economy business model. A dynamic pricing strategy is formulated to coordinate the management of distributed energy resources on the supply side and demand response resources on the consumer side, coupling electricity and carbon flows. Using prospect theory and mental accounting, the bounded rationality of generators and consumers under uncertainty is modeled. Considering the relationship between shared tariffs and shared power, a dynamic Kriging metamodel combined with the particle swarm optimization algorithm solves the complex bilevel interaction model among multi-stakeholders in the electricity–carbon market. Simulation results indicate that the proposed framework, grounded in value co-creation and carbon responsibility sharing principles, incentivizes bilateral participation in energy sharing and carbon responsibility sharing, demonstrating balanced advantages in economic, social, and environmental sustainability, and fairness.
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来源期刊
Applied Energy
Applied Energy 工程技术-工程:化工
CiteScore
21.20
自引率
10.70%
发文量
1830
审稿时长
41 days
期刊介绍: Applied Energy serves as a platform for sharing innovations, research, development, and demonstrations in energy conversion, conservation, and sustainable energy systems. The journal covers topics such as optimal energy resource use, environmental pollutant mitigation, and energy process analysis. It welcomes original papers, review articles, technical notes, and letters to the editor. Authors are encouraged to submit manuscripts that bridge the gap between research, development, and implementation. The journal addresses a wide spectrum of topics, including fossil and renewable energy technologies, energy economics, and environmental impacts. Applied Energy also explores modeling and forecasting, conservation strategies, and the social and economic implications of energy policies, including climate change mitigation. It is complemented by the open-access journal Advances in Applied Energy.
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