Assessing economic and environmental performance of multi-energy sharing communities considering different carbon emission responsibilities under carbon tax policy

被引:40
作者
Li, Longxi [1 ,2 ]
Zhang, Sen [1 ]
Cao, Xilin [1 ]
Zhang, Yuqing [1 ]
机构
[1] China Univ Geosci, Sch Econ & Management, Wuhan 430074, Peoples R China
[2] China Univ Geosci, Ctr Energy & Environm Management & Decis Making, Wuhan 430074, Peoples R China
基金
中国国家自然科学基金;
关键词
Multi-energy system; P2P energy trading; Carbon accounting method; Low-carbon community; Sensitivity analysis; PEER-TO-PEER; MARKETS;
D O I
10.1016/j.jclepro.2021.129466
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Excessive carbon emissions pose a significant threat to the sustainable development of society and have an irreversible impact on climate change. Local energy trading in low-carbon communities and the implementation of carbon tax policy are considered effective means to improve energy efficiency and reduce carbon emissions. In this regard, this paper proposes a multi-energy sharing mechanism based on Nash bargaining theory among communities with distributed energy systems. The impact of heterogeneous carbon emission responsibilities, including production responsibility, consumption responsibility, and shared responsibility, on the economic and environmental benefits of shared communities is explored under a carbon tax policy. The distributed solution of the multi-energy sharing problem is carried out through the alternating direction method of multipliers algorithm, which protects the privacy of stakeholders and maximizes social welfare and the fair allocation of shared benefits. Additionally, sensitivity analyses of electric and thermal coupling loads, carbon emission accounting coefficients, and carbon taxes, are conducted to provide further insights into the optimal schedule of distributed energy systems and the economic and environmental performance of community clusters. The method proposed in this paper can effectively address the problem of multi-energy sharing in the interconnected communities and reasonably determine the carbon emission responsibility of each trading entity under the carbon tax policy. Numerical results show that, compared with the traditional no energy sharing scenario, the proposed sharing mechanism can achieve a maximum of 5.91% cost savings and 9.25% carbon emission reduction. In addition, under the production responsibility scheme, the communities show the best economic performance, while under the consumption responsibility scheme, the communities achieve excellent environmental benefit.
引用
收藏
页数:18
相关论文
共 45 条
[11]   Carbon tax and energy programs for buildings: Rivals or allies? [J].
Freyre, Alisa ;
Klinke, Sandra ;
Patel, Martin K. .
ENERGY POLICY, 2020, 139
[12]   Beyond Carbon Pricing: Tax Reform is Climate Policy [J].
Green, Jessica F. .
GLOBAL POLICY, 2021, 12 (03) :372-379
[13]   A two-stage optimization approach on the decisions for prosumers and consumers within a community in the Peer-to-peer energy sharing trading [J].
Jiang, Aihua ;
Yuan, Huihong ;
Li, Delong .
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2021, 125
[14]   Fair P2P energy trading between residential and commercial multi-energy systems enabling integrated demand-side management [J].
Jing, Rui ;
Xie, Mei Na ;
Wang, Feng Xiang ;
Chen, Long Xiang .
APPLIED ENERGY, 2020, 262
[15]  
Kander A, 2015, NAT CLIM CHANGE, V5, P431, DOI [10.1038/NCLIMATE2555, 10.1038/nclimate2555]
[16]   Peer-to-peer multi-energy sharing for home microgrids: An integration of data-driven and model-driven approaches [J].
Li, Longxi ;
Zhang, Sen .
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2021, 133
[17]   Optimal management of multi-stakeholder distributed energy systems in low-carbon communities considering demand response resources and carbon tax [J].
Li, Longxi ;
Yu, Shiwei .
SUSTAINABLE CITIES AND SOCIETY, 2020, 61
[18]   A decentralized peer-to-peer control scheme for heating and cooling trading in distributed energy systems [J].
Li, Shiyao ;
Pan, Yiqun ;
Xu, Peng ;
Zhang, Nan .
JOURNAL OF CLEANER PRODUCTION, 2021, 285
[19]   Energy-Sharing Model With Price-Based Demand Response for Microgrids of Peer-to-Peer Prosumers [J].
Liu, Nian ;
Yu, Xinghuo ;
Wang, Cheng ;
Li, Chaojie ;
Ma, Li ;
Lei, Jinyong .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2017, 32 (05) :3569-3583
[20]   China's low-carbon governance at community level: A case study in Min'an community, Beijing [J].
Liu, Tianle ;
Wang, Yufei ;
Li, Huimin ;
Qi, Ye .
JOURNAL OF CLEANER PRODUCTION, 2021, 311