A Method for Carbon Emission Measurement and a Carbon Reduction Path of Urban Power Sector

doi:10.16183/j.cnki.jsjtu.2022.222

Abstract

Abstract:

To measure and reduce carbon emissions in the urban power sector, a method for measuring carbon emissions in the urban power sector and a carbon reduction path are proposed. First, a carbon emission measurement model for the urban power sector is established based on the data of local power generation and net inward power. Then, carbon reduction measures for the urban power sector are proposed from the generation side, grid side, load side and energy storage side. After that, an evaluation model for the effect of the carbon reduction measures is established. Finally, taking a typical city F in the Pearl River Delta as an example, the proposed carbon emission calculation model is used to calculate the carbon emissions of power sector of the city, and the effectiveness of carbon reduction in 2030 carbon peak scenario of the city is evaluated based on the carbon reduction measures. The results show that the proposed model can accurately measure the carbon emissions of the urban power sector, and by utilizing carbon reduction measures, carbon emissions of the city can be reduced by at least 10.6 million tons in 2030.

Key words: carbon emission, power sector, carbon emission reduction, carbon peak

CLC Number:

TM61

HU Zhuangli, LUO Yichu, CAI Hang. A Method for Carbon Emission Measurement and a Carbon Reduction Path of Urban Power Sector[J]. Journal of Shanghai Jiao Tong University, 2024, 58(1): 82-90.

Figures/Tables 8

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年份	能源供应侧 ×10^-7/t	能源消费侧×10^-7/t					测算误差/%
年份	能源供应侧 ×10^-7/t	工业领域	建筑领域	交通领域	农业农村领域	合计	测算误差/%
2010	4.999	3.614	0.631	0.545	0.047	4.836	3.26
2011	5.246	3.745	0.734	0.534	0.056	5.070	3.36
2012	5.589	3.430	0.776	0.538	0.069	4.813	13.89
2013	5.635	3.419	0.790	0.552	0.063	4.824	14.40
2014	5.371	3.218	0.753	0.579	0.061	4.610	14.16
2015	5.191	3.027	0.794	0.585	0.065	4.472	13.85
2016	5.026	2.993	0.817	0.592	0.062	4.463	11.19
2017	5.338	3.187	0.940	0.622	0.142	4.890	8.40
2018	5.347	3.106	0.992	0.616	0.146	4.860	9.10
2019	5.243	2.931	1.021	0.619	0.131	4.702	10.33
2020	5.062	2.808	1.021	0.561	0.125	4.515	10.81

年份	煤品		油品		天然气		净调入电力
年份	碳排放量×10^-7/t	占比/%	碳排放量×10^-7/t	占比/%	碳排放量×10^-7/t	占比/%	碳排放量×10^-7/t	占比/%
2010	2.345	46.9	0.585	11.7	0.115	2.3	1.954	39.1
2011	2.303	43.9	0.751	14.3	0.177	3.4	2.015	38.4
2012	2.861	51.2	0.717	12.8	0.201	3.6	1.810	32.4
2013	2.583	45.8	0.980	17.4	0.204	3.6	1.867	33.1
2014	2.414	45.0	0.778	14.5	0.273	5.1	1.905	35.5
2015	2.120	40.8	0.801	15.4	0.248	4.8	2.022	39.0
2016	1.805	35.9	0.862	17.1	0.340	6.8	2.020	40.2
2017	1.951	36.5	0.786	14.7	0.347	6.5	2.255	42.2
2018	2.103	39.3	0.517	9.7	0.456	8.5	2.271	42.5
2019	2.063	39.3	0.553	10.6	0.468	8.9	2.159	41.2
2020	1.983	39.2	0.474	9.4	0.447	8.8	2.158	42.6

年份	发、用电消费量×10^-10/(kW·h)			净调入电量碳排放 ×10^-7/t
年份	全社会用电量	净调入电量	本地区发电量	净调入电量碳排放 ×10^-7/t
2010	4.657	3.461	1.196	1.954
2011	4.879	3.433	1.446	2.015
2012	5.070	3.332	1.737	1.810
2013	5.271	3.498	1.773	1.867
2014	5.641	4.063	1.578	1.905
2015	5.878	4.479	1.399	2.022
2016	6.208	4.764	1.445	2.020
2017	6.738	5.164	1.575	2.255
2018	6.909	5.353	1.556	2.271
2019	7.027	5.466	1.561	2.159
2020	7.103	5.568	1.535	2.158

年份	全社会用电量× 10^-10/ (kW·h)	外区净调入电量× 10^-10/ (kW·h)	本地区电源发电量× 10^-10/(kW·h)
年份	全社会用电量× 10^-10/ (kW·h)	外区净调入电量× 10^-10/ (kW·h)	煤电	气电	非化石能源电力
2010	4.657	3.461	1.196	0.000	0.000
2011	4.879	3.433	1.438	0.000	0.008
2012	5.070	3.332	1.628	0.054	0.056
2013	5.271	3.498	1.630	0.053	0.090
2014	5.641	4.063	1.212	0.050	0.315
2015	5.878	4.479	1.028	0.001	0.370
2016	6.208	4.764	0.945	0.046	0.453
2017	6.738	5.164	1.095	0.056	0.424
2018	6.909	5.353	1.055	0.069	0.432
2019	7.027	5.466	0.994	0.147	0.420
2020	7.103	5.568	1.134	0.200	0.201