Dynamic Optimization of Carbon Reduction Pathways in Coastal Metropolises Considering Hidden Influence of Decarbonization on Energy Demand

doi:10.16183/j.cnki.jsjtu.2022.437

Abstract

Abstract:

Setting a reasonable carbon reduction plan in coastal metropolises is the key part to reach the global carbon target. Carbon reduction will change urban climate and influence energy demand, both of which affect the optimization results of carbon reduction pathways. Current generation expansion optimization models consider direct abatement contribution and solve most problems of planning for long-term carbon emission reduction in energy systems. However, the construction of new type power systems also indirectly impacts carbon emissions by changing microclimate factors such as heat island intensity. By combining generation expansion with carbon emission prediction model, the proposed approach in this paper considers the hidden mechanism of carbon and heat emission change on air-conditioning loads and dynamically optimizes the carbon reduction pathways in coastal metropolises. Taking Pudong Area in Shanghai as an example, the estimated cost of carbon reduction is reduced by the proposed approach. Some suggestions for the carbon reduction in coastal metropolises are made according to the simulation results.

Key words: dynamic optimization, carbon emission reduction, power system planning, microclimate, load forecasting

CLC Number:

TM715
X321

XIAO Yinjing, ZHANG Di, WEI Juan, GE Rui, CHEN Dawei, YANG Guixing, YE Zhiliang. Dynamic Optimization of Carbon Reduction Pathways in Coastal Metropolises Considering Hidden Influence of Decarbonization on Energy Demand[J]. Journal of Shanghai Jiao Tong University, 2024, 58(5): 600-609.

Figures/Tables 5

References 29

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