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Frontiers in Energy >> 2020, Volume 14, Issue 2 doi: 10.1007/s11708-020-0660-9

Multi-objective optimal allocation strategy for the energy internet in Huangpu District, Guangzhou, China

. Guangzhou Institute of Energy Conversion, Chinese Academy of Sciences, Guangzhou 510640, China; Key Laboratory of Renewable Energy, Chinese Academy of Sciences, Guangzhou 510640, China; University of Chinese Academy of Sciences, Beijing 100049, China; Energy Development Research Institute, CSG, Guangzhou 510663, China.. Guangzhou Institute of Energy Conversion, Chinese Academy of Sciences, Guangzhou 510640, China; Key Laboratory of Renewable Energy, Chinese Academy of Sciences, Guangzhou 510640, China; University of Chinese Academy of Sciences, Beijing 100049, China.. Guangzhou Institute of Energy Conversion, Chinese Academy of Sciences, Guangzhou 510640, China; Key Laboratory of Renewable Energy, Chinese Academy of Sciences, Guangzhou 510640, China; Nano Science and Technology Institute, University of Science and Technology of China, Suzhou 215123, China

Accepted: 2020-03-26 Available online: 2020-03-26

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Abstract

To improve the overall efficiency of the energy system, the basic structure for the energy internet of coordination and optimization of “generation-grid-load-storage” of Huangpu District, Guangzhou, China is designed, while the arrangement for the output of centralized and distributed energy module and energy storage are proposed. Taking economic benefit maximization, environmental benefit maximization and energy efficiency maximization as sub-objectives, the mathematical model of multi-objective optimal allocation and operation strategy of the energy internet is established considering supply-demand balance constraints, equipment characteristic constraints, operation mode constraints, and energy conditions constraints. The calculation results show that without considering the outsourced electricity, the balanced strategy, the economic development strategy, the environmental protection strategy, and the energy efficiency strategy are obtained by calculation, which are all superior to the traditional energy supply strategy. Moreover, considering the outsourced electricity, the proportion of outsourced electricity to total electricity is 19.8%, which is the system optimization of the energy internet under certain power demand. Compared with other strategies without outsourced electricity, the outsourced electricity strategy can have a certain emission reduction effect, but at the same time reduce the economic benefit. Furthermore, the huge difference in demand for thermal and cooling load between industrial and commercial areas results in the installed capacity of gas distributed energy stations in industrial areas being nearly twice as large as that in commercial areas. The distributed photovoltaic power generation is allocated according to the proportion of the installed roof areas of photovoltaic power generation system in residential, industrial, and commercial areas.

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