Mobile Energy Storage Spatio-temporal Dispatch in Low-carbon Distribution Networks

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Publicado en:Journal of Physics: Conference Series vol. 3012, no. 1 (Jun 2025), p. 012024
Autor principal: Liu, Jinsong
Otros Autores: Huang, Bo, Liu, Shu, Chen, Fang, Xing Lei
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IOP Publishing
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022 |a 1742-6588 
022 |a 1742-6596 
024 7 |a 10.1088/1742-6596/3012/1/012024  |2 doi 
035 |a 3219321200 
045 2 |b d20250601  |b d20250630 
100 1 |a Liu, Jinsong  |u State Grid Shanghai Electric Power Research Institute , NO. 171 Handan Rd Shanghai, 200433, P.R.China 
245 1 |a Mobile Energy Storage Spatio-temporal Dispatch in Low-carbon Distribution Networks 
260 |b IOP Publishing  |c Jun 2025 
513 |a Journal Article 
520 3 |a As the proportion of new energy generation increases, optimizing the scheduling of energy storage devices to achieve decarbonized grid operation becomes a key issue. This paper proposes a low-carbon joint dispatch optimization model based on mobile energy storage. By constructing a spatio-temporal network model of the energy storage device, the charging and discharging behaviors, mobility characteristics, distribution network current constraints, and carbon emission factors of the energy storage device are considered comprehensively to optimize its operation. With the objective of minimizing the operating cost and carbon emission, the model adopts the mixed integer programming method to optimize the variables such as the movement path, charging and discharging power, and the state of the energy storage device. The model introduces the carbon emission factor of gas turbine and grid power purchase, combines the scheduling of energy storage devices with the low-carbon objective, and ensures the feasibility of the scheme through the tidal current constraints, SOC limits and path continuity constraints. The example results show that the proposed model effectively reduces the grid operation cost and carbon emission, while enhancing the capacity of renewable energy consumption, providing a new idea for the application of mobile energy storage in low-carbon grid scheduling. 
653 |a Carbon content 
653 |a Discharge 
653 |a Integer programming 
653 |a Scheduling 
653 |a Carbon 
653 |a Charging 
653 |a Emissions 
653 |a Energy storage 
653 |a Mixed integer 
653 |a Operating costs 
653 |a Energy consumption 
653 |a Constraints 
653 |a Tidal currents 
653 |a Gas turbines 
653 |a Optimization models 
700 1 |a Huang, Bo  |u University of Shanghai for Science and Technology , NO. 516 Jungong Rd, Shanghai, 200093, P.R.China 
700 1 |a Liu, Shu  |u State Grid Shanghai Electric Power Research Institute , NO. 171 Handan Rd Shanghai, 200433, P.R.China 
700 1 |a Chen, Fang  |u State Grid Shanghai Electric Power Research Institute , NO. 171 Handan Rd Shanghai, 200433, P.R.China 
700 1 |a Xing Lei  |u State Grid Shanghai Electric Power Research Institute , NO. 171 Handan Rd Shanghai, 200433, P.R.China 
773 0 |t Journal of Physics: Conference Series  |g vol. 3012, no. 1 (Jun 2025), p. 012024 
786 0 |d ProQuest  |t Advanced Technologies & Aerospace Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3219321200/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch 
856 4 0 |3 Full Text - PDF  |u https://www.proquest.com/docview/3219321200/fulltextPDF/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch