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Optimal planning of local biomass-based integrated energy system considering anaerobic co-digestion

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  • Yang, Hanyu
  • Dou, Xun
  • Pan, Feng
  • Wu, Qiuwei
  • Li, Canbing
  • Zhou, Bin
  • Hao, Lili

Abstract

The biomass resource is very abundant in rural areas because of diverse agricultural activities, which enables the biogas to substitute the natural gas for the energy supply in where the natural gas network cannot extend. Thanks to the flexibility of biogas whose physical characteristic is similar to natural gas, it can not only power the biogas-based generators in the power distribution system but also meet the local biogas demand through a local biogas grid, finally formulating a distributed local biomass-based integrated energy system (IES). In such a system, proper anaerobic digestion (AD) plants planning is of great importance as the cost of transporting biomass feedstock is costly due to its high weight per unit of energy generated. Conventional AD plants planning is usually formulated as optimization problems of biomass supply chain whose focus is the planning of the transportation routes from biomass supply node to the AD plants, neglecting the downstream of the supply chain from the AD plants to the end-users. In this paper, a novel comprehensive optimization model formulated as a mixed-integer second-order-cone problem (MISOCP) is proposed to minimize the total investment and energy supply costs of the local biomass-based IES and to determine the networks of local biogas grid, to plan facilities, e.g., biogas-based generators and AD plants, and to optimize biomass transportation routes. with consideration of the network physical characteristics. Additionally, considering the anaerobic co-digestion (AcoD) technology has better performance on biogas yield compared to anaerobic mono-digestion (AmoD), a strategy is developed to choose mono-digestion or co-digestion system for AD plants as well. This model is demonstrated with a real-world test system, and an environmental and economic assessment for evaluating the profitability of each AD plant is presented. The planning results showed that AcoD plant is most cost-competitive when the food waste and animal manure are locally-sufficient.

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  • Yang, Hanyu & Dou, Xun & Pan, Feng & Wu, Qiuwei & Li, Canbing & Zhou, Bin & Hao, Lili, 2022. "Optimal planning of local biomass-based integrated energy system considering anaerobic co-digestion," Applied Energy, Elsevier, vol. 316(C).
    • Handle: RePEc:eee:appene:v:316:y:2022:i:c:s0306261922004652
    DOI: 10.1016/j.apenergy.2022.119075
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    1. Ju, Liwei & Lu, Xiaolong & Yang, Shenbo & Li, Gen & Fan, Wei & Pan, Yushu & Qiao, Huiting, 2022. "A multi-time scale dispatching optimal model for rural biomass waste energy conversion system-based micro-energy grid considering multi-energy demand response," Applied Energy, Elsevier, vol. 327(C).
    2. Yang, Shenbo & Fang, Jiangpeng & Zhang, Zheyu & Lv, ShuoShuo & Lin, Hongyu & Ju, Liwei, 2024. "Two-stage coordinated optimal dispatching model and benefit allocation strategy for rural new energy microgrid," Energy, Elsevier, vol. 292(C).
    3. Ronei de Almeida & Claudinei de Souza Guimarães, 2023. "A Short Review on Dye-Wastewater Valorization Using Up-Flow Anaerobic Sludge Blanket Reactors," Waste, MDPI, vol. 1(4), pages 1-17, November.
    4. Yunusoglu, Pinar & Ozsoydan, Fehmi Burcin & Bilgen, Bilge, 2024. "A machine learning-based two-stage approach for the location of undesirable facilities in the biomass-to-bioenergy supply chain," Applied Energy, Elsevier, vol. 362(C).
    5. Wang, Pengya & Wang, Jianxiao & Jin, Ruiyang & Li, Gengyin & Zhou, Ming & Xia, Qing, 2022. "Integrating biogas in regional energy systems to achieve near-zero carbon emissions," Applied Energy, Elsevier, vol. 322(C).
    6. Akter, Mst. Mahmoda & Surovy, Israt Zahan & Sultana, Nazmin & Faruk, Md. Omar & Gilroyed, Brandon H. & Tijing, Leonard & Arman, & Didar-ul-Alam, Md. & Shon, Ho Kyong & Nam, Sang Yong & Kabir, Mohammad, 2024. "Techno-economics and environmental sustainability of agricultural biomass-based energy potential," Applied Energy, Elsevier, vol. 359(C).

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