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黄河流域水资源-能源-粮食的协同优化

彭少明Shaoming Peng郑小康Zheng Xiaokang王煜Wang Yu蒋桂芹Guiqin Jiang

2017DOAJ (DOAJ: Directory of Open Access Journals)Engineering被引 149开放获取

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摘要

As an important energy and major grain producing area in China, the Yellow River basin has had a shortage of water resources, becoming a key factor in the restriction of energy and food development. And the system risk of water, energy and food has been escalated. An overall analysis framework model of water-energy-food based on the synergetic theory was established in order to optimize the relationship between water resources, energy, and food. Further, a total partition structure model was built, also known as the water-energy-food collaborative optimization model with an inter-feedback function. The support, restriction, and interactive bond mechanism and intelligent multi-factor balancing algorithm were also studied. Finally, the integration of the collaborative optimization distribution scheme and strategy for food production, energy, and water resource utilization in the Yellow River basin was demonstrated. Results show that, by collaborative optimization and comprehensive allocation of water resources, energy, and food, the average annual water supply is expected to be 53.560 billion m3, increased by 2.398 billion m3. Both the food production distribution and energy production structure and scale are to be optimized; with an increase of 12%, per capita yield of food will reach 416 kg. Coal mining, oil mining, and total thermal power installed capacity will increase by 2.86 times, 4.08 times, and 0.80 times, respectively. According to the results, a guaranteed degree of water resources for energy development and food production security can be significantly improved, with domestic and ecological water demand given the highest priority in the model. Meanwhile, increased food and energy production can be realized, as well.

引用本文(GB/T 7714)

彭少明, Shaoming Peng, 郑小康, 等. 黄河流域水资源-能源-粮食的协同优化[J]. DOAJ (DOAJ: Directory of Open Access Journals), 2017.

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DOI:https://doi.org/10.14042/j.cnki.32.1309.2017.05.005

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