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Power generation expansion optimization model considering multi-scenario electricity demand constraints: a case study of Zhejiang Province, China

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dc.creator Wang, Peng
dc.creator Wang, Chunsheng
dc.creator Hu, Yukun
dc.creator Varga, Liz
dc.creator Wang, Wei
dc.date 2018-07-02T13:26:15Z
dc.date 2018-07-02T13:26:15Z
dc.date 2018-06-08
dc.date.accessioned 2022-05-25T16:36:44Z
dc.date.available 2022-05-25T16:36:44Z
dc.identifier Peng Wang, Chunsheng Wang, Yukun Hu, et al., Power generation expansion optimization model considering multi-scenario electricity demand constraints: a case study of Zhejiang Province, China. Energies, Volume 11, Issue 6, article number 1498
dc.identifier 1996-1073
dc.identifier https://doi.org/10.3390/en11061498
dc.identifier http://dspace.lib.cranfield.ac.uk/handle/1826/13295
dc.identifier.uri http://localhost:8080/xmlui/handle/CUHPOERS/182154
dc.description Reasonable and effective power planning contributes a lot to energy efficiency improvement, as well as the formulation of future economic and energy policies for a region. Since only a few provinces in China have nuclear power plants so far, nuclear power plants were not considered in many provincial-level power planning models. As an extremely important source of power generation in the future, the role of nuclear power plants can never be overlooked. In this paper, a comprehensive and detailed optimization model of provincial-level power generation expansion considering biomass and nuclear power plants is established from the perspective of electricity demand uncertainty. This model has been successfully applied to the case study of Zhejiang Province. The findings suggest that the nuclear power plants will contribute 9.56% of the total installed capacity, and it will become the second stable electricity source. The lowest total discounted cost is 1033.28 billion RMB and the fuel cost accounts for a large part of the total cost (about 69%). Different key performance indicators (KPI) differentiate electricity demand in scenarios that are used to test the model. Low electricity demand in the development mode of the comprehensive adjustment scenario (COML) produces the optimal power development path, as it provides the lowest discounted cost.
dc.language en
dc.publisher MDPI
dc.rights Attribution 4.0 International
dc.rights http://creativecommons.org/licenses/by/4.0/
dc.subject power generation expansion
dc.subject scenario analysis
dc.subject provincial-level
dc.subject linear programming
dc.title Power generation expansion optimization model considering multi-scenario electricity demand constraints: a case study of Zhejiang Province, China
dc.type Article


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