Power Generation Expansion Optimization Model Considering Multi-Scenario Electricity Demand Constraints: A Case Study of Zhejiang Province, China

Peng Wang, Chunsheng Wang, Yukun Hu, Liz Varga and Wei Wang
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Peng Wang: School of Information Science and Engineering, Central South University, Changsha 410083, China
Chunsheng Wang: School of Information Science and Engineering, Central South University, Changsha 410083, China
Yukun Hu: School of Management, Cranfield University, Bedford MK43 0AL, UK
Liz Varga: School of Management, Cranfield University, Bedford MK43 0AL, UK
Wei Wang: College of Electrical Engineering, Guangxi University, Nanning 530004, China

Energies, 2018, vol. 11, issue 6, 1-15

Abstract: 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.

Keywords: power generation expansion; scenario analysis; provincial-level; linear programming (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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