A multi-region optimization planning model for China's power sector. (1st January 2015)

• Record Type: Journal Article
• Authors: Cheng, Rui; Xu, Zhaofeng; Liu, Pei; Wang, Zhe; Li, Zheng; Jones, Ian
• Is Part Of: Applied energy. Volume 137(2015:Jan. 01)
• Page Start: 413
• Page End: 426
• Publication Date: 2015-01-01
• Subjects: Power sector -- Multi-region model -- Optimal planning -- Power transmission -- Cap-and-trade; Power (Mechanics) -- Periodicals; Energy conservation -- Periodicals; Energy conversion -- Periodicals; 621.042
• DOI: 10.1016/j.apenergy.2014.10.023
• Languages: English
• ISSNs: 0306-2619

Abstract

Highlights: A multi-region model is proposed to optimize the planning of China's power sector. Spatial distribution of resource, generation and demand is taken into account. Results of multi-region model and single-region model are compared and discussed. There is a saving of cost when using multi-region model. Regional generation mix and power transmission pathways are presented. Abstract: Demand for electricity in China kept accelerating in recent years; moreover, there exist serious mismatches among the distribution of power demand, energy resources, and power generation infrastructure across different regions in China, both of which indicate a necessity of a holistic and integrated approach to the strategic planning and development of its power industry. Material benefits could be realized by ensuring that the long term development of the power system is optimized by taking into consideration the different regional dynamics and characteristics. This paper proposes a multi-region optimization model that can deliver insights into how planning of the long term development of China's power sector could minimize the total cost of China's power sector by considering regional variations in availabilities of resources and inter-region power transmission line capacity. A case study considered how investment decisions to expand and alter the existing generation mix could be optimized across a timeframe from 2011 to 2050. By comparing results between single and multi-region optimizations, it was possible to show the likely impact on how investment decisions would differ when regional differences were taken into account. The multi-region optimization arguably better reflects and considers conditions and challenges in the real world.