How to Develop Renewable Power in China? A Cost-Effective Perspective

被引:30
作者
Cong, Rong-Gang [1 ,2 ]
Shen, Shaochuan [3 ]
机构
[1] North China Elect Power Univ, Sch Econ & Management, Beijing 102206, Peoples R China
[2] Lund Univ, Ctr Environm & Climate Res CEC, S-22362 Lund, Sweden
[3] Zhejiang Univ Technol, Coll Chem Engn & Mat Sci, State Key Lab Breeding Base Green Chem Synth Tech, Hangzhou 310014, Zhejiang, Peoples R China
来源
SCIENTIFIC WORLD JOURNAL | 2014年
基金
瑞典研究理事会;
关键词
ENERGY-SOURCES; FUTURE-TRENDS; WIND POWER; TECHNOLOGY; DIFFUSION; MODEL; ELECTRICITY; EXPERIENCE; POLICIES; ETHANOL;
D O I
10.1155/2014/946932
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
To address the problems of climate change and energy security, Chinese government strived to develop renewable power as an important alternative of conventional electricity. In this paper, the learning curve model is employed to describe the decreasing unit investment cost due to accumulated installed capacity; the technology diffusion model is used to analyze the potential of renewable power. Combined with the investment cost, the technology potential, and scenario analysis of China social development in the future, we develop the Renewable Power Optimization Model (RPOM) to analyze the optimal development paths of three sources of renewable power from 2009 to 2020 in a cost-effective way. Results show that (1) the optimal accumulated installed capacities of wind power, solar power, and biomass power will reach 169000, 20000, and 30000 MW in 2020; (2) the developments of renewable power show the intermittent feature; (3) the unit investment costs of wind power, solar power, and biomass power will be 4500, 11500, and 5700 Yuan/KW in 2020; (4) the discounting effect dominates the learning curve effect for solar and biomass powers; (5) the rise of on-grid ratio of renewable power will first promote the development of wind power and then solar power and biomass power.
引用
收藏
页数:7
相关论文
共 36 条
[1]  
Abanades A., 2012, Agronomy Research, V10, P11
[2]   Strategies and policies from promoting the use of renewable energy resource in the UAE [J].
Al-Amir, Jawaher ;
Abu-Hijleh, Bassam .
RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2013, 26 :660-667
[3]   IRES - A PROGRAM TO DESIGN INTEGRATED RENEWABLE ENERGY-SYSTEMS [J].
ASHENAYI, K ;
RAMAKUMAR, R .
ENERGY, 1990, 15 (12) :1143-1152
[4]   NEW PRODUCT GROWTH FOR MODEL CONSUMER DURABLES [J].
BASS, FM .
MANAGEMENT SCIENCE SERIES A-THEORY, 1969, 15 (05) :215-227
[5]   Policies and market factors driving wind power development in the United States [J].
Bird, L ;
Bolinger, M ;
Gagliano, T ;
Wiser, R ;
Brown, M ;
Parsons, B .
ENERGY POLICY, 2005, 33 (11) :1397-1407
[6]   State renewable energy electricity policies: An empirical evaluation of effectiveness [J].
Carley, Sanya .
ENERGY POLICY, 2009, 37 (08) :3071-3081
[7]   Renewable energy policy and electricity market reforms in China [J].
Cherni, Judith A. ;
Kentish, Joanna .
ENERGY POLICY, 2007, 35 (07) :3616-3629
[8]   An optimization model for renewable energy generation and its application in China: A perspective of maximum utilization [J].
Cong, Rong-Gang .
RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2013, 17 :94-103
[9]   Potential impact of (CET) carbon emissions trading on China's power sector: A perspective from different allowance allocation options [J].
Cong, Rong-Gang ;
Wei, Yi-Ming .
ENERGY, 2010, 35 (09) :3921-3931
[10]   A regional energy planning methodology including renewable energy sources and environmental constraints [J].
Cormio, C ;
Dicorato, M ;
Minoia, A ;
Trovato, M .
RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2003, 7 (02) :99-130