Abstract

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.

Highlights

  • According to the twelfth five-year plan about renewable energy development published by State Council of China in 2012, the proportion of nonfossil energy in primary energy consumption will be increased to 11.4% in 2015 and 15% in 2020 [1]

  • This paper tries to analyze the optimal development path of renewable power in a cost-effective way; that is, (1) the development of renewable power is subject to economic affordability, while the unit investment cost has the decreasing trend due to the increase of accumulated installed capacities; (2) the development of renewable power is constrained by relevant technology maturity; (3) the development of renewable power should meet the requirement of the plan for national economy

  • We find that the discounting effect dominates the learning curve effect for solar power and biomass power

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Summary

Introduction

According to the twelfth five-year plan about renewable energy development published by State Council of China in 2012, the proportion of nonfossil energy in primary energy consumption will be increased to 11.4% in 2015 and 15% in 2020 [1]. This paper tries to analyze the optimal development path of renewable power in a cost-effective way; that is, (1) the development of renewable power is subject to economic affordability (i.e., the investment in each year should be less than a certain proportion of GDP), while the unit investment cost has the decreasing trend due to the increase of accumulated installed capacities (the learning curve effect); (2) the development of renewable power is constrained by relevant technology maturity (the technology diffusion effect); (3) the development of renewable power should meet the requirement of the plan for national economy. Considering the factors above, we construct the Renewable Power Optimization Model (RPOM) to analyze the optimal development paths of three main sources of renewable power (wind power, solar power, and biomass power) in China in a cost-effective way. The main conclusion and possible future work are presented

Literature Review
Cost and Technology Maturity of Renewable Power
Model Results and Sensitivity Analysis
Conclusions
Full Text
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