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     Research Journal of Applied Sciences, Engineering and Technology


The Power Generation Capacity Investment Model Basing on the Newton KKT Interior-point Method under the Market Environment of Low Carbon

Zeng Ming, Ma Shaoyin, Ma Mingjuan, Xue Song and Shi Hui
School of Economics and Management, North China Electric Power University, Beijing 102206, China
Research Journal of Applied Sciences, Engineering and Technology  2013  21:3993-4002
http://dx.doi.org/10.19026/rjaset.6.3501  |  © The Author(s) 2013
Received: January 25, 2013  |  Accepted: March 02, 2013  |  Published: November 20, 2013

Abstract

Under the market environment of low carbon, whether renewable energy can obtain the power for sustainable development, promote the goal of the whole society and make money for investors depends on the rational optimization of power investment capacity and achieving power generation resources coordinated scheduling. This study constructs an expansion model of the generation capacity investment taking oligopoly, policy tools, carbon emissions trading right and green certificate system into account and uses the case analysis of the impact of ETS mechanism and the Tradable Green Certificate mechanism on power generation enterprises investment capacity with Newton KKT interior-point method. This study can also provide a strong decision basis for policy making.

Keywords:

Carbon emissions trading, generation capacity investment model, green certificate, Newton KKT interior-point method, oligopoly,


References


Competing interests

The authors have no competing interests.

Open Access Policy

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Copyright

The authors have no competing interests.

ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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