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| 1 |
ID:
185699
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| Summary/Abstract |
Renewable portfolio standards have been found to be effective in promoting renewable energy developments; however, in China, the implementation of renewable portfolio standards is not yet fully developed. Based on policy acceptance, generation costs, and renewable power target perspectives, this paper proposes a multi-objective equilibrium model to develop an annual single province power plan. A case study from Guangdong province, China, is presented to demonstrate the practicality and efficiency of the presented model. Comparison analysis with current plans are made, three scenarios which consider the non-hydro renewable targets, market competition and a tougher environmental attitude are designed to adapted to the decision maker's preferences. It was found that: (1) the optimal model reallocated policy costs between power users, distributed the generation capacity between provinces, and could obtain 35.4% renewable electricity and 4.3% of non-hydro renewable electricity consumption in Guangdong; and (2) compared with the current plan, the optimal model effectively maintained power tariffs, decreased generation costs by 2.42%, and decreased Guangdong's electricity generation CO2 emissions by 8.21%. Policy suggestions for provincial governments to better implement provincial renewable portfolio standards are given.
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| 2 |
ID:
124328
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| Publication |
2013.
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| Summary/Abstract |
There is a large disparity in the amount of wind power capacity installed in each of the states in the U.S. It is often thought that the different policies of individual state governments are the main reason for these differences, but this may not necessarily be the case. The aim of this paper is to use statistical methods to study the factors that have the most influence on the amount of installed wind capacity in each state. From this analysis, we were able to use these variables to accurately predict the installed wind capacity and to gain insight into the driving factors for wind power development and the reasons behind the differences among states. Using our best model, we find that the most important variables for explaining the amount of wind capacity have to do with the physical and geographic characteristics of the state as opposed to policies in place that favor renewable energy.
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