Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
7402120 | Energy Policy | 2014 | 10 Pages |
Abstract
One of the key aspects of developing a regional renewable energy plan involves incorporating national renewable energy targets into provincial targets whilst including interim phase targets and technology targets. This paper proposes a renewable energy model based on national targets 'decomposed' into regional targets that incorporate technological processes and environmental conditions at the individual project level. At the project level, resource potential is allocated into individual projects based on the current technological level. The available resources and renewable energy generation of each project changes as the technology evolves and the environmental conditions change over time. The model can be adjusted according to actual needs of each region; thus policymakers can establish the respective targets for power, heating, oil and gas as well as renewable energy based on the regional context. Overall, the total national target can be decomposed into regional targets and technological targets. This paper proposes long-term regional development targets for renewable energy based on the total supply curve for renewable energy in different periods. Fujian province will be applied as an example to validate the target decomposition model of renewable energy targets of various regions and technologies in China. The model projected that the economic capacity of renewable energy generation in Fujian province for dam hydropower, offshore wind power, onshore wind power, photovoltaic power and waste incineration power is expected to reach 4748Â MW, 4036Â MW, 3581Â MW, 2663Â MW and 766Â MW, respectively by 2025. The research result could have wider implications such as achieving GHG emissions reductions targets, addressing environmental concerns, providing high tech jobs within the region and contributing to energy security at the local and national level.
Keywords
Related Topics
Physical Sciences and Engineering
Energy
Energy Engineering and Power Technology
Authors
Zhen Liu, Jenny Lieu, Xiliang Zhang,