TY - GEN
T1 - Intelligent and concurrent analytic platform for renewable energy policy assessment using open data resources
AU - Wang, Danny Y.C.
AU - Trappey, Amy J.C.
AU - Trappey, Charles V.
AU - Li, S. J.
PY - 2014/1/1
Y1 - 2014/1/1
N2 - Renewable, clean and economically viable energy sources are needed as alternatives to fossil fueled energy in order to effectively reduce carbon dioxide emissions. Often, the facilities installation costs for generating renewable energy is higher than the cost of traditional power generating facilities. Thus, governments need effective policies, regulations, and incentives to promote the usage of renewable energy. The policies used for promoting specific categories of renewable energies, such as on-shore or off-shore wind farms and solar power plants, vary significantly. These policies' success depends on the policy goals, regulations, taxation, incentives and promotional schemes, which require careful evaluation and assessment using globally available energy/environment/economic (3E) data. The purpose of this study is to propose an intelligent and concurrent analytic platform for renewable energy policy assessment, which can automatically collect, update, integrate, and harmonize data from pre-authorized websites and online databases for analytic modeling. Further, data mining techniques (e.g., clustering analysis and self-organizing maps - SOM) are adopted to identify types of renewable energies, their attributes, economic factors, projected demands and supplies, and environmental benefits and impacts. The research achieves three outcomes. First, the intelligent and concurrent platform architecture is developed and the prototype system is implemented with data management, decision-support model management, and user interface modules. Second, the dynamic data retrieval technique from authorized online data sources for analytic modeling is depicted. Finally, the SOM intelligent model is built and linked to the database as an analytic tool in the model management module.
AB - Renewable, clean and economically viable energy sources are needed as alternatives to fossil fueled energy in order to effectively reduce carbon dioxide emissions. Often, the facilities installation costs for generating renewable energy is higher than the cost of traditional power generating facilities. Thus, governments need effective policies, regulations, and incentives to promote the usage of renewable energy. The policies used for promoting specific categories of renewable energies, such as on-shore or off-shore wind farms and solar power plants, vary significantly. These policies' success depends on the policy goals, regulations, taxation, incentives and promotional schemes, which require careful evaluation and assessment using globally available energy/environment/economic (3E) data. The purpose of this study is to propose an intelligent and concurrent analytic platform for renewable energy policy assessment, which can automatically collect, update, integrate, and harmonize data from pre-authorized websites and online databases for analytic modeling. Further, data mining techniques (e.g., clustering analysis and self-organizing maps - SOM) are adopted to identify types of renewable energies, their attributes, economic factors, projected demands and supplies, and environmental benefits and impacts. The research achieves three outcomes. First, the intelligent and concurrent platform architecture is developed and the prototype system is implemented with data management, decision-support model management, and user interface modules. Second, the dynamic data retrieval technique from authorized online data sources for analytic modeling is depicted. Finally, the SOM intelligent model is built and linked to the database as an analytic tool in the model management module.
KW - Integration system
KW - Renewable energy
KW - Self-organizing map
UR - http://www.scopus.com/inward/record.url?scp=84929155596&partnerID=8YFLogxK
U2 - 10.3233/978-1-61499-440-4-781
DO - 10.3233/978-1-61499-440-4-781
M3 - Conference contribution
AN - SCOPUS:84946093838
T3 - Moving Integrated Product Development to Service Clouds in the Global Economy - Proceedings of the 21st ISPE Inc. International Conference on Concurrent Engineering, CE 2014
SP - 781
EP - 789
BT - Moving Integrated Product Development to Service Clouds in the Global Economy - Proceedings of the 21st ISPE Inc. International Conference on Concurrent Engineering, CE 2014
A2 - Chou, Shuo-Yan
A2 - Stjepandic, Josip
A2 - Xu, Wensheng
A2 - Cha, Jianzhong
A2 - Curran, Richard
PB - IOS Press BV
Y2 - 8 September 2014 through 11 September 2014
ER -