Quantitative techniques for analysis of large data sets in renewable distributed generation Conference Paper

abstract

• Distributed generation (DG) reduces losses and eliminates some of the transmission and distribution costs. It may also reduce fossil fuel emissions, defer capital costs, and improve the distribution feeder voltage conditions. The calculation of the effects of small residential photovoltaic (PV) and wind DG systems on various feeder operating variables is complicated by both the probabilistic nature of their output and the variety of their possible spatial allocations. A method based on a combination of clustering techniques and a convex hull algorithm is proposed that may reduce the computational burden by an order of magnitude, while still allowing accurate estimation of DG-enhanced feeder operation.

name of conference

• IEEE PES Power Systems Conference and Exposition, 2004.

authors

• Begovic, Miroslav

published proceedings

• 2004 IEEE PES Power Systems Conference and Exposition

author list (cited authors)

• Pregelj, A., Begovic, M., & Rohatgi, A.

complete list of authors

• Pregelj, A||Begovic, M||Rohatgi, A

publication date

• December 2004

keywords

• Air Pollution Control
• Capital Cost
• Clustering Algorithms
• Clustering Technique
• Convex Hull Algorithm
• Convex Programming
• Cost Reduction
• Costs
• DG
• Data Analysis
• Distributed Control
• Distributed Power Generation
• Distribution Cost Elimination
• Distribution Feeder Voltage Condition
• Feeder Operation
• Fossil Fuel Emission Reduction
• Fossil Fuels
• Large Data Set
• Loss Reduction
• Photovoltaic Power Systems
• Photovoltaic Systems
• Power Distribution Economics
• Power Transmission Economics
• Propagation Losses
• Quantitative Technique
• Renewable Distributed Generation
• Residential Photovoltaic System
• Solar Power Generation
• Statistical Analysis
• Transmission Cost Elimination
• Voltage
• Wind Dg System
• Wind Power Plants

International Standard Book Number (ISBN) 10

• 078038718X

International Standard Book Number (ISBN) 13

• 9780780387188

start page

• 892

end page

• vol.2

volume

• 2