DocumentCode
2069583
Title
Optimizing grid connected renewable energy resources with variability
Author
Momoh, J.A. ; D´Arnaud, K.
Author_Institution
Center for Energy Syst. & Control (CESaC), Howard Univ., Washington, DC, USA
fYear
2012
fDate
22-26 July 2012
Firstpage
1
Lastpage
6
Abstract
The randomness of photovoltaic (PV) and wind as renewable energy resources (RER) are best modeled as stochastic variable resources with given status and probability density function (pdf). The objective´s multiple criteria consist of cost and reliability. These are interlinked by the impact of RER and networks consisting of voltages, flows and available generation resources. To account for the variability and randomness, heuristic technique is developed so as to handle the resources in the implication of the optimal power flow. This will account for the stochastic nature of the problem. The scheme proposed is a framework towards building or designing a stochastic optimal power flow for handling variability of the load randomness. Case studies are proposed under different power output of PV and wind contributions are tested for both the performance load flow and optimization.
Keywords
load flow; photovoltaic power systems; power generation economics; power generation reliability; power grids; power system simulation; probability; renewable energy sources; stochastic processes; wind power plants; PDF; PV RER; generation resource; grid connected renewable energy resource optimization; handling variability; heuristic technique; photovoltaic renewable energy resource; probability density function; reliability; stochastic optimal power flow; stochastic variable resource; wind RER; wind renewable energy resource; Indexes; Load flow; Load modeling; Loading; Mathematical model; Probabilistic logic; Wind speed; optimal power flow; probability density function; renewable resources; variability;
fLanguage
English
Publisher
ieee
Conference_Titel
Power and Energy Society General Meeting, 2012 IEEE
Conference_Location
San Diego, CA
ISSN
1944-9925
Print_ISBN
978-1-4673-2727-5
Electronic_ISBN
1944-9925
Type
conf
DOI
10.1109/PESGM.2012.6345704
Filename
6345704
Link To Document