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 :
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