DocumentCode :
2673463
Title :
A reliability assessment methodology for distribution systems with distributed generation
Author :
Duttagupta, Suchismita S. ; Singh, Chanan
Author_Institution :
Dept. of Electr. & Comput. Eng., Texas A&M Univ., College Station, TX
fYear :
0
fDate :
0-0 0
Abstract :
Reliability assessment is of primary importance in designing and planning distribution systems that operate in an economical manner with minimal interruption of customer loads. With the advances in renewable energy sources, distributed generation (DG), is forecasted to increase in distribution networks. This paper presents a new methodology that can be used to quantitatively analyze the reliability of such distribution systems and can be applied in preliminary planning studies for such systems. The method uses a sequential Monte Carlo simulation of the distribution system´s stochastic model to generate the operating behavior. This is combined with a path augmenting Max flow algorithm to evaluate the load status for each state change of operation in the system. Overall system and load point reliability indices such as hourly loss of load, frequency of loss of load and expected energy unserved can be computed using this technique. The reliability indices can be compared for different scenarios and strategies for placement of DG using this methodology
Keywords :
Monte Carlo methods; distributed power generation; load forecasting; power distribution planning; power distribution reliability; Max flow algorithm; Monte Carlo simulation; distributed generation; distribution system planning; reliability assessment methodology; stochastic model; Costs; Distributed control; Economic forecasting; Maintenance; Power generation; Power generation economics; Power system economics; Power system reliability; Renewable energy resources; Standby generators;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power Engineering Society General Meeting, 2006. IEEE
Conference_Location :
Montreal, Que.
Print_ISBN :
1-4244-0493-2
Type :
conf
DOI :
10.1109/PES.2006.1708964
Filename :
1708964
Link To Document :
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