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Evaluating Influence of Variable Renewable Energy Generation on Islanded Microgrid Power Flow
- Source :
- IEEE Access, Vol 6, Pp 71339-71349 (2018)
- Publication Year :
- 2018
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2018.
-
Abstract
- With the proliferation of renewable energy, the uncertainty has challenged the continuous operation of microgrids; thus, it is of importance to tackle uncertainties in power system operation. In this paper, a global sensitivity analysis (GSA) method is proposed to evaluate the influence of uncertainties on the power flow of islanded microgrids (IMGs). First, a probabilistic power flow model for IMGs is established considering the droop-controlled distributed generation units and the uncertainties of renewable energy generation output and load demands. Then, the global sensitivity analysis is introduced to identify important variables that affect IMG power flow. In addition to conventional GSA indices, the Shapley value-based GSA index is designed to evaluate the influence of correlated input variables. Moreover, the sparse polynomial chaos expansion is used to establish the surrogate models of IMG power flow, which improves the efficiency of GSA. Finally, the proposed method is tested on the 33-bus and 69-bus IMG systems, and the simulation results are compared with those considering other methods. The rankings of random input variables that affect IMG power flow are given, and the influence of correlation between different variables is discussed.
- Subjects :
- Mathematical optimization
General Computer Science
business.industry
Computer science
Islanded microgrid
020209 energy
General Engineering
02 engineering and technology
AC power
renewable energy
Shapley value
Renewable energy
Electric power system
Variable renewable energy
probabilistic power flow
global sensitivity analysis
Distributed generation
0202 electrical engineering, electronic engineering, information engineering
General Materials Science
lcsh:Electrical engineering. Electronics. Nuclear engineering
Microgrid
uncertainty
business
lcsh:TK1-9971
Subjects
Details
- ISSN :
- 21693536
- Volume :
- 6
- Database :
- OpenAIRE
- Journal :
- IEEE Access
- Accession number :
- edsair.doi.dedup.....5155fd46b16d866e0d827f99daab04d2