2018Unpublished venueRequires access

Multiple Scenarios Microgrid Equivalent Modeling Based on the Uncertainty of Distributed Generations

Changchun Cai, Tao Yuan, Haolin Liu, Zhixiang Deng, Weili Dai, Jinbo Zhang

Open publisher page 2 citations

Abstract

The paper proposes a novel microgrid equivalent modeling methodology to decide the optimal equivalent model of microgrid in grid-tied mode based on the uncertainty of distributed generations. The uncertainty of the outputs power of distributed generations, such as PV and wind generation, make the microgrid operates different conditions. As a result, the equivalent model of microgrid will change based on the different operation condition, however, there are relationship between each other. The uncertainty characteristic of distributed generation follows Gaussian distribution, and the operations condition of microgrid will be divided into 24 scenarios in one day based on the different probability statistics of distributed generations. Multi-Scenario technology contains, Latin hypercube sampling and scenario reduction techniques, are used to deal with the uncertainty of distributed generations. The algorithm was applied into a microgrid test system, and the test results show that the new method can simplify the relationship of different operation scenarios of microgrid. And the influence of uncertainty fluctuation of distributed generations can be effectively suppressed in microgrid equivalent modeling.

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What this paper is about

The paper proposes a novel microgrid equivalent modeling methodology to decide the optimal equivalent model of microgrid in grid-tied mode based on the uncertainty of distributed generations. The uncertainty of the outputs power of distributed generations, such as PV and wind generation, make the microgrid operates different conditions. As a result, the equivalent model of microgrid will change based on the different operation condition, however, there are relationship between each other. The uncertainty characteristic of distributed generation follows Gaussian distribution, and the operations condition of microgrid will be divided into 24 scenarios in one day based on the different probability statistics of distributed generations. Multi-Scenario technology contains, Latin hypercube sampling and scenario reduction techniques, are used to deal with the uncertainty of distributed generations. The algorithm was applied into a microgrid test system, and the test results show that the new method can simplify the relationship of different operation scenarios of microgrid. And the influence of uncertainty fluctuation of distributed generations can be effectively suppressed in microgrid equivalent modeling.

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Available abstract

The paper proposes a novel microgrid equivalent modeling methodology to decide the optimal equivalent model of microgrid in grid-tied mode based on the uncertainty of distributed generations. The uncertainty of the outputs power of distributed generations, such as PV and wind generation, make the microgrid operates different conditions. As a result, the equivalent model of microgrid will change based on the different operation condition, however, there are relationship between each other. The uncertainty characteristic of distributed generation follows Gaussian distribution, and the operations condition of microgrid will be divided into 24 scenarios in one day based on the different probability statistics of distributed generations. Multi-Scenario technology contains, Latin hypercube sampling and scenario reduction techniques, are used to deal with the uncertainty of distributed generations. The algorithm was applied into a microgrid test system, and the test results show that the new method can simplify the relationship of different operation scenarios of microgrid. And the influence of uncertainty fluctuation of distributed generations can be effectively suppressed in microgrid equivalent modeling.

Key concepts: Microgrid, Distributed generation, Latin hypercube sampling, Computer science, Wind power, Mode (computer interface), Grid, Power (physics)

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