DOI:10.1007/s40565-017-0331-y |
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Multi-objective energy management system for DC microgridsbased on the maximum membership degree principle |
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Net amount: 854 |
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Author:
Panbao WANG1
, Wei WANG1
, Nina MENG1
, Dianguo XU1
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Author Affiliation:
1. School of Electrical Engineering and Automation, Harbin
Institute of Technology, Harbin 150001, China
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Foundation: |
This work was supported by National Natural
Science Foundation of China (No. 51707045). |
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Abstract: |
With the increasing quantity of DC electrical
equipment, DC microgrids have been paid more and more
attention. This paper proposes an approach to multi-objective
optimisation of an energy management system
(EMS) for a DC microgrid that includes a hybrid energy
storage system (HESS). The operating and maintenance
cost and the loss of power supply probability (LPSP) of the
system are used as optimisation targets. The power flows of
all distributed generators (DGs) in the DC microgrid during
operating period are optimized. Based on the improved
differential evolution (DE) algorithm, and by using the
multi-objective non-dominated sorting method and the
maximum membership degree principle (MMDP) of fuzzy
control, the overall satisfaction degree of Pareto solutions
to power flow optimization can be obtained. Simulation
results verify the effectiveness of the proposed EMS optimization
scheme, which is able to achieve an effective
trade-off between the economy and the reliability of
microgrid operation. |
Keywords: |
DC microgrids, Energy management system,
Multi-objective optimization, Differential evolution
algorithm, Maximum membership degree |
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Online Time:2018/07/20 |
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