Random-Fuzzy Chance-Constrained Programming Optimal Power Flow of Wind Integrated Power Considering Voltage Stability

Considering the random and fuzzy nature of wind speed, this paper proposes a multi-objective random-fuzzy chance-constrained programming optimal power flow (OPF) for wind integrated power systems. The proposed method is based on random-fuzzy chance-constrained programming. The optimization model aim...

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Vydáno v:IEEE access Ročník 8; s. 217957 - 217966
Hlavní autoři: Ma, Rui, Li, Xuan, Gao, Weicheng, Lu, Peng, Wang, Tieqiang
Médium: Journal Article
Jazyk:angličtina
Vydáno: Piscataway IEEE 2020
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Carbon dioxide
chance-constrained programming
Constraints
Decision making
Flow stability
Genetic algorithms
Load flow
Load modeling
Optimal power flow (OPF)
Optimization
Power flow
Power system stability
Programming
random-fuzzy variable
Simulation
Sorting algorithms
Stability criteria
Uncertainty
Voltage stability
wind power generation
Wind speed
ISSN:2169-3536, 2169-3536
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Shrnutí:Considering the random and fuzzy nature of wind speed, this paper proposes a multi-objective random-fuzzy chance-constrained programming optimal power flow (OPF) for wind integrated power systems. The proposed method is based on random-fuzzy chance-constrained programming. The optimization model aims at minimizing generation cost, carbon dioxide (CO2) emission, and system functional power loss, and P-Q-V steady-state voltage stability is included in the constraints. Based on random-fuzzy chance-constrained programming, the corresponding solution process of the proposed multi-objective OPF is proposed, which is a hybrid of random-fuzzy simulation, non-dominated sorting genetic algorithm-II (NSGA-II), and fuzzy satisfaction-maximizing decision-making method. The proposed approach is simulated on the IEEE 30-bus system to provide an example of its application. The simulation results demonstrate that the proposed random-fuzzy chance-constrained programming OPF has higher security and more economy than dynamic stochastic optimal power flow (DSOPF) and dynamic fuzzy optimal power flow (DFOPF).
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ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2020.3040382