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An adaptive under-frequency optimal control strategy for power system combined pumped storage and under-frequency load shedding

Authors :
Wentao Huang
Jinman Yu
Zhijun Yuan
Zhongwei He
Jun He
Minghui Deng
Source :
PLoS ONE, Vol 16, Iss 12 (2021), PLoS ONE, Vol 16, Iss 12, p e0261093 (2021), PLoS ONE
Publication Year :
2021
Publisher :
Public Library of Science (PLoS), 2021.

Abstract

With the construction and development of ultra-high voltage (UHV) power grids, large-scale, long-distance power transmission has become common. A failure of the connecting line between the sending-end power grid and the receiving-end power grid will cause a large-scale power shortage and a frequency drop in the receiving-end power grid, which can result in the frequency collapse. Presently, under-frequency load shedding (UFLS) is adopted for solving the frequency control problem in emergency under-frequency conditions, which can easily cause large load losses. In this context, a frequency coordination optimal control strategy is proposed, which combines the mode transition of pumped storage units with UFLS to deal with emergency under-frequency problems. First, a mathematical model of the frequency dynamic response is established, which combines the mode transition of pumped storage units with UFLS based on a single-machine equivalent model. Then, an optimal model of the minimal area of the power system’s operation frequency trajectory is introduced, yielding the optimal frequency trajectory, and is used for obtaining the action frequency of the joint control strategy. A simulated annealing algorithm based on the perturbation analysis is proposed for solving the optimal model, and the optimal action frequency is obtained that satisfies the transient frequency offset safety constraint of the power system. Thus, the joint optimal control of the mode transition of the pumped storage units and UFLS is realized. Finally, the EPRI-36 bus system and China’s actual power grid are considered, for demonstrating the efficiency of the proposed strategy.

Details

ISSN :
19326203
Volume :
16
Database :
OpenAIRE
Journal :
PLOS ONE
Accession number :
edsair.doi.dedup.....03f2aaa67dd2ba336a1b47f460f06cb0