Distributed Variable Droop Curve Control Strategies in Smart Microgrid

Changhong Deng, Yahong Chen, Jin Tan, Pei Xia, Ning Liang, Weiwei Yao and Yuan-ao Zhang
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Changhong Deng: School of Electrical Engineering, Wuhan University, Wuhan 430072, Hubei, China
Yahong Chen: School of Electrical Engineering, Wuhan University, Wuhan 430072, Hubei, China
Jin Tan: School of Electrical Engineering, Wuhan University, Wuhan 430072, Hubei, China
Pei Xia: School of Electrical Engineering, Wuhan University, Wuhan 430072, Hubei, China
Ning Liang: School of Electrical Engineering, Wuhan University, Wuhan 430072, Hubei, China
Weiwei Yao: School of Electrical Engineering, Wuhan University, Wuhan 430072, Hubei, China
Yuan-ao Zhang: School of Electrical Engineering, Wuhan University, Wuhan 430072, Hubei, China

Energies, 2017, vol. 11, issue 1, 1-17

Abstract: In micro grid (MG), active/reactive power sharing for all dis-patchable units is an important issue. To meet fluctuating loads’ active and reactive power demands, the units generally adopt primary P-f and Q-U droop control methods. However, at different state of charge (SOC) values, the capability of Lead Acid Battery Bank (LABB) based units to take loads varies in a large range; active power should not be shared according to the units P capacities in a constant ratio. Besides, influenced by the output and line impedance between units, reactive power is not able to be shared in proportion to the units Q capacities. Another problem, after MG power balance requirement is satisfied, frequency and voltage are deviating from their rated values thus power quality is reduced. This paper presents a new smart MG which is based on the multi agent system. To solve the problems mentioned above, P-f and Q-U droop curves are adjusted dynamically and autonomously in local agents. To improve the power quality, secondary restoration function is realized in a decentralized way, the computation tasks are assigned to local, the computation capability and communication reliability requirements for central PC are low, and operation reliability is high. Simulation results back the proposed methods.

Keywords: Smart MG; multi agent; variable (static and dynamic) droop curve; power sharing; distributed secondary control (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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