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UPQC voltage sag detection based on chaotic immune gentic algorithm

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Abstract

Photovoltaic generation is being rapidly developed as a clean energy source. The increased penetration of photovoltaics into power distribution networks has led to power-quality problems. A unified power-quality conditioner (UPQC) is an effective device for power-quality treatment and can compensate for voltage fluctuations and sags in a photovoltaic microgrid. This paper proposes a proportional–integral (PI) controller for detecting and compensating for voltage sags in a UPQC that is based on the chaotic immune genetic algorithm. Simulations showed that the proposed PI controller better compensates for the voltage than the traditional PI controller. Experimental results also showed that the new method can accurately detect and compensate for voltage sags in a photovoltaic microgrid in real time. The proposed PI controller can quickly detect voltage sags and improve the microgrid power quality; it provides a new approach to treating the power quality of a photovoltaic microgrid with a UPQC.

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Abbreviations

\(U_s \) :

The grid resource

\(u_{ac} , u_{bc} ,\) and \(u_{cc} \) :

The three-phase voltage compensation instructions

\(u_a ,u_b ,u_c \) :

The three-phase voltage

\(u_a ^{{+}},u_b ^{{+}},u_c ^{{+}}\) :

Three-phase positive sequence components

\(u_a ^{-},u_b ^{-},u_c ^{-}\) :

Three-phase negative sequence components

\(u_0 \) :

Zero sequence component

\(u_{an} ^{+},u_{bn} ^{+},u_{cn} ^{+}\) :

N-order harmonic positive sequence components

\(u_{an} ^{-},u_{bn} ^{-},u_{cn} ^{-}\) :

N-order harmonic negative sequence components

T :

Park transformation matrix

\(T^{-1}\) :

Inverse Park transformation matrix

\(U^{+}\) :

Fundamental harmonic positive sequence phase voltage actual amplitude

\(\phi ^{+}\) :

Fundamental harmonic positive-sequence initial phase.

\(U_{la} ,U_{lb} ,U_{lc} \) :

Three-phase loads voltages

B(k):

The concentration of the k-th generation of B cells

\(\varepsilon (k)\) :

The antigen concentration of the k-th generation

\(\Delta B(k)\) :

The change in the B-cell concentration

\(f\,{[\cdot ]}\,\) :

A nonlinear function associated with the change in the B-cell concentration

\(K_P \) :

The variable proportional gain coefficient

\(K_I \) :

An integration constant

\(\overline{K} _P \) :

The output of an intelligent regulator

\(\overline{K} _I \) :

The output of an intelligent regulator

J :

The performance index

T:

Sample time

\(t_i \) :

Sample point

\(\mu \) :

A real number

\(x_0 \) :

The original value

Ab :

The initialization antibody

Ag :

Antigen

\(a_{ij} \) :

The appetency

N:

The chaotic variable

\(N_c \) :

The number of clones

m :

Selected network cells

C :

A cloned antibody cell

X :

A cloned antigen cell

\(\alpha \) :

The aberration rate

\(M_p \) :

Memory-cell data set

\(\xi \% \) :

Best affinity

M :

The achieved memory data set

\(\phi \) :

A contraction factor

\(X=(X_1 ,X_2 ,\ldots ,X_k )\) :

The superior individual

\(\beta _i \) :

The adaptive control coefficient

K :

The number of iterations

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Acknowledgements

This study was supported by National Natural Science Foundation of China (51477070), Jiangsu Province Prospective Joint Research Project (BY2015028-01), a Project Funded by The Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD), and Changzhou Electric Power Company Science Research Foundation (KYH16044).

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Authors and Affiliations

  1. School of Electrical and Information Engineering, Jiangsu University, Zhenjiang, 212013, Jiangsu, China

    Fuyin Ni & Zhengming Li

  2. School of Electrical and Information Engineering, Jiangsu University of Technology, Changzhou, 213001, Jiangsu, China

    Fuyin Ni, Qi Wang & Songlin Wo

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  1. Fuyin Ni
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Correspondence to Zhengming Li.

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Ni, F., Li, Z., Wang, Q. et al. UPQC voltage sag detection based on chaotic immune gentic algorithm. Cluster Comput 20, 321–333 (2017). https://doi.org/10.1007/s10586-016-0704-4

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