# ANFIS-Based Droop Control of an AC Microgrid System: Considering Intake of Water Treatment Plant

^{1}

^{2}

^{3}

^{4}

^{*}

## Abstract

**:**

## 1. Introduction

_{2}gas) into the atmosphere harms the environment in many ways. Therefore, Considering the importance and ever-ending demand of reliable public water supply, sustainable treatment as well as sustainable power supply becomes very important so as to improve the treatment as well as reduce the burden of every municipals.

- To consider intake of water treatment plant as a microgrid system;
- To implement DGs on the microgrid system;
- To implement droop control and apply the Adaptive Neuro Fuzzy Inference ANFIS technique;
- To analyze and compare the result with generalized droop control (GDC) method.

## 2. Intake Microgrid Configuration and Modeling (Topology)

#### 2.1. Modeling and Control of PV with Battery System

#### 2.1.1. Solar Photo Voltaic (SPV) System

_{rs}and ϴ represents the reverse saturation current and the temperature of p − n junction. A is the ideality factor I

_{scr}is the short-circuit current of a single PV cell and S is solar irradiation level, n

_{s}and n

_{p}are the series and parallel number of PV cells in a string, q (=1.602 × 10

^{−19}C) and k (=1.38 × 10

^{−23}J/K) are the unit electric charge and Boltzmann’s constant respectively, also, ϴ

_{r}is the cell temperature reference and k

_{ϴ}is the temperature coefficient [32,33].

_{1}is ON (S

_{1}= 1)

_{1}is Off (D

_{1}= 1)

_{1}= 1 − S

_{1})

#### 2.1.2. Battery Energy Storage System (BESS)

_{b}and V

_{bt}represents the terminal Voltage and the internal source voltage (V), R

_{b}

_{1}represents the internal source resistance (Ω) and C

_{b}

_{1}represents internal capacitance (F), V

_{cb}

_{1}represents the Voltage (V) across C

_{b}

_{1}. Where I

_{b}

_{1}represents internal battery current (A), R

_{b}

_{2}represents poarization resistance (Ω) and R

_{b}

_{3}represents ohmic resistance (Ω), which are connected to the charging and discharging properties of the battery, i.e., transient dynamics respectively. C

_{b}

_{2}represnts the polarization capacitance (F) and V

_{cb}

_{2}represents Voltage (V) across C

_{b}

_{2}. Additionally, I

_{b}represents the battery output Current (I). Equations related to the dynamic model of the battery can be expressed in the following equations [36,37].

_{2}is on (S

_{2}= 1, S

_{3}= 0)

_{2}is off (S

_{2}= 0, S

_{3}= 1)

_{3}= 1 − S

_{2})

#### 2.2. Modelling and Control of WIND Turbine Generator

## 3. Control Unit Diagram

#### 3.1. Generalized Droop Control (GDC)

_{2}is considered the voltage at PCC located on the load side; the voltage source converter (VSC) transforms the DC voltage into AC, as per the system requirement, and the output voltage V

_{1}is considered at point A; the line impedance ZL, the reactive power Q

_{A,}and real power P

_{A}at point A can be given by.

_{A}represents real power, and Q

_{A}is the reactive power, V

_{1}represents inverter output voltage at point A, V

_{2}is the voltage at PCC and δ represents power angle and ϴ represents the phase angle of the line impedance Z

_{L}, also, X

_{L}and R

_{L}represents the line reactance as well as inductance of the line. In general, either X

_{L}or R

_{L}is ignored in Equations (23) and (24), by neglecting reactance and inductance of the line the P-V/Q-f or P-f/Q-V relation of the droop characteristics are developed. Additionally, the virtual reactive power Q

_{vir}as well as the real power P

_{vir}can be derived as,

#### 3.2. Simulation of the GDC System

## 4. ANFIS-Based Droop Control Approach

#### ANFIS Architecture and Controller

- Rule no 1: If P is A
_{1}and Q is B_{1}, then f_{1}= p_{1}P + q_{1}Q + r_{1}, - Rule no 2: If P is A
_{2}and Q is B_{2}, then f_{2}= p_{2}P + q_{2}Q + r_{2}.

_{1}, q

_{1}, r

_{1}and p

_{2}, q

_{2}, r

_{2}represents the parameters of each of the output functions. Each node of these output is referred as firing strength of a rule. The corresponding layers of the ANFIS are explained in the followings

_{i}(or A

_{i}) represents the linguistic label (could be small, large, etc.). Additionally, it can be stated that O

_{1},

_{i}is the MF of A

_{i}. and it specifies the degree to which it satisfies the quantifier A

_{i}. Normally, μA

_{i}is selected in a bell-shaped form containing a limit set of 1 as maximum and 0 as minimum correspondingly, μA

_{i}(P) can be given as follows [55,56]

_{i}or linguistic label.

_{2},

_{i}= W

_{i}= μ

_{Ai}(P) × μB

_{i}(Q); i = 1,2

_{i}. The signals from the incoming are ith line with the precursor (if) of the rule.

## 5. Results and Discussion

## 6. Conclusions

## Author Contributions

## Funding

## Conflicts of Interest

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**Figure 5.**Battery equivalent circuit [37].

Sl. No. | Load | Power | Unit |
---|---|---|---|

1 | Raw water pump 1 | 350 | kW |

2 | Raw water pump 2 | 350 | kW |

3 | Indoor & outdoor lighting | 2.5 | kW |

4 | Sludge pump | 2.8 | kW |

5 | Auxiliary load | 1.9 | kW |

Sl. No. | Source | Value | Unit |
---|---|---|---|

1 | Solar | 2.5 | kW |

2 | Battery | 1.5 | kW |

3 | Wind | 1 | kW |

4 | HT Diesel generator | 1000 | kVA |

Sl. No. | Grid Connected (0–0.5) | Islanded (0.5–1) | Load (HT/LT) | Operation Time (s) |
---|---|---|---|---|

1 | On | On | Raw water pump 1 | 0–1 |

2 | On | On | Raw water pump 2 | 0–1 |

3 | Off | On | Indoor & outdoor lighting | 0–0.6 |

4 | Off | On | Sludge pump | 0.2–0.8 |

5 | Off | On | Auxiliary load | 0.4–0.9 |

Parameters | Values | Parameters | Values |
---|---|---|---|

ϴ | 289 °k | n_{p} | 249 |

q | 1.602 × 10^{−19} C | I_{src} | 8.12A |

S | 1.2 | Ѳ_{r} | 300 °k |

I_{rs} | 1.8 × 10^{−7} | n_{s} | 238 |

A | 1.692 | k_{ѳ} | 0.0014 |

K | 1.38 × 10^{−23} J/K |

Parameters | Values | Parameters | Values |
---|---|---|---|

C_{b}_{1} | 49,000 F | R_{b}_{3} | 0.0019 Ω |

C_{b}_{2} | 1.5 F | R_{b}_{4} | 0.045 Ω |

R_{b}_{1} | 0.045 Ω | V_{b} | 46V |

R_{b}_{2} | 0.001 Ω |

Parameters | Values | Parameters | Values |
---|---|---|---|

V_{w-rated} | 8.5 m/s | β | 0 deg |

Ρ | 1.204 kg/m^{3} | n_{gear} | 5.8 |

R | 4.6 | P_{T-rated} | 22.9 kW |

Sl. No. | Details | Data | Details | Data |
---|---|---|---|---|

1 | Input Numbers of MFs | 63 | Error tolerance | 0 |

2 | Input MFs type | Product of two sigmoidal membership function (psigmf) | Epochs | 200 |

3 | Output MFs type | Constant | Optimization method | Hybrid |

Sl. No. | Details | Data | Details | Data |
---|---|---|---|---|

1 | Input Numbers of MFs | 63 | Error tolerance | 0 |

2 | Input MFs type | Triangular membership function (trimf) | Epochs | 200 |

3 | Output MFs type | Linear | Optimization method | Hybrid |

Sl. No. | Parameters | P-f ANFIS Data | Q-V ANFIS Data |
---|---|---|---|

1 | Number of nodes | 59 | 43 |

2 | Number of linear parameters | 54 | 36 |

3 | Number of nonlinear parameters | 36 | 21 |

4 | Total number of parameters | 90 | 57 |

5 | Number of training data pairs | 500172 | 500,172 |

6 | Number of fuzzy rules | 18 | 12 |

7 | Number of checking data pairs | 0 | 0 |

8 | Minimal training RMSE | 0.002753 | 0.001753 |

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## Share and Cite

**MDPI and ACS Style**

Rohmingtluanga, C.; Datta, S.; Sinha, N.; Ustun, T.S.; Kalam, A.
ANFIS-Based Droop Control of an AC Microgrid System: Considering Intake of Water Treatment Plant. *Energies* **2022**, *15*, 7442.
https://doi.org/10.3390/en15197442

**AMA Style**

Rohmingtluanga C, Datta S, Sinha N, Ustun TS, Kalam A.
ANFIS-Based Droop Control of an AC Microgrid System: Considering Intake of Water Treatment Plant. *Energies*. 2022; 15(19):7442.
https://doi.org/10.3390/en15197442

**Chicago/Turabian Style**

Rohmingtluanga, C., Subir Datta, Nidul Sinha, Taha Selim Ustun, and Akhtar Kalam.
2022. "ANFIS-Based Droop Control of an AC Microgrid System: Considering Intake of Water Treatment Plant" *Energies* 15, no. 19: 7442.
https://doi.org/10.3390/en15197442