^{1}

^{*}

^{2}

This paper proposes a boost inverter model capable of coping with changes in load as well as line parameters. In order to achieve an output AC voltage higher than the input DC voltage, we can use this model consisting of a pair of DC-DC converters with a load connected differentially across them. This paper aims at developing a boost inverter that is capable of achieving a very high gain, to obtain an AC voltage of 110 Vrms from a DC input of 36 V. This is exceptionally beneficial in renewable energy applications, where the input voltage garnered is quite small, and in need of stepping up for commercial use or transmission. However, aside from the voltage level itself, lowering the rise time, settling time, peak overshoot and steady state error of the system is of cardinal importance in order to maintain a reliable output voltage. Closed loop control of the differentially connected DC-DC converters is necessary to determine the optimal stable operating point. This paper addresses the above concerns through optimization of the proportional and integral constants using the novel Bacterial Foraging Algorithm, ensuring operation at the required optimal stable operating point. Moreover, load/line disturbances may occur due to which the stability of output voltage may be compromised and THD value may increase to undesirable extents. In these cases, utilization of the output voltage is no longer viable for several applications sensitive to such voltage fluctuations. We have demonstrated that our proposed model is capable of restoring/reverting to the satisfactory sinusoidal waveform fashion within a single voltage cycle. The waveform results that demonstrate the resilience of our model to such disturbances are represented appropriately.

A boost inverter is one that generates a peak ac voltage higher or lower than the input dc voltage, depending on the duty cycle. The topology selected for use in this paper follows that of [

However, there has been adequate criticism of the same, published in [

The same adaptive control has been utilized in [

The control of switched-mode power converters (SMPC) with AC output is usually accomplished by tracking a reference signal. However, newer developments that do not require an external signal have been developed too. One such control strategy is described in [

The value of THD is another important concern. This can be reduced by using closed loop system and optimizing the controller gain of proportional and integral controller constants respectively such that the system response is always maintained at the optimal stable operating point. Control of the switches is done through application of pulses. The timings are decided by the PWM settings. A detailed analysis of PWM techniques can be found in [

Upon identifying the optimal kp and ki values using BFOA, the PWM values are accordingly modified and fed to the converter switches. A particular set of optimizing values for these parameters is obtained for a particular load. Bacterial Foraging Optimization Algorithm [

A very high gain and an ability to correct the output waveform pattern to normal, stable operating fashion within a single cycle of voltage using closed loop voltage mode control incorporating the novel BFOA are the unique contributions of this paper.

Proposed system follows small signal model based voltage mode control strategy. BFOA helps us to obtain accurate values of kp and ki that are fed into the PI controller. For a good dynamic response, we need to obtain the solution for the optimization problem which is given by Equation (1) and Equation (2).

BFOA which is actually derived by the social foraging behavior of Escherichia coli bacteria was proposed by Kevin M. Passino. A bacterium's decision making calculus while foraging is guided by two constraints. The first is the maximum energy that it can garner get per unit time while at the same time moving in search of nutrients. The second constraint is its communication with the other bacteria. A bacterium essentially progresses in steps scanning for an environment with a higher nutrient gradient. This strategy of chemotactic movement of virtual bacteria in the problem search space is used in BFOA. When a bacterium gets sufficient food, it grows, increasing in length until, in the presence of favorable environment conditions it breaks and produces an exact replica of itself in a process known as reproduction. Changes in the environment may not always be favorable, for sudden or abrupt changes in the environment can result in the movement of bacteria to some other place or even their destruction. This is the process of elimination and dispersal. Thus, the three processes of chemotaxis, reproduction and elimination- dispersal form the pith of the BFOA. A trial solution represents a bacterium, the optimum solution of which can be obtained by moving on the functional surface. BFOA applications include but are not limited to PWM converter switching, optimization of power converters and control of power converters. Also, the design parameters are presented in

The hardware setup of the proposed BFOABI is presented in

Upon testing of the BFOABI model, with parameters as shown in

Sl No. | Parameter | Value |
---|---|---|

1 | Population size | 10 |

2 | No of iteration | 10 |

3 | Chemotactic size | 4 |

4 | Reproduction loop size | 4 |

5 | Elimination and dispersal loop size | 2 |

6 | Swim length | 4 |

7 | Dispersal probability | 0.2 |

disturbances tests were done on the existing boost inverter model and satisfactory results were obtained. A specific set of kp and ki values were obtained from simulation to obtain a minimum value for the following parameters: rise time, peak time, settling time and steady state error as given in

Second, in accordance with the formula indicated below, the voltages observed are clamped sinusoidal voltages, (i.e.) sinusoidal waveforms with an additional dc voltage bias Vdc.

The steady state inductor currents are also presented in

Sl No. | Parameter | Value |
---|---|---|

1 | Input dc voltage, V_{g} | 36 V |

2 | Capacitors, C1 and C2 | 20 mF |

3 | Output ac voltage, V_{o} | 110 V_{rms} |

4 | Load resistor, R | 220 |

5 | Switching frequency, f_{s} | 20,000 Hz |

6 | Real time interfacing kit | dSPACE-1104 |

7 | Dual IGBT modules, S_{1} to S_{4} | CM75DU-12H |

8 | Voltage Sensor, LEM LV 25 P | 500 V |

9 | Inductors, L_{1} and L_{2} | 200 H with 0.3 parasitic resistance |

Sl No. | Iteration | k_{p} | k_{i} | M_{p} | E_{ss} | t_{r} | t_{s} |
---|---|---|---|---|---|---|---|

1 | 50 | 3.756e^{−5} | 3.595e^{−5} | 2.1e^{−8} | 0.414 | 0.00562 | 0.017 |

When the inverter input voltage is being stepped down from 36 to 33 V as shown in

the output voltage is resilient to this change while output current reaches steady state within a fraction of 2 ms and we get a waveform with very good quality. The rise time, peak time, settling time and steady state error attains a minimum value. The resilience can be attributed to the successful closed loop control method employed incorporating the BFOA which selects the optimal operating point in a very small duration of time as evidenced by the results presented. Similar results can be observed when the line voltage is stepped up. The results of the same are presented in

When the system is subjected to a sudden change in load from a lagging power factor to a unity power factor load, it is being observed that the output current reaches steady state within a fraction of time, 2 ms, and the corresponding graph is being shown in

to a lagging load was done, we observed that the same desirable waveform pattern was observed as was with the case of line disturbance. The results of which are represented in

As proposed in this paper, from

mator of the reliability of output voltage and is an important factor for determining industrial applicability of this setup. the result obtained by our proposed model comfortably meets the Class A standard prescribed by IEEE, (i.e.) ≤ 5%, for the rated voltage of 36 V to 110 Vrms. Generally even harmonics are zero for inverters, however odd harmonics that dominate, 3rd, 5th, 9th harmonics are also well below the permissible limit, thereby earning a status of PASS on the THD testing done. This result was observed for a variety of loads, rheostatic (as shown in

BFOA based Boost Inverter was presented. DC to AC conversion was achieved in a single stage, incorporating closed loop voltage control techniques. Bacterial Foraging Algorithm was successfully utilized to obtain the optimal values of kp and ki. BFOA algorithm, as proposed, improved the system response of the boost inverter system, reducing rise time, settling time, peak overshoot and steady state error, thereby successfully fulfilling the objective of obtaining desirable time domain system responses. As per IEEE standards, the THD value was observed to be much lower than traditional topology inverters. As evidenced by our results, even when subjected to line and load disturbances, output voltage reached steady state within a time duration of 2 milliseconds exhibiting stability and an ability to withstand the disturbances in any system in which it is utilized. Thus, the proposed system is suitable for all sorts of grid connected and renewable energy applications. For future research, efforts to implement the system with a PV array input can be attempted.

We thank the Editor and the referee for their comments. Research of I. Gnanambal is funded by the National Science Foundation grant DMS 1322353. This support is greatly appreciated.

G. Arunkumar,Dr. I. Gnanambal, (2016) Utilization of Bacterial Foraging Algorithm for Optimization of Boost Inverter Parameters. Circuits and Systems,07,1430-1440. doi: 10.4236/cs.2016.78125