19.04.2020 Aufrufe

VGB POWERTECH 10 (2019)

VGB PowerTech - International Journal for Generation and Storage of Electricity and Heat. Issue 10 (2019). Technical Journal of the VGB PowerTech Association. Energy is us! Cyber security. Power generation. Environment. Flexibility.

VGB PowerTech - International Journal for Generation and Storage of Electricity and Heat. Issue 10 (2019).
Technical Journal of the VGB PowerTech Association. Energy is us!
Cyber security. Power generation. Environment. Flexibility.

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<strong>VGB</strong> PowerTech <strong>10</strong> l <strong>2019</strong><br />

Analysis of a grid integrated wind energy conversion system<br />

Initialization of the PID gain<br />

parameters and flames (upper<br />

band, lower band, etc)<br />

At this point, new(w) is the innovative<br />

weight, prev(w) is the preceding weight<br />

and ∆w is the alteration of weight of each<br />

one output.<br />

Step 7: With the subsequent equation, alteration<br />

of weight in the network is estimated.<br />

Calculate the flames Number<br />

∆w = .Y out .error(BP) (34)<br />

Moths<br />

With in limits<br />

Calculate fitness of moths<br />

and sort the moths<br />

Use the fitness function<br />

Update the position of<br />

flames<br />

No<br />

Bring it to limits<br />

In Equation (34), is the knowledge rate.<br />

Replicate the above steps up to the<br />

error(BP) get diminished error(BP)itermax<br />

Yes<br />

Print the best solution<br />

Y 1<br />

Output Layer<br />

Fig. 6. Training structure of ANN using<br />

proposed adaptive approach.<br />

Here, w ij is the mass of the i – j relation of<br />

the network. Afterward, Y i is the output of<br />

i th hidden neuron. Moreover, discover the<br />

alteration in weights derived from the acquired<br />

BP fault.<br />

Step 4: Resolve the bias (or) establishment<br />

task of the network.<br />

(32)<br />

Step 5: Resolve the bias (or) establishment<br />

task of the network.<br />

(32)<br />

Step 6: The innovative weights of the each<br />

one neurons of the network are modernized<br />

through the subsequent equation,<br />

new(w) = prev(W)+∆W (33)<br />

Results and Discussions<br />

In this segment, the presentation study of<br />

proposed adaptive procedure is investigated<br />

by means of the grid incorporated<br />

WECS. It depicts the cascaded H-bride MLI<br />

of the grid incorporated power system. At<br />

this point the working presentation of the<br />

anticipated regulator is executed in the<br />

MATLAB/Simulink platform. The efficiency<br />

of the proposed control process is investigated<br />

and contrasted by the conventional<br />

methods like MFO and FA-ANN. The Simulink<br />

diagram of the proposed system<br />

through the grid incorporated WECS is depicted<br />

in the F i g u r e 7, which is employed<br />

to manage the power flow of the grid incorporated<br />

WECS through the aid of anticipated<br />

adaptive procedure. In the function,<br />

the PID regulator is engaged to control the<br />

actual, immediate power and voltage of the<br />

grid incorporated WECS. The execution<br />

limitations are investigated and demonstrated<br />

in the Ta b l e 2 .<br />

Performance analysis<br />

Here, the presentation of the proposed<br />

regulator is investigated. The proposed<br />

procedure is exploited to adjust the dc link<br />

voltage and cascaded H-bridge MLI based<br />

on their manage signals. The presentation<br />

of the anticipated regulator is investigated<br />

in the standard wind speed situation and<br />

diverse wind speed situation. These examinations<br />

of the two situations are created as<br />

the dissimilar kind of conditions like condition<br />

1 and condition 2 correspondingly.<br />

The investigated outputs of the anticipated<br />

process are contrasted by MFO process and<br />

FA-ANN process. The complete study of the<br />

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