## Description

IEEE 33 radial bus system is considered for this case. The optimization used is the hybrid PSO GSA (particles Swarm optimisation and Gravitational Search Algorithm). The IEEE 33 bus system data is loaded and bus loading is changed to demonstrate the effective optimization algorithm. The load is increased by 1.6 times as

```
loadlevel=1.6; % different loading in the network
Sload=loadlevel.*S(PQb);
```

Where variable *‘S’* contains the apparent load matrix. backward/Forward Load flow analysis is done on IEEE 33 radial bus system at free-thesis.com. The root soul of our system is the objective function which changes the tie switch positions and place the Distribution generators in the network. For IEEE 33 radial bus system we have a choices of tap switches to be opened or closed, optimal opening/closing of tie switches must be among them during PSOGSA optimization. These are

% switche choices to be opened for network configuration from the loop % formed by closing tie switches in IEEE 33 radial bus system tap=[8 9 10 11 21 33 35 0 0 2 3 4 5 6 7 18 19 20 12 13 14 34 0 0 0 0 0 15 16 17 29 30 31 36 32 0 22 23 24 25 26 27 28 37 0];

Once objective function is called in the optimization, it gets the position of tap switch to be opened, we did it in MATLAB as

BrStatus=X(1:tie); [baseMVA,bus,branch,tie]=case33radial; % calling data from data file branch(:,5)=ones(numel(branch(:,5),1)); % open the tie switch of branch in BrStatus branch(BrStatus,5)=0;

The variable *‘X’* has the status of branch switches and we change the status of tap switch in the IEEE 33 bus data from 1 to 0. To understand it more clearly you must have a look over line data of the IEEE 33 bus system at free-thesis.com

%% Line Data % f t r(ohm) x(ohm) Status Ratio RateA branch=[... 1 2 0.0922 0.0477 1 0 9990 2 3 0.493 0.2511 1 0 9990 3 4 0.366 0.1864 1 0 9990 4 5 0.3811 0.1941 1 0 9990 5 6 0.819 0.707 1 0 9990 6 7 0.1872 0.6188 1 0 9990 7 8 1.7114 1.2351 1 0 9990 8 9 1.03 0.74 1 0 9990 9 10 1.04 0.74 1 0 9990 10 11 0.1966 0.065 1 0 9990 11 12 0.3744 0.1238 1 0 9990 12 13 1.468 1.155 1 0 9990 13 14 0.5416 0.7129 1 0 9990 14 15 0.591 0.526 1 0 9990 15 16 0.7463 0.545 1 0 9990 16 17 1.289 1.721 1 0 9990 17 18 0.732 0.574 1 0 9990 2 19 0.164 0.1565 1 0 9990 19 20 1.5042 1.3554 1 0 9990 20 21 0.4095 0.4784 1 0 9990 21 22 0.7089 0.9373 1 0 9990 3 23 0.4512 0.3083 1 0 9990 23 24 0.898 0.7091 1 0 9990 24 25 0.896 0.7011 1 0 9990 6 26 0.203 0.1034 1 0 9990 26 27 0.2842 0.1447 1 0 9990 27 28 1.059 0.9337 1 0 9990 28 29 0.8042 0.7006 1 0 9990 29 30 0.5075 0.2585 1 0 9990 30 31 0.9744 0.963 1 0 9990 31 32 0.3105 0.3619 1 0 9990 32 33 0.341 0.5302 1 0 9990 7 20 2.0 2.0 0 0 9990 8 14 2.0 2.0 0 0 9990 11 21 2.0 2.0 0 0 9990 17 32 2.0 2.0 0 0 9990 24 28 2.0 2.0 0 0 9990 ]; tie=5;

check out the 5th column, it has the last five rows zero as these have tie switches open. After optimization the position of these switches change which is after PSOGSA optimization

```
==========================================================================================
******************* SIMULATION RESULTS OF 33 BUS DISTRIBUTION NETWORK ********************
==========================================================================================
BEFORE RECONFIGURATION AFTER RECONFIGURATION by PSO AFTER RECONFIGURATION by PSOGSA
------------------------------------------------------------------------------------------------------------------------------------------------------
Tie switches: 33 34 35 36 37 10 6 14 31 28 35 6 13 36 28
------------------------------------------------------------------------------------------------------------------------------------------------------
DGs: 29.95 88.59 62.45 48.39 63.08 50.14 13.60 72.52 80.67 82.73 33.49 33.16
------------------------------------------------------------------------------------------------------------------------------------------------------
Power loss: 603.4308 kW 427.6137 kW 254.4125 kW
------------------------------------------------------------------------------------------------------------------------------------------------------
Power loss reduction: _______ 29.1363 % 57.839 %
--------------------------------------------------------------------------------------------------------------------------------------------------------
Minimum voltage: 0.83602 pu 0.94861 pu 0.94116 pu
---------------------------------------------------------------------------------------------------------------------------------------------------------
```

We have a *constraint* here, the change in tap position must respect the radial nature of the system. For this the new network must have determinant of branch injection branch current (BIBC) equal to zero. To calculate the BIBC, power flow analysis must be done for new reconfigured network.

[DistLoadFlowSolution,BIBC]=powerflow (baseMVA,bus,branch,loadlevel); % calling load flow analysis function % Check on constraint of radial distribution network %%%%% network will be radial if determinant of Branch incidence matrix will %%%%% be either 1 or -1 while det(BIBC)==0 for jj=1:dim maxL=length(nonzeros(ta(:,jj))); BrStatus(jj) = ta(round(1+(maxL-1)*rand),jj); end [baseMVA,bus,branch,tie]=case33radial; % calling data from data file branch(:,5)=ones(numel(branch(:,5),1)); % open the tie switch of branch in BrStatus branch(BrStatus,5)=0; [DistLoadFlowSolution,BIBC]=powerflow (baseMVA,bus,branch,loadlevel); % calling load flow analysis function end

The

whileloop will check and update the tap positions if radial condition is not met for current set of tap switches.

The distribution generators and its value is also calculated in the objective function. The position is calculated by sensitivity index method.In several research papers the position is also optimally calculated but that only increase the computation overhead, not the accuracy. We adopted the sensitivity index method and find out the buses with highest sensitivity to losses. All buses are arranged in decreasing order of their sensitivity factor and top 6 buses are selected for DG placement. The DG bus power is tuned by optimization and objective function gets the 6 power within range of 0-100 MVA. This power is subtracted from the selected six load buses at free-thesis.com.

bus(potentialbus,2)=bus(potentialbus,2)-DG;

The second column in *‘bus’* variable contains the IEEE33 bus data’s load values. The power flow analysis is done again and power loss is calculated. Optimization runs till all iterations are not exhausted. Finally by this approach we are able to get the 57.839% for 1.6 time loading in the IEEE 33 radial system.

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