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alt="images"/> are the lower and upper limits of the discrete variables, in the hypercube. In the hypercube, the lower and upper limit can be defined by floor and ceiling functions as presented in (Equation 1.9) and (Equation 1.10), respectively.

      where, images is the discrete version of the continuous variable Xij. To restrict the variables within the boundary of minimum and maximum limit the same procedure may be used as used in the conventional SPBO algorithm.

      1.3.1 Objective Functions

      (a) Power Loss Index (PLI)

      The images are the active power loss after and before the placement of RDGs and shunt capacitors, respectively, at the time instant t.

      Here, images are the voltage magnitude and the load angle after inserting the DGs and shunt capacitors.

      (b) Voltage Deviation Index (VDI)

      Improvement in the voltage profile in the distribution network is measured by voltage deviation from the nominal voltage of 1.0 pu. The voltage deviation index is measured as the ratio of the voltage deviations (VDs) after and before the placement of the RDGs and shunt capacitors which are defined for the time instant t as

      (1.17)image

      where VDDG is defined as

      (1.18)image

      (1.19)image

      Here, images are the voltage of ith bus after and before placement of DG to the distribution network. The value of voltage deviation near zero indicates an improved voltage profile.

      (c) Installation Cost Index (ICI)

      Total installation cost includes the cost of the RDGs and the shunt capacitors. Lifetime (LT) of the RDGs and the shunt capacitors are used to obtain the annual installation cost. The ICI is defined as

      (1.20)image

      Here, CostDG(t) is the effective annual installation cost of the DGs and shunt capacitors at time instant t, and can be defined as

      (1.21)image

      and the installation cost, considering the maximum sizes of DGs and shunt capacitors, is defined as

      (1.22)image

      In this book chapter, equal preference is given to each objective function in the weighted sum approach. Therefore, the weights for the three objective functions are images

      1.3.2 Technical Constraints Considered

      The minimization of the weighted average of the three objective functions is subjected


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