What is it about?

A single objective nonlinear-constrained GA methodology is proposed for the optimal allocation and sizing of renewable energy-based DGs. The main objective is to minimise power losses while satisfying system’s constraints within a specified tolerance such as power balance, voltage level, maximum power flow and maximum DG size. The optimisation problem is solved through combining the objective function and the nonlinear constraints by using the augmented Lagrangian genetic algorithm (ALGA).

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Why is it important?

The advantage of the applied method is that instead of expecting penalty factor which will affect the results, an initial value is assumed and the programme increases it during the programme running mode to obtain best and fast convergence to the optimal solution. The optimisation method is carried out considering different scenarios of single and multiple DG allocation.


The proposed algorithm is very useful for single and multiple DG allocation. Multiple DG allocation causes more enhancement of voltage profile across the distribution system and more reduction in power losses especially in the case of large systems. WTG allocation provides better improvements for all systems due to reactive power compensation as it was selected to operate at 0.95 PF lag. The overall results show the importance of choosing the appropriate size and location of DG to enhance the performance of power systems such as providing an opportunity for power system voltage support, reducing power losses and improving system reliability.

Dr. Amal A. Hassan
Electronics Research Institute

Read the Original

This page is a summary of: Genetic single objective optimisation for sizing and allocation of renewable DG systems, International Journal of Sustainable Energy, June 2015, Taylor & Francis,
DOI: 10.1080/14786451.2015.1053393.
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