Background: Environmental health has become a worldwide debating issue among researchers,
scientists, and governments. Although fossil fuels have been the greatest energy resources
for the human, their consumption leads to injecting greenhouse gases into the air, which
can affect the existence of all living species dramatically. In fact, fossil fuels consumption pollutes
the environment because of the injection of greenhouse gases which result in global warming. On
the other hand, reductions in fossil fuel and drinking water resources have highlighted the importance
of energy management and loss reduction in brand-new management strategies and manufacturing
methods. Distribution transformers are one of the most used devices in power distribution
networks. Hence, it seems to be logical to consider transformer losses as a definitive factor in
design and construction procedures. Furthermore, such design procedures require powerful tools
to solve complex non-linear equations and find the best solutions in the shortest time. Researchers
and scientists have always had a great challenge regarding finding the best solutions for their
analysis. In actuality, it is hard to solve complex non-linear problems by means of traditional calculation
methods even if a researcher employs a powerful computer. For this reason, metaheuristic
optimization algorithms have found great popularity among scientists. These algorithms
seek the best solution through a solution pool at an appropriate pace. Therefore, a researcher can
save more time and energy in solving an intricate problem.
Objective: In this paper, the authors aim to modify the conventional Teaching-Learning Based
Optimization (TLBO) algorithm to design an optimum distribution transformer by consideration
of the transformer Total Owning Cost (TOC). The TOC consists of operational and initial manufacturing
costs of a distribution transformer. The used raw materials affect the manufacturing cost
and it would be decreased if the copper and iron volumes are reduced in the construction instruction.
However, the operational cost that includes iron and copper losses must not be forgotten in
design analysis. Indeed, loss consideration is of great significance to keep energy from frittering
away and as a result, protects environmental resources.
Materials and Methods: A novel approach based on an optimization technique for distribution
transformer design problems is presented in this paper. The entire expenses of a transformer consist
of transformer construction and operating costs. In other words, by reducing copper and iron
volumes, the initial cost of a transformer will be decreased. Due to the electromagnetic and electrical
losses in transformers, the initial cost of a transformer is not its entire design problem and
the operating cost must be considered in the design algorithm. Appropriate limits on efficiency,
voltage regulation, temperature rise, no-load current and winding fill factor are the constraints on
the transformer design problems in the international standards. With respect to these constraints,
the transformer designer can minimize the volume of the core and windings. In this paper, the
Conditional Teaching-Learning Based Optimization (CTLBO) algorithm determines the appropriate
transformer properties, while transformer construction cost and its operating cost are selected
as an objective function for optimization method. In order to attain a suitable voltage regulation,
transformer impedance is chosen as an optimization constraint.
Results: The result of the paper demonstrates the proposed algorithm ability in reducing the Total
Owning Cost (TOC) during transformer lifetime, which could be useful for energy distribution
companies. In addition, the result analysis proves that the total losses of the transformer are reduced
by the proposed approach in comparison to conventional design techniques. Then, more energy
will be saved in the power grid when the proposed transformer is utilized in the power network.
Conclusion: In this paper, a suitable method to design an optimum distribution transformer is
proposed which enables manufacturers to construct their product based on the proposed method.
In this way, it can be claimed that not only more money will be saved during the transformer operation,
but also the energy consumption will be decreased drastically. Therefore, world resources
will remain for future generations.