This paper deals with the concept of the stochastic optimization methodology for power line designing, which allows optimizing transmission network planning. The paper presents a comparison of both methods applied for selecting the best line design alternative -the deterministic economic intervals method and the stochastic approach based method, taking into account market conditions. Both methods are utilized for designing overhead power lines, including the choice of main line parameters such as tower height, type and coordinates, conductor type and cross-section, line fittings, etc. Moreover, the use of High Temperature Low Sag conductors -a part of the advanced technology -was evaluated alongside the use of conductors of the traditional type. The optimization problem is formulated as minimization of the total annual costs. The proposed methodology is tested in the developed tool, which is realized in MATLAB software by using the Monte Carlo method, and in an overhead power line designing program -PLS-CADD. Two basic case studies for verifying the proposed power line planning solution are presented in the paper.

The distribution line planning task has become more complex due to several impacting factors. This paper presents a stochastic approach for implementing an optimization procedure with a statistical representation of the electricity prices, ambient temperature and load currents in the distribution network. The validation of this stochastic approach is based on the comparison results of both examined approaches (stochastic and deterministic), which are applied for the computation of the total average annual costs. Attention has been focused on reducing total average annual costs by optimizing the conductor profile of a power line and the transformer capacity. Thus, the Net Present Value of the total average annual costs can be evaluated during the planning period. The problem is formulated as a minimization of the Net Present Value of the total average annual costs of an examined distribution line project. The tool is implemented in MATLAB software by using the Monte Carlo method. The proposed stochastic approach has been applied in the solution of an example of a distribution line project, which is presented.

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