Purpose. In the present article, a new approach of the energy grid studies is introduced to program energy carriers. In this view, aproper plan is designed on the use of energy carriers considering the energy optimum use. Indeed, the proper energy grid is designed by applying Iran energy balance sheet information. It is proper to mention that, the energy grid modelling is done in a matrix form. The electrical energy distribution among power stations is achieved by using the particle swarm optimization algorithm. In the present paper, concerning the dynamic programming method, it is tried to determine a suitable combination of energy carriers. References 16, tables 17, figures 1. Key words: particle swarm optimization, final energy consumption, energy planning, energy carriers, dynamic programing. Цель. В настоящей статье предлагается новый подход к исследованию энергетических сетей для планирования энергоносителей. С этой целью разработан корректный план использования энергоносителей с учетом оптимального потребления энергии. Разработана соответствующая энергосистема с использованием информации о энергетическом баланса Ирана. Необходимо отметить, что моделирование энергосистемы выполняется в матричной форме. Распределение электрической энергии между электростанциями достигается за счет использования алгоритма оптимизации методом роя частиц. В настоящей работе, посвященной методу динамического программирования, предпринята попытка определить подходящую комбинацию энергоносителей.Библ. 16, табл. 17, рис. 1. Ключевые слова: оптимизация методом роя частиц, конечное потребление энергии, планирование в энергетике, энергоносители, динамическое программирование.

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Purpose. In this paper, for simultaneous placement of distributed generation (DG) and capacitors, a new approach based on Spring Search Algorithm (SSA), is presented. This method is contained two stages using two sensitive index Sv and Ss. Sv and Ss are calculated according to nominal voltage and network losses. In the first stage, candidate buses are determined for installation DG and capacitors according to Sv and Ss, Then in the second stage, placement and sizing of distributed generation and capacitors are specified using SSA. The spring search algorithm is among the optimization algorithms developed by the idea of laws of nature and the search factors are a set of objects. The proposed algorithm is tested on 33-bus and 69-bus radial distribution networks. The test results indicate good performance of the proposed method. References 30, tables 4, figures 4.

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One of the most powerful tools for solving optimization problems is optimization algorithms (inspired by nature) based on populations. These algorithms provide a solution to a problem by randomly searching in the search space. The design’s central idea is derived from various natural phenomena, the behavior and living conditions of living organisms, laws of physics, etc. A new population-based optimization algorithm called the Binary Spring Search Algorithm (BSSA) is introduced to solve optimization problems. BSSA is an algorithm based on a simulation of the famous Hooke’s law (physics) for the traditional weights and springs system. In this proposal, the population comprises weights that are connected by unique springs. The mathematical modeling of the proposed algorithm is presented to be used to achieve solutions to optimization problems. The results were thoroughly validated in different unimodal and multimodal functions; additionally, the BSSA was compared with high-performance algorithms: binary grasshopper optimization algorithm, binary dragonfly algorithm, binary bat algorithm, binary gravitational search algorithm, binary particle swarm optimization, and binary genetic algorithm. The results show the superiority of the BSSA. The results of the Friedman test corroborate that the BSSA is more competitive.