This paper presents a new methodology for the optimal integrated planning of medium- and low-voltage distribution systems, considering the location and sizing of distributed generation. The integrated problem is formulated as a mixed-integer nonlinear model and, to solve it, two well-known optimization algorithms (simulated annealing and iterated local search) are used. The intensification and diversification processes are usually the bottleneck of metaheuristic techniques for solving complex problems. To overcome such complexity, a new neighborhood search method based on the Zbus matrix (NSZM) is proposed, to explore the solution space more efficiently and effectively for both algorithms. The proposed methodology is validated and tested on a real distribution system taken from the literature. The results obtained are better than those reported in the literature. To verify the efficiency of the new NSZM method, the Wilcoxon signed ranks test is used to measure the performance behavior of the NSZM method in the two optimization algorithms used. The numerical results demonstrate that the NSZM method enhances both algorithms equally.

En este artículo se propone una metodología para la compra y venta de energía que considera elementos almacenadores de energía en la operación de sistemas de distribución de energía eléctrica, y su objetivo es mejorar las utilidades del operador de red con un adecuado manejo de la curva de carga. En la formulación del problema son propuestos dos modelos matemáticos cuya función es minimizar el costo de compra de la energía eléctrica. El primer modelo (lineal) incluye la compra de energía y el segundo (no lineal) considera, además de lo anterior, las pérdidas técnicas de energía del sistema de distribución. Ambos modelos matemáticos consideran restricciones ope- rativas de los almacenadores de energía y de la red de energía eléctrica. La metodología propuesta puede ser usada por los operadores de red como una estrategia para la compra y venta de energía; además, proporciona una herramienta matemática que puede ser aplicada en la operación y el planeamiento de sistemas de distribución de energía, considerando elementos almacenadores de energía. La metodología propuesta es verificada empleando dos sistemas de prueba de diferente tamaño, con lo cual se obtienen resultados que corroboran un beneficio económico cuando se usan almacenadores de energía en la operación de los sistemas de distribución.

This study focuses on the optimal planning of secondary power distribution systems considering distributed renewable generators (DG) and energy storage systems (ESS) to minimize expansion costs. The methodology solves a mixed integer non-linear mathematical model that describes the planning problem, including the operating and technical aspects of the secondary power distribution system. Such methodology uses an iterated local search algorithm and a two-stage load flow decomposition method to solve said problem. The two-stage load flow decomposition method finds the optimal operation of the storage devices and the low-voltage distribution system for each solution proposed by the iterated local search algorithm; thus, optimal energy management is achieved for the best solution. The proposed methodology was tested on a real medium-sized secondary power distribution system to establish its effectiveness. The results obtained show a reduction of 51.97 % in the total energy purchase cost of the system and a decrease of 3.02 % in the installation costs of the secondary circuits and distribution transformers when DG and ESS are considered. In conclusion, the results show that the integration of these distributed energy resources into the distribution system planning problem increases the profits of distribution companies from energy purchase and sale and reduces their fixed costs.

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