Hosting Capacity for Renewable Generations in Distribution Grids

abstract: Nowadays, the widespread introduction of distributed generators (DGs) brings great challenges to the design, planning, and reliable operation of the power system. Therefore, assessing the capability of a distribution network to accommodate renewable power generations is urgent and necessary. In this respect, the concept of hosting capacity (HC) is generally accepted by engineers to evaluate the reliability and sustainability of the system with high penetration of DGs. For HC calculation, existing research provides simulation-based methods which are not able to find global optimal. Others use OPF (optimal power flow) based methods where too many constraints prevent them from obtaining the solution exactly. They also can not get global optimal solution. Due to this situation, I proposed a new methodology to overcome the shortcomings. First, I start with an optimization problem formulation and provide a flexible objective function to satisfy different requirements. Power flow equations are the basic rule and I transfer them from the commonly used polar coordinate to the rectangular coordinate. Due to the operation criteria, several constraints are incrementally added. I aim to preserve convexity as much as possible so that I can obtain optimal solution. Second, I provide the geometric view of the convex problem model. The process to find global optimal can be visualized clearly. Then, I implement segmental optimization tool to speed up the computation. A large network is able to be divided into segments and calculated in parallel computing where the results stay the same. Finally, the robustness of my methodology is demonstrated by doing extensive simulations regarding IEEE distribution networks (e.g. 8-bus, 16-bus, 32-bus, 64-bus, 128-bus). Thus, it shows that the proposed method is verified to calculate accurate hosting capacity and ensure to get global optimal solution.Dissertation/ThesisMasters Thesis Electrical Engineering 201

Application for technical evaluation of the "Distributed Generation Hosting Capacity" in electrical distribution networks

The increase installation of Distributed Generation (DG) in distribution networks brings benefits to their operation, when the DG units are correctly located and well dimensioned. Nevertheless, an excessive penetration in inappropriate locations, can lead to operational problems. This article presents a computational tool that comprehensively evaluates the maximum GD (kW) capacity to be connected to a network in order to ensure satisfactory operation. The technique used consists of a systematic DG insertion procedure and verification of the electrical parameters of the network (with gradual injection increments). In other words, this application makes it possible to anticipate problems that could appear due to the insertion of new DG, as a tool that supports the planning of distribution networks. The programming was developed in free software: Python and OpenDSS. Particularly, this tool creates photovoltaic generators (PVSystem) and connects them in different locations under two alternatives: randomly selected nodes or a nodes list entered by the user. The engineer/planner can determine the amount of nodes where DG connection is possible, percentage of insertion and the number of evaluation days (N Montecarlo cases). Furthermore, the application allows simulating the uncertainty in demand and generation. In the several simulation modes, an evaluation of currents through the lines and voltages in the buses reflect the performance of the network, energy losses and harmonic distortion indices. As results, the tool shows graphs and tables in pop-up screens. Additionally, a report is generated in * .csv format.En este artículo se presenta una herramienta computacional que evalúa de forma integral la capacidad máxima de GD (kW) que puede conectarse a una red para que funcione satisfactoriamente. La técnica utilizada consiste en un procedimiento sistemático de inserción de GD y verificación de los parámetros eléctricos de la red (con incrementos graduales de inyección). En otras palabras, esta aplicación permite anticiparse a los problemas que podrían aparecer debido a la inserción de nueva GD, como una herramienta para apoyar la planificación de redes de distribución. La programación ha sido desarrollada en software libre: Python y OpenDSS.En particular, la herramienta crea generadores fotovoltaicos (PVSystem) y los conecta en diferentes ubicaciones bajo dos alternativas: en barras seleccionadas aleatoriamente o en un listado de barras ingresadas por el usuario. El usuario (planificador) determina: cantidad de barras en las que puede conectarse GD, porcentaje de inserción y número de días de evaluación (N casos de Montecarlo). Además, la aplicación permite simular la incertidumbre en la demanda y la generación. En los diferentes modos de simulación se evalúan corrientes a través de las líneas y voltajes en las barras que reflejan el desempeño de la red, además de las pérdidas de energía e índices de distorsión armónica. Como resultados se presentan gráficos y tablas en pantallas emergentes; además, se genera un informe en formato *.csv.Fil: Lechón, Luis F.. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan. Instituto de Energía Eléctrica. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Energía Eléctrica; ArgentinaFil: Samper, Mauricio Eduardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan. Instituto de Energía Eléctrica. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Energía Eléctrica; ArgentinaFil: Baron, Gustavo Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan. Instituto de Energía Eléctrica. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Energía Eléctrica; Argentin