As the installation of solar-photovoltaic and wind-generation systems continue to grow, the location must be strategically selected to maintain a reliable grid. However, such strategies are commonly subject to system adequacy constraints, while system security constraints (e.g., frequency stability, voltage limits) are vaguely explored. This may lead to inaccuracies in the optimal placement of the renewables, and thus maximum benefits may not be achieved. In this context, this paper proposes an optimization-based mathematical framework to design a robust distributed generation system, able to keep system stability in a desired range under system perturbance. The optimum placement of wind and solar renewable energies that minimizes the impact on system stability in terms of the standard frequency deviation is obtained through particle swarm optimization, which is developed in Python and executed in PowerFactory-DIgSILENT. The results reveal that the proposed approach has the potential to reduce the influence of disturbances, enhancing critical clearance time before frequency collapse and supporting secure power system operation.
El este artículo se trabajó bajo un diseño de micro-red híbrida que incluye generación fotovoltaica y red eléctrica para realizar un análisis de estabilidad de la respuesta de la micro-red considerando escenarios de operación aislada y conectada a la red red. La metodología de análisis de estabilidad se desarrolló utilizando el software ETAP, a partir del modelado y simulación de 4 casos correspondientes a distintos escenarios de operación de la micro-red de carga concentrada de 400 kW, en los que se identificó las posibles fallas de estabilidad. Finalmente se probó y resolvió el peor tipo de falla ocurrida, determinando que el sistema fotovoltaico no influye en la estabilidad en operación aislada, adjudicando la inestabilidad a los dispositivos auxiliares de la red, y a la rapidez de respuesta de los mismos a las fallas. Se concluyó que el tiempo de despeje crítico y el ángulo de despeje crítico de la falla son cruciales para saber si un sistema de energía eléctrica podrá volver a una condición estable o volverse inestable.
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