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A Novel Dynamic Load Modeling for Power Systems Restoration: An Experimental Validation on Active Distribution Networks

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In this paper, a novel approach to assess the power demand of distribution networks during a restoration process following an outage is presented. The possibility of correctly estimating such power… Click to show full abstract

In this paper, a novel approach to assess the power demand of distribution networks during a restoration process following an outage is presented. The possibility of correctly estimating such power demand represents a very important support in the choice and management of reliable restoration paths which significantly contributes to increase the resilience of the power system. In fact, due to the ever-growing penetration of renewable energy sources in the worldwide networks, electrical systems are often pushed to operate closer to their design limits and so, in particular conditions, black outs can be more frequent compared to the past. In this context, the aim of this work is to develop a general expression which can consider and represent all the key elements which affect the active and reactive power demand of distribution grids during the restoration process. The proposed method considers also the relationship between distributed generation and frequency behaviour in the power demand estimation. This aspect is generally neglected in literature although it has a significative impact. The effectiveness of the present approach is experimentally demonstrated on field. More specifically, the developed tool is applied to estimate the power demand of two real distribution networks and the tool results are compared with on-field recordings. This comparison demonstrates that the proposed approach represents a promising tool which, together with the restoration tests, could be an important ally in the design and management of the restoration plan of electrical networks.

Keywords: restoration; distribution networks; power demand; power

Journal Title: IEEE Access
Year Published: 2022

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