# Influence of Load Dynamics on Converter-Dominated Isolated Power Systems
## 1 Introduction
Composite load models consist in a combination of static and dynamic load models, and some authors state that these models could provide more accurate responses [11; 12]. An alternative method to modeling nonlinear loads consists in taking advantage of artificial neural networks for load representations under a black-box modeling approach. This method perceives the system behavior without the need for a physical model to calculate the output [11; 13]. With the wide development of the smart grid concept, the need for developing load models with the ability of incorporating the changes in power consumption in response to the customer behavior also emerged. Therefore, some authors proposed load models which incorporate the impact of demand side management. Such models are designed based on their physical characteristics and can be controlled to reflect the desired demand response strategy [11; 14]. In recent years, due to large-scale integration of distributed generation in distribution grids, some authors focused on developing aggregated models of active distribution networks in the face of the transmission grid exploiting \"black-box\" and \"gray-box\" approaches. In \"black-box\" modeling, the physical structure of the equivalent model is not considered, contrarily to the \"gray-box\" approach [11; 15]. In [15], the authors proposed a \"gray-box\" aggregated dynamic model for active distribution networks, which is composed of an equivalent power converter, an equivalent synchronous generation unit and an equivalent load model. The aim of the proposed model is to represent the transient behavior of the distribution network following large voltage disturbances. Recent works available in the literature addressing the impacts of load modeling lie within the scope of microgrids (MG) [16; 17; 18; 19; 20]. The relevance of proper load modeling in MG dynamics following events such as switching operations, loss of generating units and the starting of IM is discussed in [16]. In [17] the authors investigated the influence of IM in the stability of an islanded MG dominated by converter-based generation, in contrast to a case where the load is represented by static models. The authors conclude that the inclusion of IM in load modeling is of major importance to assess the network oscillatory behavior and the load margin with adequate accuracy. A similar study was performed in [18], where the stability of an islanded MG with both static and dynamic load models was analyzed. It was concluded that the interaction between the two types of loads may lead to unstable conditions. In [19], the stability of medium-voltage megawatt scale MG with IM loads was studied, and they operated with 100% converter-interfaced generation. In order to eliminate the oscillatory behavior induced by the IM loads, a damping control loop was proposed to be added to the well-known droop-controlled MG. Regarding the dynamic stability, an analysis was performed in [20] aiming to evaluate the load composition and parametrization effect, considering both static and dynamic loads. The case study consisted in a medium-voltage MG, where a fault followed by an unpredicted islanding event was considered (a slight voltage drop of 0.2 p.u. was simulated). In such conditions, the authors concluded that increasing the share of IM loads has a beneficial effect due to their inertia, thus contributing to improving the frequency behavior in the moments subsequent to the islanding. A methodology for the real-time identification of the exponential dynamic load model parameters based in real data measurement was proposed in [21]. The proposed real-time estimation of exponential load parameters is preferred in comparison with the aggregate load model (augmented with IM loads) as the number of parameters to be identified precludes real-time application. The transient response of individual loads can directly impact the frequency and voltage stability of systems with low or non-inexistent synchronous inertia.