Distributed renewable energy systems (DRESs) and their interconnection network, typically using Internet-based protocols, are susceptible to a wide range of cybersecurity and resilience challenges. These challenges have been shown to cause problems for the overall grid optimization process. In order to detect such events, we argue that an adequate correlation between network and energy generation data is required. Therefore, in this study, we provide a work-in-progress insight related to the profiling of real network data and energy generation measurements gathered by a local windturbine at Lancaster University. We argue that such an analysis is very important to profile various attack vectors in the modern energy networks that consider DRESs and take necessary actions to prevent any data breaches in the future.