The energy system is in a transformation for a sustainable society. The overall targets are to meet climate goals and to reach energy independence. Wind turbines provide a main solution converting renewable energy resources into electricity with a resulting enormous global growth. A challenge is, however, to reduce the operation and maintenance costs for wind generation to ensure good investments. Asset management (AM) aims to handle assets in an optimal way in order to fulfil an organization’s goal whilst considering risk. This chapter proposes a novel method for AM and preventive maintenance using condition monitoring. The suggested model is an autoencoder-based anomaly detection method for tracking the condition of wind turbines. First, the technique uses supervisory control and data acquisition (SCADA) signals as its data input. The method then analyses the discrepancies between the acquired data from the SCADA system and the estimated values by the autoencoder models. The distribution of the output error is then calculated using the Kernel Density Estimation. Finally, a novel dynamic thresholding approach is employed to effectively extract anomalies in the data. The results show that the approach can identify significant irregularities before a breakdown happens. Additionally, it confirms that the method may notify operators of prospective changes in wind turbines even in the absence of alarm recordings.

This paper investigates methods to secure Remote Terminal Units (RTUs) which are the building blocks of a smart grid systems - the next generation version to replace the power grid systems that are being used today. RTUs are identified as the heart of automation and control (SCADA) systems by the systems engineers. As such, security and maintaining nominal operability of such devices has prime importance, especially for the industrial automation networks such as the smart grid. A way of measuring the security of systems and networks is executing a series of cybersecurity weakness assessment tests called penetration testing. Another way of such an assessment is called vulnerability analysis by threat modelling which involves careful investigation and modelling of each and every component of a network/system under investigation. This article, aims at marrying these two methodologies for the vulnerability assessment of the RTUs in a methodological and scientific way.

Carbon-neutral societies are moving closer tousing renewable electricity as their primary source of energy. Indeed, decarbonization, decentralization, and digitization areall aspects of a paradigm change in burgeoning power systems. Furthermore, the design, fault rate, load demand, and climate all have a role in the complexity of the electrical network. This research 1 looks at its use and deployment in network security, with a particular emphasis on the vulnerabilities of RTU frameworks. The necessity for risk management in today’s environment, the requirement for a networked power grid, and the hardware and software components of the SCADA system have been thoroughly examined. Finally, a literature review of interoperable power grids with detailed specifics of RTU deployment was provided.