Biblio

The digitalization of the electric power industry and the development of territories isolated from the unified energy system are priorities in the development of the energy sector. Thanks to innovative solutions and digital technologies, it becomes possible to make more effective managing and monitoring. Such solution is IoT platform with intelligent control system implemented by software.

Technological developments in the energy sector while offering new business insights, also produces complex data. In this study, the relationship between smart grid and big data approaches have been investigated. After analyzing where the big data techniques and technologies are used in which areas of smart grid systems, the big data technologies used to detect attacks on smart grids have been focused on. Big data analytics produces efficient solutions, but it is more critical to choose which algorithm and metric. For this reason, an application prototype has been proposed using big data approaches to detect attacks on smart grids. The algorithms with high accuracy were determined as 92% with Random Forest and 87% with Decision Tree.

The energy sector has been actively looking into cyber risk assessment at a global level, as it has a ripple effect; risk taken at one step in supply chain has an impact on all the other nodes. Cyber-attacks not only hinder functional operations in an organization but also waves damaging effects to the reputation and confidence among shareholders resulting in financial losses. Organizations that are open to the idea of protecting their assets and information flow and are equipped; enough to respond quickly to any cyber incident are the ones who prevail longer in global market. As a contribution we put forward a modular plan to mitigate or reduce cyber risks in global supply chain by identifying potential cyber threats at each step and identifying their immediate counterm easures.

The successful operations of modern power grids are highly dependent on a reliable and ecient underlying communication network. Researchers and utilities have started to explore the opportunities and challenges of applying the emerging software-de ned networking (SDN) technology to enhance eciency and resilience of the Smart Grid. This trend calls for a simulation-based platform that provides sufcient exibility and controllability for evaluating network application designs, and facilitating the transitions from inhouse research ideas to real productions. In this paper, we present DSSnet, a hybrid testing platform that combines a power distribution system simulator with an SDN emulator to support high delity analysis of communication network applications and their impacts on the power systems. Our contributions lay in the design of a virtual time system with the tight controllability on the execution of the emulation system, i.e., pausing and resuming any speci ed container processes in the perception of their own virtual clocks, with little overhead scaling to 500 emulated hosts with an average of 70 ms overhead; and also lay in the ecient synchronization of the two sub-systems based on the virtual time. We evaluate the system performance of DSSnet, and also demonstrate the usability through a case study by evaluating a load shifting algorithm.