Biblio
The inherent heterogeneity in the uncertainty of variable generations (e.g., wind, solar, tidal and wave-power) in electric grid coupled with the dynamic nature of distributed architecture of sub-systems, and the need for information synchronization has made the problem of resource allocation and monitoring a tremendous challenge for the next-generation smart grid. Unfortunately, the deployment of distributed algorithms across micro grids have been overlooked in the electric grid sector. In particular, centralized methods for managing resources and data may not be sufficient to monitor a complex electric grid. This paper discusses a decentralized constrained decomposition using Linear Programming (LP) that optimizes the inter-area transfer across micro grids that reduces total generation cost for the grid. A test grid of IEEE 14-bus system is sectioned into two and three areas, and its effect on inter-transfer is analyzed.
Primary user emulation (PUE) attack is one of the main threats affecting cognitive radio (CR) networks. The PUE can forge the same signal as the real primary user (PU) in order to use the licensed channel and cause deny of service (DoS). Therefore, it is important to locate the position of the PUE in order to stop and avoid any further attack. Several techniques have been proposed for localization, including the received signal strength indication RSSI, Triangulation, and Physical Network Layer Coding. However, the area surrounding the real PU is always affected by uncertainty. This uncertainty can be described as a lost (cost) function and conditional probability to be taken into consideration while proclaiming if a PU/PUE is the real PU or not. In this paper, we proposed a combination of a Bayesian model and trilateration technique. In the first part a trilateration technique is used to have a good approximation of the PUE position making use of the RSSI between the anchor nodes and the PU/PUE. In the second part, a Bayesian decision theory is used to claim the legitimacy of the PU based on the lost function and the conditional probability to help to determine the existence of the PUE attacker in the uncertainty area.