A Heterogeneous Communications Network for Smart Grid by Using the Cost Functions

Smart Grids (SG) is an intelligent power grid in which the different SG node types with different communication requirements communicates different types of information with Control Stations (CS). Radio Access Technologies (RATs) due to its advantages are considered as the main access method to be used in order to have bidirectional data transferring between different node types and CS. Besides, spectrum is a rare source and its demand is increasing significantly. Elaborating a heterogeneous in order to fulfill different SG node types communication requirements effectively, is a challenging issue. To find a method to define desirability value of different RAT to support certain node types based on fitness degree between RAT communication characteristics and node type communication requirements is an appropriate solution. This method is implemented by using a comprehensive Cost Function (CF) including a communication CF (CCF) in combination with Energy CF (ECF). The Key Point Indicators which are used in the CCF are SG node type communication requirements. The existing trade of between Eb/N0 and spectral efficiency is considered as ECF. Based on the achieved CCF and ECF and their tradeoffs, SG node types are assigned to different RATs. The proposed assigning method is sensitive to the SG node types densities. The numerical results are achieved by using MATLAB simulation. The other different outcomes of the research output such as cognitive radio in SG and collectors effect number on data aggregation are discussed as well

Secure Control and Operation of Energy Cyber-Physical Systems Through Intelligent Agents

The operation of the smart grid is expected to be heavily reliant on microprocessor-based control. Thus, there is a strong need for interoperability standards to address the heterogeneous nature of the data in the smart grid. In this research, we analyzed in detail the security threats of the Generic Object Oriented Substation Events (GOOSE) and Sampled Measured Values (SMV) protocol mappings of the IEC 61850 data modeling standard, which is the most widely industry-accepted standard for power system automation and control. We found that there is a strong need for security solutions that are capable of defending the grid against cyber-attacks, minimizing the damage in case a cyber-incident occurs, and restoring services within minimal time. To address these risks, we focused on correlating cyber security algorithms with physical characteristics of the power system by developing intelligent agents that use this knowledge as an important second line of defense in detecting malicious activity. This will complement the cyber security methods, including encryption and authentication. Firstly, we developed a physical-model-checking algorithm, which uses artificial neural networks to identify switching-related attacks on power systems based on load flow characteristics. Secondly, the feasibility of using neural network forecasters to detect spoofed sampled values was investigated. We showed that although such forecasters have high spoofed-data-detection accuracy, they are prone to the accumulation of forecasting error. In this research, we proposed an algorithm to detect the accumulation of the forecasting error based on lightweight statistical indicators. The effectiveness of the proposed algorithms was experimentally verified on the Smart Grid testbed at FIU. The test results showed that the proposed techniques have a minimal detection latency, in the range of microseconds. Also, in this research we developed a network-in-the-loop co-simulation platform that seamlessly integrates the components of the smart grid together, especially since they are governed by different regulations and owned by different entities. Power system simulation software, microcontrollers, and a real communication infrastructure were combined together to provide a cohesive smart grid platform. A data-centric communication scheme was selected to provide an interoperability layer between multi-vendor devices, software packages, and to bridge different protocols together