Probabilistic Graphical Models

A smart grid (SG) consists of many subsystems and networks, all working together as a system of systems, many of which are vulnerable and can be attacked remotely. Therefore, security has been identified as one of the most challenging topics in SG development, and designing a mutual authentication scheme and a key management protocol is the first important step. This paper proposes an efficient scheme that mutually authenticates a smart meter of a home area network and an authentication server in SG by utilizing an initial password, by decreasing the number of steps in the secure remote password protocol from five to three and the number of exchanged packets from four to three. Furthermore, we propose an efficient key management protocol based on our enhanced identity-based cryptography for secure SG communications using the public key infrastructure. Our proposed mechanisms are capable of preventing various attacks while reducing the management overhead. The improved efficiency for key management is realized by periodically refreshing all public/private key pairs as well as any multicast keys in all the nodes using only one newly generated function broadcasted by the key generator entity. Security and performance analyses are presented to demonstrate these desirable attributes.

Efficient Authentication and Key Management Mechanisms for Smart Grid Communications

Advanced metering infrastructure (AMI), as the totality of systems and networks to measure, collect, store, analyze, and use energy usage data, is supposed to be the core component in smart grid. In AMI, there are numerous challenges among which cyber security is a major one that needs to be addressed with priority. The information centric networking (ICN) is a promising architecture for the future Internet that disseminates content based on named data instead of named hosts. The congestion control and self-security can enable more scalable, secure, collaborative, and pervasive networking, these make the ICN a potential network architecture for smart grid. This paper aims to apply the ICN approach on AMI system, which we termed as information centric AMI (ICN-AMI). To the best of our knowledge, this is the first attempt to distribute contents (or requests for contents) based on ICN in AMI system. Moreover, a simulation-based performance evaluation is employed to evaluate the effectiveness of the proposed ICN-AMI approach in traffic control for developing AMI system in smart grid. In addition, we proposed a novel key management scheme (KMS) for a large number of smart meters in this system to ensure confidentiality, integrality, and authentication. To validate the scheme, the security analysis, comparisons are done to demonstrate that the proposed information centric KMS (ICN-KMS) is possible and a promising solution for ICN-AMI system.

A Key Management Scheme for Secure Communications of Information Centric Advanced Metering Infrastructure in Smart Grid

Smart grids are evolving as the next generation power systems that transform the traditional ways of functioning of present electrical grids. Advanced metering infrastructure (AMI) is one of the key components in smart grids. An AMI comprises of systems and networks, that are responsible for collecting and analyzing data received from smart meters. In addition, AMI also manages the different applications related with power and services based on the data collected from smart meters. Thus, AMI plays a significant role in the smooth functioning of smart grids. Malicious adversaries have immense opportunities for attacking the AMI, as it is made up of systems that are highly vulnerable to such attacks. Providing security to AMI is necessary as adversaries can cause potential infrastructural damage and privacy threats in smart grid. One of the most effective and challenging topic’s identified, is the key management system (KMS), for sustaining the security concerns in AMI. Therefore, KMS seeks to be a promising research area for future development of AMI. To the best of our knowledge, this survey is the first to highlight the significance of KMS for the security point of view for AMI in smart grids. We believe that we have taken here the needed initiatives that will help understand the importance of key management in AMI security, and strengthen future research works carried out in this area. This survey highlights the key security issues of AMIs and focuses on how key management techniques can be utilized for safeguarding AMI. At first, we discuss the main features of AMIs, the deployment scenario of smart grids and identify the relationship between smart grid and AMI. Then, we explore the main features of AMI, and also introduce the security issues and challenges. We also provide a discussion on the role of key management in AMI, and point out the differences between traditional electrical systems and smart grids. We then classify and provide a review of the existing works in literature that deal with secure KMS in AMI. Finally, we summarize the possible future open research issues and challenges of KMS in AMI.

Key Management Systems for Smart Grid Advanced Metering Infrastructure: A Survey

Security is fundamental to the operation of smart grid and its advanced metering infrastructure (AMI). Key establishment is the core component in key management schemes and plays a crucial role in satisfying the security requirements. In recent years, many key establishment protocols have been proposed in the context of smart grids. However, their high overhead and complexity have undermined their ability to be practically employed in AMI. In this paper, we propose a novel identity-based key establishment protocol which employs elliptic curves at its core and has the lowest computational overhead among current secure protocols, especially at the meter side. We have given a detailed and comparative analysis of both security and computational burden for the proposed protocol as well as the previous efforts. We have evaluated the resilience of different protocols to well-known attacks by discussion, however, for the proposed protocol, we have also used AVISPA tool to formally verify its security. Compared to the previous solutions, the proposed protocol either is more secure or scores higher in performance benchmarks run on the same hardware.

A Novel Identity-Based Key Establishment Method for Advanced Metering Infrastructure in Smart Grid

Load flow is an important tool used by power engineers for planning, to determine the best operation for a power system and exchange of power between utility companies. In order to have an efficient operating power system, it is necessary to determine which method is suitable and efficient for the system’s load flow analysis. A power flow analysis method may take a long time and therefore prevent achieving an accurate result to a power flow solution because of continuous changes in power demand and generations. This paper presents analysis of the load flow problem in power system planning studies. The numerical methods: Gauss-Seidel, Newton-Raphson and Fast Decoupled methods were compared for a power flow analysis solution. Simulation is carried out using Matlab for test cases of IEEE 9-Bus, IEEE 30-Bus and IEEE 57-Bus system. The simulation results were compared for number of iteration, computational time, tolerance value and convergence. The compared results show that Newton-Raphson is the most reliable method because it has the least number of iteration and converges faster.

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Analysis of the Load Flow Problem in Power System Planning Studies

Electricity grids must cope with rising demand and complexity in a changing world. Smart grid is a promising solution to address these challenges. Recently, Advanced Metering Infrastructure (AMI) is proposed as an integral part of the smart grid that collect and analyze the measurements of energy consumption using the communication network that links the smart meters. The cyber security issues in AMI become very important to guarantee the trustworthiness of the AMI. In order to achieve data confidentiality, privacy and authentication in AMI, security measures using various crypto algorithms will be needed, thus demand key distribution and management schemes. Since the number of electric appliances and devices need to be monitored in households and commercial facilities is large and the devices may have limited computational power and storage, thus novel key distribution and management schemes would be indispensable for the success of securing AMI from cyber attacks. In this work, we propose a light-weight key distribution and management scheme tailored to AMI. Specifically, a group ID based mechanism is proposed to establish the keys for a large amount of entities with small overhead. Security analysis is performed to evaluate the proposed method.

Light-weight key distribution and management for Advanced Metering Infrastructure

In future wireless systems, efficient spectrum usage enabled by technologies such as cognitive radio (CR), dynamic spectrum access, non-orthogonal multiuser within licensed and unlicensed band requires knowledge of prevalence situation in a frequency band through learning. It is critical for wireless devices to identify the type and number of users and their waveforms in a frequency band at a given time. In this paper, this problem is formulated as a multi-class classification problem for accurate spectrum situation prediction under complicated coexistence scenarios. Deep learning is chosen for obtaining the statistics of the different coexisting wireless systems through learning from superimposed radio frequency (RF) data. Specifically, Deep Neural Network (DNN), Convolutional Neural Network (CNN) and Long Short Term Memory (LSTM) are adopted and designed. They are trained using real RF traces for different coexisting scenarios collected from a USRP based testbed to identify the presence of signals with varying levels of Signal to Noise Ratio, even when the signal is superimposed with other signals as sources of interference. Experimental results demonstrate the potential of deep learning for spectrum situation prediction under complicated coexistence scenarios.

Spectrum Occupancy Prediction in Coexisting Wireless Systems Using Deep Learning

Hybrid organic-inorganic perovskite solar cells have attracted the attention of researchers and scientists throughout the world. From 2009, when actual research work began on photovoltaic perovskite applications, a lab power conversion efficiency above 23.3% have been achieved. Whereas, silicon solar cells have only achieved power conversion efficiencies around 17.5% in both residential and commercial applications. A typical perovskite solar cell consists of 6 main layers of different materials: a glass layer, a thin layer of fluorine-doped tin oxide substrate (FTO), an electron transport layer of TiO2, a perovskite active layer known as methylammonium lead iodide (CH3NH3PbI3), a hole transport layer of Spiro-Ometad, and a gold (Au) electrode. This paper summarizes the research that focused on the selective use of the perovskite solar cell’s composite materials, specifically, the Spiro-Ometad layer, the methylammonium lead iodide layer (CH3NH3PbI3), and the TiO2 layer with a variation of the thickness of the perovskite layer. Initial simulation results show a power conversion efficiency of 20.34% when using a gold (Au) electrode. Further research is needed, in which new technology for device fabrication will create homogeneous thin-film layers that will be tested for increased efficiency.

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Simulation and Analysis of Methylammonium Lead Iodide (CH 3 NH 3 PbI 3 ) Perovskite Solar Cell with Au Contact Using SCAPS 1D Simulator

Many different photovoltaic technologies are being developed for better solar energy conversion. Until now, crystalline Si solar cell represents the dominant photovoltaic technology with a market share of more than 94% with an efficiency between (15%-20%). Organic-inorganic halide Perovskite Solar Cell (PSC) has emerged as the most promising candidate for the next generation high-efficiency solar cell technology that attracted interest from researchers around the world due to their high efficiency of more than 24.% in a short period from (2008-2019) and low fabrication cost. In this paper, we designed a lead-based PSC model with a cell structure of Glass/FTO/TiO2/CH3NH3PBI3/Spiro-OMeTAD/(Au, Ag, Al, Cu, Cr, Cu-graphite alloy, and Pt) and analyzed the structure with different contact materials using Solar Cell Capacitance Simulator (SCAPS-1D) which is well adopted by many researchers to study and analyze the hybrid solar cell. Using the software allows researchers to inexpensively and promptly, the effect of the absorber and the contact materials on the performance of the proposed solar cell model. We also studied the bandgap of the active layer, defect density, thickness, operating temperature, and the fabrication method of the model. Furthermore, the adoption of multibeam multi-target MAPLE and PLD or with acronym MBMT-MAPLE/PLD techniques as a new fabrication method in our simulation program mentioned above. A promising result was achieved. Efficiencies of 27.25%, 26.52%, 18.90%, 25.66%, 22.77%, 27.25%, and 27.25% were obtained for the devices with Au, Ag, Al, Cu, Cr, Pt, and Cu-graphite alloy, respectively. The effect of the work function on the back contact has a significant influence over the FF and efficiency.

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Simulation and Analysis Method of Different Back Metals Contact of CH 3 NH 3 PbI 3 Perovskite Solar Cell Along with Electron Transport Layer TiO 2 Using MBMT-MAPLE/PLD

John Fuller

Papers

Analysis of the Load Flow Problem in Power System Planning Studies

Light-weight key distribution and management for Advanced Metering Infrastructure

Spectrum Occupancy Prediction in Coexisting Wireless Systems Using Deep Learning

Simulation and Analysis of Methylammonium Lead Iodide (CH 3 NH 3 PbI 3 ) Perovskite Solar Cell with Au Contact Using SCAPS 1D Simulator

Simulation and Analysis Method of Different Back Metals Contact of CH 3 NH 3 PbI 3 Perovskite Solar Cell Along with Electron Transport Layer TiO 2 Using MBMT-MAPLE/PLD