Paul Moulema

Toward Integrating Distributed Energy Resources and Storage Devices in Smart Grid

The smart grid, as one of typical applications supported by Internet of Things, denoted as a re-engineering and a modernization of the traditional power grid, aims to provide reliable, secure, and efficient energy transmission and distribution to consumers. How to effectively integrate distributed (renewable) energy resources and storage devices to satisfy the energy service requirements of users, while minimizing the power generation and transmission cost, remains a highly pressing challenge in the smart grid. To address this challenge and assess the effectiveness of integrating distributed energy resources and storage devices, in this paper, we develop a theoretical framework to model and analyze three types of power grid systems: 1) the power grid with only bulk energy generators; 2) the power grid with distributed energy resources; and 3) the power grid with both distributed energy resources and storage devices. Based on the metrics of the power cumulative cost and the service reliability to users, we formally model and analyze the impact of integrating distributed energy resources and storage devices in the power grid. We also use the concept of network calculus, which has been traditionally used for carrying out traffic engineering in computer networks, to derive the bounds of both power supply and user demand to achieve a high service reliability to users. Through an extensive performance evaluation, our evaluation results show that integrating distributed energy resources conjointly with energy storage devices can reduce generation costs, smooth the curve of bulk power generation over time, reduce bulk power generation and power distribution losses, and provide a sustainable service reliability to users in the power grid.

A cloud computing based system for cyber security management

The exponential increase of cyber security has led to an ever-increasing accumulation of big network data for cyber security applications. The big data analysis for cyber security management presents challenges in data capturing, storing and processing. To address these challenges, in this paper we develop a cloud computing based system for cyber security management to fasten the analysis process of big network data. Our developed system is built on the MapReduce framework and consists of end-user devices, cloud infrastructure and a monitoring centre. To make our proposed system efficient, we introduce two key function modules of our system: data storage module and task scheduling module. We conduct the system implementation using Apache Hadoop, and our implemented system consists of data collection, data normalisation, data computation and data visualisation. Using ranking and aggregation as primitives for performing cyber security management, we conducted extensive experiments to show the effectiveness of our developed system. We also discuss how to extend our proposed system to other applications.

A Novel En-route Filtering Scheme against False Data Injection Attacks in Cyber-Physical Networked Systems

In Cyber-Physical Networked Systems (CPNS), the adversary can inject false measurements into the controller through compromised sensor nodes, which not only threaten the security of the system, but also consume network resources. To deal with this issue, a number of en-route filtering schemes have been designed for wireless sensor networks. However, these schemes either lack resilience to the number of compromised nodes or depend on the statically configured routes and node localization, which are not suitable for CPNS. In this paper, we propose a Polynomial-based Compromise-Resilient En-route Filtering scheme (PCREF), which can filter false injected data effectively and achieve a high resilience to the number of compromised nodes without relying on static routes and node localization. PCREF adopts polynomials instead of Message Authentication Codes (MACs) for endorsing measurement reports to achieve resilience to attacks. Each node stores two types of polynomials: authentication polynomial and check polynomial, derived from the primitive polynomial, and used for endorsing and verifying the measurement reports. Through extensive theoretical analysis and experiments, our data shows that PCREF achieves better filtering capacity and resilience to the large number of compromised nodes in comparison to the existing schemes.

A cloud computing based architecture for cyber security situation awareness

The exponential growth of cyber space has created opportunities for world-wide web-based businesses and information sharing, but also led to the proliferation of cyber attacks. To conduct the cyber security situation awareness, a large volume of data streams from monitored devices needs to be efficiently stored and processed in real time. In this paper, we propose a cloud computing based architecture for conducting cyber security situation awareness. Particularly, we leverage the cloud infrastructure with a cost-effective data storage and investigate efficient stream processing techniques to reduce operational delays. To effectively detect threats, we present a parallel cloud based threat detection that integrates both signature-based detection and anomaly-based detection. To capture the insightful characteristics of attacks, we discuss the attack scene analysis based on spatiotemporal correlation and visualization schemes to analyze, trace, and visualize abnormal behaviors. Lastly, we present the testbed setup and the implementation workflow to validate the effectiveness of our proposed system.

On Effectiveness of Smart Grid Applications Using Co-Simulation

The smart grid is a complex system that comprises components from both the power grid and communication networks. To understand the behavior of such a complex system, co-simulation is a viable tool to capture the interaction and the reciprocal effects between a communication network and a physical power grid. In this paper, we systematically review the existing efforts of co-simulation and design a framework to explore co-simulation scenarios. Using the demand response and energy price as examples of smart grid applications and operating the communication network under various conditions (e.g., normal operation, performance degrade, and security threats), we implement these scenarios and conduct a performance evaluation of smart grid applications by leveraging a co-simulation platform.

On effectiveness of mesh-based protocols for smart grid communication networks

The smart grid requires a reliable, efficient and cost effective communication network that meets performance requirements. Due to their cost effectiveness and ubiquitous nature, wireless mesh networks have been considered as an alternative for smart grid communication networks. In this paper, we first review smart grid communication network requirements by applying various use cases that enables the design of network models for simulation. Using the ns-3 simulator tool, we then systematically compare the effectiveness of two representative wireless mesh network protocols: Hybrid Wireless Mesh Network Protocol (HWMP) and Ad hoc On-Demand Distance Vector (AODV) Protocol in terms of various performance metrics and network settings. Our evaluation data shows that the HWMP protocol is suitable for small size mesh grids whereas AODV performs better for large mesh grids. We also conduct a simulation study to investigate the performance of Worldwide Interoperability for Microwave Access (WIMAX) technology in smart grid communication networks with different modulation techniques.

Integrating Renewable Energy Resources in Smart Grid Toward Energy-Based Cyber-Physical Systems

Abstract The inherent intermittency of renewable energy resources can seriously affect the stability and reliability of energy service in the smart grid. In this chapter, we first review the renewable energy resources and existing efforts toward their integration into the power grid. We then design simulation scenarios that consider the integration of different types of renewable energy resources and deployment techniques. After that, we propose a control mechanism that is capable of mitigating the inherent variability of renewable energy resources. Using GridLAB-D and GridMat simulation tools, 1 we implement these scenarios and evaluate the effectiveness of mixing different types of renewable energy resources and techniques, as well as our proposed control mechanism. Our simulation data shows that mixing different types of renewable energy resources and energy storage can effectively reduce power generation costs and power losses. Our simulation data also show that the proposed control mechanism is effective in responding to failure and contingencies by monitoring the status of distributed energy resources.

A smart grid simulation testbed using Matlab/Simulink

The smart grid is the integration of computing and communication technologies into a power grid with a goal of enabling real time control, and a reliable, secure, and efficient energy system [1]. With the increased interest of the research community and stakeholders towards the smart grid, a number of solutions and algorithms have been developed and proposed to address issues related to smart grid operations and functions. Those technologies and solutions need to be tested and validated before implementation using software simulators. In this paper, we developed a general smart grid simulation model in the MATLAB/Simulink environment, which integrates renewable energy resources, energy storage technology, load monitoring and control capability. To demonstrate and validate the effectiveness of our simulation model, we created simulation scenarios and performed simulations using a real-world data set provided by the Pecan Street Research Institute.

On simulation study of mesh-based protocols for smart grid communication networks

The smart grid requires a reliable, efficient and cost effective two-way communication network that meets performance requirements. Due to their cost effectiveness and ubiquitous nature, wireless mesh networks have been considered as a viable solution for smart grid communication networks. In this paper, we first review smart grid communication network requirements using various use cases that enables the design of network models for simulation. Using the ns-3 simulator tool, we then systematically compare the effectiveness of two representative wireless mesh network protocols: Hybrid Wireless Mesh Network Protocol (HWMP) and Ad hoc On-Demand Distance Vector (AODV) Protocol in terms of various performance metrics and network settings. Our evaluation results show that HWMP protocol is suitable for small size mesh grids while AODV performs better for large mesh grids.

An Integrated Simulation Study on Reliable and Effective Distributed Energy Resources in Smart Grid

The investigation of the reliability, effectiveness, and impact of Distributed Energy Resources (DERs) on smart grid applications (demand-response, real time price, etc.) requires an integrated evaluation framework. In this paper, we design an integrated simulation platform and demonstrate its use via investigating the impact of DERs on smart grid applications (demand-response and energy market) under various adverse conditions, along with network architectures. Using the standard IEEE bus system, we systematically evaluate the integration of DERs and the performance impact on demand response and energy markets with respect to system management, uncertainties and different network architectures. Our experimental results demonstrate the ability of designed co-simulation tool to evaluate the performance of DERs and system management and networking techniques. Our results are comprehensive, providing a concise representation of DER performance for the design and implementation of real smart grid system.