Biblio

Transactive Energy (TE) is an emerging discipline that utilizes economic and control techniques for operating and managing the power grid effectively. Distributed Energy Resources (DERs) represent a fundamental shift away from traditionally centrally managed energy generation and storage to one that is rather distributed. However, integrating and managing DERs into the power grid is highly challenging owing to the TE implementation issues such as privacy, equity, efficiency, reliability, and security. The TE market structures allow utilities to transact (i.e., buy and sell) power services (production, distribution, and storage) from/to DER providers integrated as part of the grid. Flexible power pricing in TE enables power services transactions to dynamically adjust power generation and storage in a way that continuously balances power supply and demand as well as minimize cost of grid operations. Therefore, it has become important to analyze various market models utilized in different TE applications for their impact on above implementation issues.In this demo, we show-case the Transactive Energy Simulation and Analysis Toolsuite (TE-SAT) with its three publicly available design studios for experimenting with TE markets. All three design studios are built using metamodeling tool called the Web-based Graphical Modeling Environment (WebGME). Using a Git-like storage and tracking backend server, WebGME enables multi-user editing on models and experiments using simply a web-browser. This directly facilitates collaboration among different TE stakeholders for developing and analyzing grid operations and market models. Additionally, these design studios provide an integrated and scalable cloud backend for running corresponding simulation experiments.

Owing1 to an immense growth of internet-connected and learning-enabled cyber-physical systems (CPSs) [1], several new types of attack vectors have emerged. Analyzing security and resilience of these complex CPSs is difficult as it requires evaluating many subsystems and factors in an integrated manner. Integrated simulation of physical systems and communication network can provide an underlying framework for creating a reusable and configurable testbed for such analyses. Using a model-based integration approach and the IEEE High-Level Architecture (HLA) [2] based distributed simulation software; we have created a testbed for integrated evaluation of large-scale CPS systems. Our tested supports web-based collaborative metamodeling and modeling of CPS system and experiments and a cloud computing environment for executing integrated networked co-simulations. A modular and extensible cyber-attack library enables validating the CPS under a variety of configurable cyber-attacks, such as DDoS and integrity attacks. Hardware-in-the-loop simulation is also supported along with several hardware attacks. Further, a scenario modeling language allows modeling of alternative paths (Courses of Actions) that enables validating CPS under different what-if scenarios as well as conducting cyber-gaming experiments. These capabilities make our testbed well suited for analyzing security and resilience of CPS. In addition, the web-based modeling and cloud-hosted execution infrastructure enables one to exercise the entire testbed using simply a web-browser, with integrated live experimental results display.

Multirotor Unmanned Aerial Vehicles (UAV) have grown in popularity for research and education, overcoming challenges associated with fixed wing and ground robots. Unfortunately, extensive physical testing can be expensive and time consuming because of short flight times due to battery constraints and safety precautions. Simulation tools offer a low barrier to entry and enable testing and validation before field trials. However, most of the well-known simulators today have a high barrier to entry due to the need for powerful computers and the time required for initial set up. In this paper, we present OpenUAV, an open source test bed for UAV education and research that overcomes these barriers. We leverage the Containers as a Service (CaaS) technology to enable students and researchers carry out simulations on the cloud. We have based our framework on open-source tools including ROS, Gazebo, Docker, PX4, and Ansible, we designed the simulation framework so that it has no special hardware requirements. Two use-cases are presented. First, we show how a UAV can navigate around obstacles, and second, we test a multi-UAV swarm formation algorithm. To our knowledge, this is the first open-source, cloud-enabled testbed for UAVs. The code is available on GitHub: https://github.com/Open-UAV.

Despite the known benefits of simulations in the study of mixed energy systems in the context of smart grid, the lack of collaboration facilities between multiple domain experts prevents a holistic analysis of smart grid operations. Current solutions do not provide a unified tool-chain that supports a secure and collaborative platform for not only the modeling and simulation of mixed electrical energy systems, but also the elastic execution of co-simulation experiments. To address above limitations, this paper proposes a design studio that provides an online collaborative platform for modeling and simulation of smart grids with mixed energy resources.

In-depth consideration and evaluation of security and resilience is necessary for developing the scientific foundations and technology of Cyber-Physical Systems (CPS). In this demonstration, we present SURE [1], a CPS experimentation and evaluation testbed for security and resilience focusing on transportation networks. The testbed includes (1) a heterogeneous modeling and simulation integration platform, (2) a Web-based tool for modeling CPS in adversarial environments, and (3) a framework for evaluating resilience using attacker-defender games. Users such as CPS designers and operators can interact with the testbed to evaluate monitoring and control schemes that include sensor placement and traffic signal configuration.

Abstract-Virtual evaluation of complex command and control concepts demands the use of heterogeneous simulation environments. Development challenges include how to integrate multiple simulation platforms with varying semantics and how to integrate simulation models and the complex interactions between them. While existing simulation frameworks may provide many of the required services needed to coordinate among multiple simulation platforms, they lack an overarching integration approach that connects and relates the semantics of heterogeneous domain models and their interactions. This paper outlines some of the challenges encountered in developing a command and control simulation environment and discusses our use of the GME meta-modeling tool-suite to create a model-based integration approach that allows for rapid synthesis of complex HLA-based simulation environments.