Biblio

Our simulation-based experiments are aimed to demonstrate a use case on the feasibility of fulfillment of global energy demand by primarily relying on solar energy through the integration of a longitudinally-distributed grid. These experiments demonstrate the availability of simulation technologies, good approximation models of grid components, and data for simulation. We also experimented with integrating different tools to create realistic simulations as we are currently developing a detailed toolchain for experimentation. These experiments consist of a network of model houses at different locations in the world, each producing and consuming only solar energy. The model includes houses, various appliances, appliance usage schedules, regional weather information, floor area, HVAC systems, population, number of houses in the region, and other parameters to imitate a real-world scenario. Data gathered from the power system simulation is used to develop optimization models to find the optimal solar panel area required at the different locations to satisfy energy demands in different scenarios.

With the advent of remarkable development of solar power panel and inverter technology and focus on reducing greenhouse emissions, there is increased migration from fossil fuels to carbon-free energy sources (e.g., solar, wind, and geothermal). A new paradigm called Transactive Energy (TE) has emerged that utilizes economic and control techniques to effectively manage Distributed Energy Resources (DERs). Another goal of TE is to improve grid reliability and efficiency. However, to evaluate various TE approaches, a comprehensive simulation tool is needed that is easy to use and capable of simulating the power-grid along with various grid operational scenarios that occur in the transactive energy paradigm. In this research, we present a web-based design and simulation platform (called a design studio) targeted toward evaluation of power-grid distribution system and transactive energy approaches. The design studio allows to edit and visualize existing power-grid models graphically, create new power-grid network models, simulate those networks, and inject various scenario-specific perturbations to evaluate specific configurations of transactive energy simulations. The design studio provides (i) a novel Domain-Specific Modeling Language (DSML) using the Web-based Generic Modeling Environment (WebGME) for the graphical modeling of power-grid, cyber-physical attacks, and TE scenarios, and (ii) a reusable cloud-hosted simulation backend using the Gridlab-D power-grid distribution system simulation tool.

Today's smart-grids have seen a clear rise in new ways of energy generation, transmission, and storage. This has not only introduced a huge degree of variability, but also a continual shift away from traditionally centralized generation and storage to distributed energy resources (DERs). In addition, the distributed sensors, energy generators and storage devices, and networking have led to a huge increase in attack vectors that make the grid vulnerable to a variety of attacks. The interconnection between computational and physical components through a largely open, IP-based communication network enables an attacker to cause physical damage through remote cyber-attacks or attack on software-controlled grid operations via physical- or cyber-attacks. Transactive Energy (TE) is an emerging approach for managing increasing DERs in the smart-grids through economic and control techniques. Transactive Smart-Grids use the TE approach to improve grid reliability and efficiency. However, skepticism remains in their full-scale viability for ensuring grid reliability. In addition, different TE approaches, in specific situations, can lead to very different outcomes in grid operations. In this paper, we present a comprehensive web-based platform for evaluating resilience of smart-grids against a variety of cyber- and physical-attacks and evaluating impact of various TE approaches on grid performance. We also provide several case-studies demonstrating evaluation of TE approaches as well as grid resilience against cyber and physical attacks.