Bora A. Akyol

Scalable real time data management for smart grid

This paper presents GridMW, a scalable and reliable data middleware layer for smart grids. Smart grids promise to improve the efficiency of power grid systems and reduce green house emissions through incorporating power generation from renewable sources and shaping demands to match the supply. As a result, power grid will become much more dynamic and require constant adjustments, which requires analysis and decision making applications to improve the efficiency and reliability of smart grid systems. However, these applications rely on large amounts of data gathered from power generation, transmission, and consumption. To this end, millions of sensors, including phasor measurement units (PMU) and smart meters, are being deployed across the smart grid system. Existing data middleware does not have the capability to collect, store, retrieve, and deliver the enormous amount of data from these sensors to analysis and control applications. Most existing data middleware approaches utilize general software systems for flexibility so that the solutions can provide general functionality for a range of applications. However, overheads incurred by generalized APIs cause high latencies and unpredictability in performance, which in turn prevents achieving near real time latencies and high throughput. In our work, by tailoring the system specifically to smart grids, we are able to eliminate much of these overheads while still keeping the implementation effort reasonable. This is achieved by using a log structure inspired architecture to directly access the block device layer, eliminating the indirection incurred by high level file system interfaces. Preliminary results show our system can significantly improve performance compared to traditional systems.

VOLTTRON™: An agent platform for integrating electric vehicles and Smart Grid

The VOLTTRON™ platform provides a secure environment for the deployment of intelligent applications in the Smart Grid. The platforms design is based on the needs of control applications running on small form factor devices, namely security and resource guarantees. Services such as resource discovery, secure agent mobility, and interacting with smart and legacy devices are provided by the platform to ease the development of control applications and accelerate their deployment. VOLTTRON has been demonstrated in several different domains that influenced and enhanced its capabilities. This paper will discuss the features of VOLTTRON and highlight its usage to coordinate electric vehicle charging with home energy usage.

GridOPTICS(TM) A Novel Software Framework for Integrating Power Grid Data Storage, Management and Analysis

This paper describes the architecture and design of GridOPTICSTM, a novel software framework for integrating a collection of software tools developed by NPNNLs Future Power Grid Initiative (FPGI) into a coherent, powerful operations and planning tool for the power grid of the future. GridOPTICSTM enables plug-and-play of various analysis, modeling and visualization software tools to improve the efficiency and reliability of power grid. To bridge the data access for different control purposes, GridOPTICSTM provides a scalable, lightweight event processing layer that hides the complexity of data collection, storage, delivery and management. A significant challenge is the requirement to access large amount of data in real time. We address this challenge though a scalable system architecture that balances system performance and ease of integration. The initial prototype of GridOPTICSTM was demonstrated with several use cases from PNNLs FPGI and show that our system can provide real time data access to a diverse set of applications with easy to use APIs.

An Intelligent Sensor Framework for the Power Grid

The number of sensors connected to the electric power system is expected to grow by several orders of magnitude by 2020. However, the information networks which will transmit and analyze the resulting data are ill-equipped to handle the resulting volume with reliable real-time delivery. Without the ability to manage and use this data, deploying sensors such as phasor measurement units in the transmission system and smart meters in the distribution system will not result in the desired improvements in the power grid. The ability to exploit the massive data being generated by new sensors would allow for more efficient flow of power and increased survivability of the grid. Additionally, the power systems of today are not capable of managing two-way power flow to accommodate distributed generation capabilities due to concerns about system stability and lack of system flexibility. The research that we are performing creates a framework to add “intelligence” to the sensors and actuators being used today in the electric power system. Sensors that use our framework will be capable of sharing information through the various layers of the electric power system to enable two-way information flow to help facilitate integration of distributed resources. Several techniques are considered including use of peer-to-peer communication as well as distributed agents. Specifically, we will have software agents operating on systems with differing levels of computing power. The agents will cooperate to bring computation closer to the data. The types of computation considered are control decisions, data analysis, and demand/response. When paired with distributed autonomous controllers, the sensors form the basis of an information system that supports deployment of both micro-grids and islanding. Our efforts in the area of developing the next generation information infrastructure for sensors in the power grid form the basis of a broader strategy that enables better integration of distributed generation, distribution automation systems and decentralized control (micro-grids).Copyright

Transaction-based building controls framework, Volume 2: Platform descriptive model and requirements

Transaction-based Building Controls (TBC) offer a control systems platform that provides an agent execution environment that meets the growing requirements for security, resource utilization, and reliability. This report outlines the requirements for a platform to meet these needs and describes an illustrative/exemplary implementation.

VOLTTRON: User Guide

This document is a user guide for the deployment of the Transactional Network platform and agent/application development within the VOLTTRON. The intent of this user guide is to provide a description of the functionality of the Transactional Network Platform. This document describes how to deploy the platform, including installation, use, guidance, and limitations. It also describes how additional features can be added to enhance its current functionality.

Transactional network: Improving efficiency and enabling grid services for buildings

Because of a need to reduce electricity consumption and to make electricity generation cleaner, there is an impetus to improve the energy efficiency of the building stock and widespread installation of distributed variable renewable energy generation. Soon, a significant fraction of transportation energy will be in the form of electricity. Significant gains in building operational efficiency are possible because between 20% and 30% of the energy consumed in commercial buildings is typically wasted because of poor or inefficient building operations. To address these problems, the U.S. Department of Energys Building Technologies Office is supporting the development of the concept of a “transactional network” that supports energy, operational, and financial transactions between building systems (e.g., rooftop units), and the electric power grid using applications, or “agents,” that reside either on the equipment, on local building controllers, or in the Cloud. This article describes the transactional network concept, the platform, and two example agents/applications within VOLTTRON™ that improve operational efficiency and enable grid services for packaged air conditioners and heat pumps (rooftop units). It also describes the results from testing the concept at some demonstration sites.

VOLTTRON Lite: Integration Platform for the Transactional Network

In FY13, Pacific Northwest National Laboratory (PNNL) with funding from the Department of Energy’s (DOE’s) Building Technologies Office (BTO) designed, prototyped and tested a transactional network platform. The platform is intended to support energy, operational and financial transactions between any networked entities (equipment, organizations, buildings, grid, etc.). Initially, in FY13, the concept demonstrated transactions between packaged rooftop units (RTUs) and the electric grid using applications or “agents” that reside on the platform, on the equipment, on local building controller or in the Cloud. This document describes the core of the transactional network platform, the Volttron Lite™ software and associated services hosted on the platform. Future enhancements are also discussed. The appendix of the document provides examples of how to use the various services hosted on the platform.

LINEBACkER: Bio-inspired data reduction toward real time network traffic analysis

One essential component of resilient cyber applications is the ability to detect adversaries and protect systems with the same flexibility adversaries will use to achieve their goals. Current detection techniques do not enable this degree of flexibility because most existing applications are built using exact or regular-expression matching to libraries of rule sets. Further, network traffic defies traditional cyber security approaches that focus on limiting access based on the use of passwords and examination of lists of installed or downloaded programs. These approaches do not readily apply to network traffic occurring beyond the access control point, and when the data in question are combined control and payload data of ever increasing speed and volume. Manual analysis of network traffic is not normally possible because of the magnitude of the data that is being exchanged and the length of time that this analysis takes. At the same time, using an exact matching scheme to identify malicious traffic in real time often fails because the lists against which such searches must operate grow too large. In this work, we propose an adaptation of biosequence alignment as an alternative method for cyber network detection based on similarity-measuring algorithms for gene sequence analysis. These methods are ideal because they were designed to identify similar but non-identical sequences. We demonstrate that our method is generally applicable to the problem of network traffic analysis by illustrating its use in two different areas based on different attributes of network traffic. Our approach provides a logical framework for organizing large collections of network data, prioritizing traffic of interest to human analysts, and makes it possible to discover traffic signatures without the bias introduced by expert-directed signature generation. Pattern recognition on reduced representations of network traffic offers a fast, efficient, and more robust way to detect anomalies.

An evaluation of the network simulators in large-scale distributed simulations

Networks for the smart grids are characterized by millions of sensor nodes exchanging information about the status of the grid. This information exchange must be realized reliably and efficiently due to the mission critical nature of the power grid. Hence, the applications and the network protocols developed for the smart grid need go through rigorous testing and analysis before deployment. Developers usually do not have access to such a large-scale network that can be used as a controlled test-bed; therefore, network simulation becomes an essential tool for testing. Network simulation is a well studied problem in the literature and there are various widely used network simulators. These simulators can be adopted for testing applications and protocols of the smart grid. Due to the scale of these networks, parallel/distributed simulations need to be conducted. Even though most network simulators support distributed simulations, generating a large-scale network model to simulate can still be a cumbersome task. In this survey, we describe a selection of commonly used network simulators and evaluate them with respect to the following features that can aid users in distributed simulations of large-scale networks: transparency of setting up distributed simulation, automated topology generation, information hiding, lightweight routing protocols, network error simulation, evaluation of the network model during simulation and trace analysis tools. As a complementary result, we identify two issues with network simulators that can be addressed with runtime steering methods.