After a critical event, infrastructures suffer varying levels of damages and infrastructure managers are tasked with optimizing their available resources.
However, infrastructures are closely linked to each other and managers require information and resources from other infrastructures to make these optimum
decisions. For example, the food distribution system closely depends on the transportation system for its functioning, and the transportation system depends
on the Oil and Gas distribution system. Very often, infrastructure managers like to focus on its own facility without taking the consideration of the whole picture. The interdependencies are completely missing therefore a catastrophic chain reaction is just matter of time. I2Sim, however, relies on the state of art computing power to calculate the interdependencies between all the infrastructures and determine the consequence before actions. DR-NEP offers a common platform for managers to update the state of his/her infrastructure(s). It also allows managers to request information and resources from other infrastructures, and communicate their decisions to other managers.
Concept of Interdependencies:
I2Sim/DR-NEP offers an integration platform for simulators to communicate their results and various actors to coordinate between each other. However, the problem of optimizing available resources still exists for two reasons:
(1) Resources are generally limited after a major catastrophic event and
(2) interdependencies exist in complex systems, as illustrated in the above figure.
For example, the hospital depends on electricity and water for functioning and the
water pumping station requires electricity to pump water into the hospital.
The electric substation is faced with the task of distributing electricity in an optimum way, however, after a major event, electricity could be limited. Finally, as the system grows in size,
these interdependencies also grow manyfold and facility managers could find it difficult to make the best
decisions. So how does the electric system distribute electricity in an optimum way? I2Sim finds the
interdependencies in large systems and can suggest to the managers of utilities near-optimum decisions.
Infrastructure Interdependency Simulator (I2Sim):
I2Sim is developed by the I2Sim group of the University of
British Columbia to model the interdependencies among critical infrastructure (CI) systems (e.g., electricity, water, gas, etc.). It allows coordinated decision making to be made for optimum
deployment of resources and priorities in system restoration after critical events. For example, in a power grid problem, I2Sim can determine that the water pumping station and the hospital should
be served immediately, while the other infrastructures can be left without service until the system is
repaired. Similarly, when multiple points of service need to be repaired, I2Sim accesses which points
should be repaired first and coordinates these priorities in service and restoration among infrastructure
owners and emergency responders, ensuring minimal injuries and loss of lives during
The following is an introduction of one possible area that I2Sim can be used to determine interdependencies during major disaster event. The DR-NEP project has been under development for over three years and one of the most advance disaster management tools in the community.
DR-NEP offers a service oriented architecture (SAAS) for disaster responders and
researchers to connect to this common platform. The components of DR-NEP are:
Customized Map and Web APIs: DR-NEP offers customized KML based mapping APIs that work with popular mapping tools, like Google Earth. Authorized users can change the state of their infrastructure(s), report decisions taken,
and view the status of other components in the systems on any compatible mobile device.
Authorized users can also query the information of interest using the web interface. It provides details such as past events, results from other simulators, and information shared by other actors.
Enterprise service bus (ESB) and SOAP based webservices: The ESB is the backbone of DR-NEP. All actors and simulators communicate and coordinate with each other through the ESB.
The ESB exposes two sets of webservices: (1) For disaster responders and researchers to update and view the
information of their interest. (2) For connecting simulators such that these simulators use the webservices
to get the required inputs from the database and return results back to the ESB after running the simulations.
Database: The ESB stores all the information in a common database. The information could be used by authorized users to perform What-if studies, simulation practice, etc.
DR-NEP offers a common platform to integrate data and results from different simulators.
Let us take the example of three people speaking three different languages, but are trying to communicate with each other.
Each person would need to learn two other languages to understand and communicate with the two others. However, if there was one common language,
then each person would only need to learn the one common language. This reduces the efforts required to learn a new language every time a new person joins
The same analogy can be used for connecting simulators that implement different protocols for operations. DR-NEP offers a common protocol (language) to connect
such simulators. An adapter must be configured for every simulator that translates simulator-specific protocol into java-based protocol for DR-NEP. Once the
adapter is configured, DR-NEP can automate the process of starting the connected simulators and pushing and pulling data into simulators.
Smart Power Systems
The traditional electrical grid model is based on large generation plants with high-voltage transmission lines carrying energy to population centres hundreds of kilometers away. Much sophistication has been put into the operation of the high-voltage transmission system to avoid local problems from propagating throughout the entire grid and causing major blackouts. In contrast, at the low-voltage customer level, distribution systems have remained unsophisticated “bare-bone” wires and breakers.
The situation in distribution systems is changing rapidly due to a number of factors: 1) Restrictions in capital investment are driving system operation closer to the capacity limits and are making feeder redundancy increasingly a major factor. 2) Deployment of advanced metering infrastructures (AMI) “smart meters” will make real time demand consumption continuously available. 3) Penetration of intermittent renewable generation (solar, wind, etc.) will add uncertainty on the available generation and, therefore, on the grid supported demand. 4) Penetration of electrical vehicles will add additional peaks to existing load patterns. 5) Storage deployment will allow additional controlling functions to load dispatching. 6) Advances in power electronics will allow more sophisticated operation and control mechanisms.
This work is developing Distribution System Management (DSM) tools that will automate and optimize the operation of the power distribution systems of the future and will allow the seamless penetration of renewable energy sources like wind and solar while maintaining the integrity and reliability of the grid.
Some of the objectives of this work include:
Volt-VAR Optimization (VVO) to optimize voltage profiles, and consequently energy efficiency, in distribution feeders with distributed renewable sources and distributed storage.
Optimization of topological structures to maximize feeder utilization.
Load disaggregation from smart meters as part of VVO optimization and load forecasting.
Stochastic load and generation forecasting with intermittent distributed generation and electrical vehicles penetration.
Design and Engineering of Electrical Insulatoin Systems for Power Neworks Presentation Slides from Dr. Srivastava is available here:
Smart Distribution System
Dr. José R. Martí
Electrical and Computer Engineering
The University of British Columbia
3058 - 2332 Main Mall
Vancouver BC V6T 1Z4