Reference number : GC-2017-Q1-01668, amendment number : , agreement type : G, recipient legal name : Simpson-Porco, John (University of Waterloo), recipient country : CA, recipient province : nan, recipient city : Ontario, recipient postal code : nan, program name english : Discovery Grants Program - Individual, program name french : Programme de subventions à la découverte - individuelles, program purpose english : Electric power is what drives our technological civilization forward. Over the past few decades, climate change and pollution issues have propelled many countries to adopt sustainable energy solutions. We can now produce clean power from renewable sources such as wind turbines and solar farms. Yet, producing power is only half the battle. Equally as important is our ability to reliably transmit that power through the power grid to consumers. 
 
Our existing power grid is hierarchical and consists of several layers. The lowest layer is the distribution grid, where consumers -- and now, many renewable power sources -- are connected. As fossil fuels are slowly displaced by renewables, we replace large, very reliable sources of power with many smaller and less predictable sources. This transition is pushing distribution grids worldwide into operating situations they were simply not designed for, and grid operators are facing new stability and control issues. Our ability to effectively use renewable energy is currently bottlenecked by our ability to control and optimize our legacy distribution grids. 
 
The long-term objective of this research program is to develop control and optimization strategies to maximize the amount of renewable energy in the power grid. The key idea is to develop a deeper mathematical understanding of how power is transmitted through the grid, then use this understanding to more efficiently coordinate previously independent generation and control equipment. Critical research will include the development of new mathematical models for power flow, quantifying the renewable penetration and stability limits of the grid, and designing feedback controllers which increase these limits. Coordinating independent groups of sensors, distributed generators, and control equipment in real time will allow us maximize our current grid infrastructure, without compromising grid stability. By leveraging the engineering principles of modern feedback control, we will be able to compensate for the effects of increased uncertainty from renewable generation, leading to a clean yet reliable grid. 
 
To accelerate the wide-spread adoption of small-scale renewable power, this research will provide the essential advances in grid control needed to reduce the stress on our legacy distribution grids, enabling utilities to maximize their assets without costly equipment upgrades. Such software-powered solutions are a vital piece of the energy puzzle. Also central is ensuring there are highly qualified personnel (HQP) with the control and optimization skills necessary to address the country's energy challenges, in both the utility and private product sectors. HQP who successfully participate in this unique, specialized program will be at the forefront of the transition to a 21st century grid powered by renewables and coordinated feedback control., program purpose french : Electric power is what drives our technological civilization forward. Over the past few decades, climate change and pollution issues have propelled many countries to adopt sustainable energy solutions. We can now produce clean power from renewable sources such as wind turbines and solar farms. Yet, producing power is only half the battle. Equally as important is our ability to reliably transmit that power through the power grid to consumers. 
 
Our existing power grid is hierarchical and consists of several layers. The lowest layer is the distribution grid, where consumers -- and now, many renewable power sources -- are connected. As fossil fuels are slowly displaced by renewables, we replace large, very reliable sources of power with many smaller and less predictable sources. This transition is pushing distribution grids worldwide into operating situations they were simply not designed for, and grid operators are facing new stability and control issues. Our ability to effectively use renewable energy is currently bottlenecked by our ability to control and optimize our legacy distribution grids. 
 
The long-term objective of this research program is to develop control and optimization strategies to maximize the amount of renewable energy in the power grid. The key idea is to develop a deeper mathematical understanding of how power is transmitted through the grid, then use this understanding to more efficiently coordinate previously independent generation and control equipment. Critical research will include the development of new mathematical models for power flow, quantifying the renewable penetration and stability limits of the grid, and designing feedback controllers which increase these limits. Coordinating independent groups of sensors, distributed generators, and control equipment in real time will allow us maximize our current grid infrastructure, without compromising grid stability. By leveraging the engineering principles of modern feedback control, we will be able to compensate for the effects of increased uncertainty from renewable generation, leading to a clean yet reliable grid. 
 
To accelerate the wide-spread adoption of small-scale renewable power, this research will provide the essential advances in grid control needed to reduce the stress on our legacy distribution grids, enabling utilities to maximize their assets without costly equipment upgrades. Such software-powered solutions are a vital piece of the energy puzzle. Also central is ensuring there are highly qualified personnel (HQP) with the control and optimization skills necessary to address the country's energy challenges, in both the utility and private product sectors. HQP who successfully participate in this unique, specialized program will be at the forefront of the transition to a 21st century grid powered by renewables and coordinated feedback control., agreement title english : Real-Time Distributed Control for Low-Inertia Power Grids, agreement title french : Real-Time Distributed Control for Low-Inertia Power Grids, agreement number : RGPIN, agreement value : 120000.0, agreement start date : 2017-05-10, agreement end date : nan, description english : nan, description french : nan, expected results english : nan, expected results french : nan, additional information english : Grant or Award spanning more than one fiscal year. (2017-2018 to 2022-2023), additional information french : Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier. (2017-2018 à 2022-2023), owner organization : nserc-crsng, owner organization title : Natural Sciences and Engineering Research Council of Canada | Conseil de recherches en sciences naturelles et en génie du Canada