Reference number : GC-2017-Q1-02383, amendment number : , agreement type : G, recipient legal name : EL-SHATSHAT, Ramadan (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 : Microgrid is a recently-coined term that describes a micro power distribution system composed of clusters of distributed generation (DG) sources, including wind and solar sources, that serve a group of distributed loads. The ability of the microgrid to facilitate DG sources to supply a highly localized area with reliable electricity has motivated a significant amount of research on how to exploit the strengths of the microgrid concept to transform conventional power systems into intelligent decentralized electric power distribution systems, called smartgrids. In particular, a significant question is the suitability of smartgrids to optimize the management and control of the distribution system, reducing its CO2 emissions, improving its efficiency and reliability, and ensuring its security. The successful transformation of an existing power distribution system into a smartgrid faces several technical and economic challenges related to its creation, operation, and management. These include the seamless integration of the renewable sources, and its cost-effectiveness, reliability, and long-term sustainability. 
This Discovery program aims to develop new algorithms necessary for optimizing the management, control, and operation of smartgrids in the presence of fluctuating renewable generation sources and system loads. In addition, this program will focus on developing new methods and techniques for pairing the strengths of artificial intelligence and graph theory with the inherent scalability and re-configurability of power grids for devising flexible and dynamically clustered smartgrids and the underlying management and operation optimization tools. 
The proposed research will assist power distribution system planners and operators in making decisions that ensure the cost-effective planning and proper operation of electricity distribution systems. Ultimately, it will contribute to reducing greenhouse gas emission in Canada, shifting the energy-generation portfolio from one based on fossil fuels to one based on renewable energy sources. It will also enable the effective handling of peak demands, while ensuring high reliability and power quality. Moreover, the distributed management of energy consumption and the optimized operation of small-zoned microgrid will produce significant economic benefits in terms of energy savings, more efficient utilization of available resources, and improvement of the overall efficiency of energy systems., program purpose french : Microgrid is a recently-coined term that describes a micro power distribution system composed of clusters of distributed generation (DG) sources, including wind and solar sources, that serve a group of distributed loads. The ability of the microgrid to facilitate DG sources to supply a highly localized area with reliable electricity has motivated a significant amount of research on how to exploit the strengths of the microgrid concept to transform conventional power systems into intelligent decentralized electric power distribution systems, called smartgrids. In particular, a significant question is the suitability of smartgrids to optimize the management and control of the distribution system, reducing its CO2 emissions, improving its efficiency and reliability, and ensuring its security. The successful transformation of an existing power distribution system into a smartgrid faces several technical and economic challenges related to its creation, operation, and management. These include the seamless integration of the renewable sources, and its cost-effectiveness, reliability, and long-term sustainability. 
This Discovery program aims to develop new algorithms necessary for optimizing the management, control, and operation of smartgrids in the presence of fluctuating renewable generation sources and system loads. In addition, this program will focus on developing new methods and techniques for pairing the strengths of artificial intelligence and graph theory with the inherent scalability and re-configurability of power grids for devising flexible and dynamically clustered smartgrids and the underlying management and operation optimization tools. 
The proposed research will assist power distribution system planners and operators in making decisions that ensure the cost-effective planning and proper operation of electricity distribution systems. Ultimately, it will contribute to reducing greenhouse gas emission in Canada, shifting the energy-generation portfolio from one based on fossil fuels to one based on renewable energy sources. It will also enable the effective handling of peak demands, while ensuring high reliability and power quality. Moreover, the distributed management of energy consumption and the optimized operation of small-zoned microgrid will produce significant economic benefits in terms of energy savings, more efficient utilization of available resources, and improvement of the overall efficiency of energy systems., agreement title english : Intelligent Microgrids-based Solutions for Optimizing Power Distribution Systems, agreement title french : Intelligent Microgrids-based Solutions for Optimizing Power Distribution Systems, 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