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Grant: Discovery Grants Program - Individual

York University

$56,000.00

Optimal Grid Management for Large-Scale Sustainable Coordination

FY 2023-24

Summary
Recent changes in climate patterns are causes for great consternation as the ensuing environmental consequences are devastating and costly. Climate change related costs are projected to increase up to $43 billion every year in Canada by 2050. In light of these repercussions, many nations (including Canada) have pledged to actively limit the impact of climate change while increasing resilience to related adverse risks in the Paris Climate Accord established in 2016. One vital component of this initiative is the promotion of clean energy production and consumption.Mechanisms actively engaged today for reducing greenhouse emissions and carbon footprint are predominantly based on monetary incentives. For example, carbon pricing penalizes generation sources with high carbon emissions and time-of-use pricing assigns fixed prices for electricity consumption over specific blocks of time periods over a day via smart meters. As these do not reflect actual costs and congestions incurred for generation, transmission and distribution; inefficiencies are inevitable. Active mechanisms that optimally coordinate actuating power components in real-time to promote grid sustainability are still not yet a reality due to the intractability caused by the presence of large number of control variables, highly fluctuating non-linear constraints and complex dynamics modelling underlying physical interdependencies.The proposed research program aims to tap onto the ubiquitous cyber-physical capability present in the modern smart grid to construct a more adaptive and unified grid management framework consisting of three specific objectives: 1) contextual grid monitoring; 2) large-scale coordination of actuating power components residing at the transmission, distribution and microgrid levels; and 3) active planning for increasing system resilience to constantly occurring changes. To achieve these goals, the inherent separability and decomposable structure of optimization and control formulations in the grid will be capitalized to construct adaptive monitoring, control and planning algorithms at various degrees of granularity. Recent advances in large-scale optimization, distributed game theory and social learning analysis will be leveraged to design information exchanges and strategic local decision-making for large populations of power entities to enhance the efficiency and sustainability in power grid operations.This proposal is in line with the climate change initiative taken at the federal level by the government of Canada via the Pan-Canadian Framework on Clean Growth and Climate Change. Core goals of this initiative include supporting sustainable technology and incorporating resilience to adverse effects of climate change. These are also key elements of the proposed research program contributing to the efforts of securing a safe and sustainable planet for future generations.
Program
Discovery Grants Program - Individual
Location
Ontario, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data

As published

Application id
RGPIN-2018-05650
Name nom
Srikantha, Pirathayini
Department département
Electrical Engineering & Computer Science - Electrical Engineering & Computer Science
Organization id
38
Institution établissement
York University
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2023
Competition year année de concours
2018
Award amount
56000
Program id
RGPIN
Program name en
Discovery Grants Program - Individual
Program name fr
Programme de subventions à la découverte - individuelles
Group en
DISCOVERY RESEARCH
Group fr
RECHERCHE AXÉE SUR LA DÉCOUVERTE
Committee code
1510
Committee name en
Electrical and Computer Engineering
Committee name fr
Génie électrique et informatique
Area of application code
304
Area of application group en
Energy resources
Area of application group fr
Ressources d'énergie
Area of application en
Electrical energy
Area of application fr
Énergie électrique
Research subject code
9999
Research subject group en
Not available
Research subject group fr
Not available
Research subject en
Non disponible
Research subject fr
Non disponible
Application title
Optimal Grid Management for Large-Scale Sustainable Coordination
Keyword
Demand Response; Distributed Generation; Distributed Optimization; Game Theory; Grid Maintenance; Intelligent Control; Large-Scale Coordination; Monitoring; Smart Grid; Sustainable Management
Application summary
Recent changes in climate patterns are causes for great consternation as the ensuing environmental consequences are devastating and costly. Climate change related costs are projected to increase up to $43 billion every year in Canada by 2050. In light of these repercussions, many nations (including Canada) have pledged to actively limit the impact of climate change while increasing resilience to related adverse risks in the Paris Climate Accord established in 2016. One vital component of this initiative is the promotion of clean energy production and consumption.Mechanisms actively engaged today for reducing greenhouse emissions and carbon footprint are predominantly based on monetary incentives. For example, carbon pricing penalizes generation sources with high carbon emissions and time-of-use pricing assigns fixed prices for electricity consumption over specific blocks of time periods over a day via smart meters. As these do not reflect actual costs and congestions incurred for generation, transmission and distribution; inefficiencies are inevitable. Active mechanisms that optimally coordinate actuating power components in real-time to promote grid sustainability are still not yet a reality due to the intractability caused by the presence of large number of control variables, highly fluctuating non-linear constraints and complex dynamics modelling underlying physical interdependencies.The proposed research program aims to tap onto the ubiquitous cyber-physical capability present in the modern smart grid to construct a more adaptive and unified grid management framework consisting of three specific objectives: 1) contextual grid monitoring; 2) large-scale coordination of actuating power components residing at the transmission, distribution and microgrid levels; and 3) active planning for increasing system resilience to constantly occurring changes. To achieve these goals, the inherent separability and decomposable structure of optimization and control formulations in the grid will be capitalized to construct adaptive monitoring, control and planning algorithms at various degrees of granularity. Recent advances in large-scale optimization, distributed game theory and social learning analysis will be leveraged to design information exchanges and strategic local decision-making for large populations of power entities to enhance the efficiency and sustainability in power grid operations.This proposal is in line with the climate change initiative taken at the federal level by the government of Canada via the Pan-Canadian Framework on Clean Growth and Climate Change. Core goals of this initiative include supporting sustainable technology and incorporating resilience to adverse effects of climate change. These are also key elements of the proposed research program contributing to the efforts of securing a safe and sustainable planet for future generations.