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Grant: Alliance Grants

Toronto Metropolitan University

$292,000.00

Forecasting and Modeling of Distributed Energy Resources, and Models for Distributed System Operator Planning and Operation

FY 2023-24

Summary
Large scale integration of distributed energy resources (DERs), such as renewables, storage and smart loads into electric power distribution systems, is a path that leads to greening of our energy systems and a zero carbon 2050 future. This is a future that our society desires and helps to mitigate climate change. This is also a challenging task. Electric utilities require aggregate methods for forecasting of DERs, aggregate steady-state and aggregate transient DER models - at feeder and substation levels - to best manage their electric power networks. Further, with the potential of peer-to-peer energy transactions between DERs and other customers, better economic techno-models are a pressing need such that DERs derive best value and utility customers gain the best advantage. Accordingly, proposed work is driven by this urgent need to green our energy supply through increasing the uptake of DERs. DERs are small in size and numerous. Their intermittent and uncertain nature poses a challenge for utilities to monitor, forecast, model, analyse and operate their networks. The overarching goal is to develop tools and frameworks that support the sustainable and seamless integration of diverse forms of energy from DERs into the HONI grid in ways that maximize opportunity, access to the grid, and choice for all stakeholders (including DER owners and electricity customers), which will also enable deep electrification. To achieve this outcome, we are proposing four work packages (WPs) to develop AI-based, high-resolution, aggregate, DER forecasting tools, steady-state DER models, transient DER models, and distribution system operator (DSO) and distribution network operator (DNO) models for operation and planning, comprising algorithms and software implementation. Canada needs to increase its clean energy supply two or three folds from its current situation. The project's outcomes will contribute to the Canadian economy though enhanced supply reliability, resilience to face extreme weather, and economic accessibility, facilitating greater DER uptake as the pathway to deep clean electrification.
Program
Alliance Grants
Location
Ontario, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data

As published

Application id
572272-2022
Name nom
Venkatesh, Bala B
Department département
Electrical, Computer and Biomedical Engineering
Organization id
43
Institution établissement
Toronto Metropolitan University
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2023
Competition year année de concours
2022
Award amount
292000
Program id
ALLRP
Program name en
Alliance Grants
Program name fr
Subventions Alliance
Group en
RESEARCH PARTNERSHIPS
Group fr
PARTENARIATS DE RECHERCHE
Committee code
96
Committee name en
RPP Internal Decision Cttee
Committee name fr
Cté de décision interne - PPR
Area of application code
300
Area of application group en
Energy resources
Area of application group fr
Ressources d'énergie
Area of application en
Energy resources (including production, exploration, processing, distribution and use)
Area of application fr
Ressources d'énergie (production, exploration, traitement, distribution et utilisation de l'énergie)
Research subject code
2501
Research subject group en
Electrical and electronic engineering
Research subject group fr
Power systems
Research subject en
Génie électrique et électronique
Research subject fr
Réseaux électriques
Application title
Forecasting and Modeling of Distributed Energy Resources, and Models for Distributed System Operator Planning and Operation
Keyword
Deep electrification; Distributed energy resources; Distribution feeders; Distribution system; Distribution system operator; Energy forecast; Operation; Optimization; Power system analysis; Renewables
Application summary
Large scale integration of distributed energy resources (DERs), such as renewables, storage and smart loads into electric power distribution systems, is a path that leads to greening of our energy systems and a zero carbon 2050 future. This is a future that our society desires and helps to mitigate climate change. This is also a challenging task. Electric utilities require aggregate methods for forecasting of DERs, aggregate steady-state and aggregate transient DER models - at feeder and substation levels - to best manage their electric power networks. Further, with the potential of peer-to-peer energy transactions between DERs and other customers, better economic techno-models are a pressing need such that DERs derive best value and utility customers gain the best advantage. Accordingly, proposed work is driven by this urgent need to green our energy supply through increasing the uptake of DERs. DERs are small in size and numerous. Their intermittent and uncertain nature poses a challenge for utilities to monitor, forecast, model, analyse and operate their networks. The overarching goal is to develop tools and frameworks that support the sustainable and seamless integration of diverse forms of energy from DERs into the HONI grid in ways that maximize opportunity, access to the grid, and choice for all stakeholders (including DER owners and electricity customers), which will also enable deep electrification. To achieve this outcome, we are proposing four work packages (WPs) to develop AI-based, high-resolution, aggregate, DER forecasting tools, steady-state DER models, transient DER models, and distribution system operator (DSO) and distribution network operator (DNO) models for operation and planning, comprising algorithms and software implementation. Canada needs to increase its clean energy supply two or three folds from its current situation. The project's outcomes will contribute to the Canadian economy though enhanced supply reliability, resilience to face extreme weather, and economic accessibility, facilitating greater DER uptake as the pathway to deep clean electrification.
Toronto Metropolitan University - $292,000 Grant (202… | Canada Spends