In recent years, there has been a growing interest in sustainable energy resources, such as solar, geothermal, wave, and wind energy. The renewable energy sector’s share of the energy supply is expected to grow to 18.6% by 2030. Moreover, the International Energy Agency (IEA) predicts that wind energy will have a 12% share of the global energy supply by 2050. To reach this target, the wind energy production capacity will have to increase at an average rate of 47 GW/year, resulting in massive investments and a dynamic, growing market for wind-related technology and services.
In this context, the overall vision for this aspect of our research program is to leverage modeling, simulation and optimization methods to optimize energy systems by maximizing their energy efficiency, minimizing their cost, and minimizing their environmental impact. The following are two application-specific projects that we are currently pursuing:
Simulation and design optimization of wind turbine layouts
We are currently focused on modelling wind turbine wakes using CFD methods. The turbulent nature of turbine wakes and the complex geometries of turbine blades increase the modelling difficulty of the problem. In the absence of high-quality experimental data of multiple wake interactions in complex terrains, CFD simulations can provide valuable insight into these complex flow phenomena. One of the main goals of this project is to develop a relatively low-cost CFD model without loss of physical representation. Such models enable simulation-based optimization of the turbine layout with adjoint methods, leading to the design of wind farms that take advantage of both the stochastic wind resource profile and local terrain effects to maximize their energy generation.
Infrastructure for Hybrid/Electric Vehicles
Fuel cell vehicles (FCVs), Hybrid Gas-Electric vehicles (HEVs) and Fully-Electric vehicles (EVs) utilizing either hydrogen (FCVs) or electricity (HEVs, EVs) produced from renewable electricity have very low well-to-wheel emissions, and have become the most promising transportation alternative to conventional automobiles. Most major automakers have already developed and are currently marketing FCVs, HEVs or EVs.
Despite the technical maturity of these technologies, a significant barrier to broad adoption is the need for extensive generation, distribution and fueling infrastructure to support an ever-increasing car population. Deploying such infrastructure will require massive investments by governments and industry, and will require new policy frameworks, economic incentives to facilitate and guide these investments.
Here at the ATOMS Lab, we are developing system-level optimization models to support the design, evaluation and implementation of policies, incentives and investments required for broad adoption of FCVs, HEVs and EVs. We are currently focused on the Greater Toronto Area (GTA) over medium to long-term planning periods. The resulting optimization model provides valuable insights for policymakers and stakeholders to the infrastructure, power, financing, and operational requirements of the overall system to achieve targeted penetration levels while minimizing the overall investment and environmental impact.
