Design and engineering of complex systems for Industrial IoT, electrical power, thermal energy and transportation sectors. This includes renewable energy integration, grid infrastructure, energy storage, smart grids, thermal management, electrification of transportation and other projects. By leveraging innovative engineering practices, such as system modeling, optimization, and advanced control strategies, complex systems can be designed to maximize efficiency, reliability, and environmental sustainability. The technology implementation range is including data infrastructures such as Google Cloud and AWS, sensor integration for Internet of Things (IoT), advanced algorithmics, cyber-physical interfases and integration with external Application Programmable Interfaces (APIs). Find more at github.com/leonkraversky.
Techno-economic modeling for conventional and renewable electricity generation and storage projects with expertise in solar PV facilities. Techno-economic modeling involves analyzing various factors such as project costs, system performance, energy production, future energy and electricity pricing, equipment selection, and operation and maintenance expenses. By considering these variables, it becomes possible to estimate the levelized cost of electricity, assess the project's profitability, and optimize the design and configuration of the solar PV facility. This modeling approach provides valuable insights for stakeholders, enabling informed decision-making, risk mitigation, and the identification of opportunities for cost reduction and performance improvement.
Developing custom system simulations with expertise in energy projects. These simulations involve the creation of virtual models that replicate the behavior and performance of physical systems. Professionals in this field can design and implement custom simulations tailored to specific project requirements. These simulations enable detailed analysis and optimization of system performance and operational parameters. By utilizing advanced modeling techniques, such as computational fluid dynamics, dynamic system modeling, and data-driven approaches, these simulations can provide valuable insights into system behavior, efficiency, and potential challenges. Custom system simulations play a vital role in decision-making, allowing stakeholders to assess different design options, evaluate the impact of various factors, and identify opportunities for improvement.