Archives: Research Area

Energy Systems

Energy systems

Electricity cannot be economically stored at utility scales. Supply and demand must be balanced at all times, and the structure of the transmission grid massive amounts of inefficiency. In order to deal with these issues, and to ensure reliable access to power, the global standard is to centralize control under Independent System Operators, who coordinate […]

Machine Learning

machine learning

Invenia’s machine learning is focused on systems with a fundamental importance to everyday life, but which are not dealt with efficiently. Our central interest is in optimizing complex decision-making and resource usage under uncertainty. In particular, the electricity grid offers data with unique properties, including many time series with complex structures, and operations that change […]

Development, Architecture and Operations

At Invenia, software development expertise is applied to building and optimizing our distributed machine learning system: the Energy Intelligence System (EIS). Developers at Invenia also build and support the underlying systems and foundational technical tools, focusing on long-term solutions while also addressing current needs and anticipating future requirements. The success and versatility of these systems […]

Complex Systems

complex systems

Complex Systems is a broad area of research focused on studying systems made of a large number of interacting components and the emergence of complex collective behaviors. Social systems, the brain, and electricity grids are examples. A related area of interest is Complex Adaptive Systems, referring to systems reorganizing themselves to solve complex problems. Neural […]


Our interest in finance tools and techniques stems from our work in electricity grids, which provide unique challenges with transmission due to the physical properties of electricity. We are studying risk, the processes that improve the efficiency of the grid and the consequences of regulatory changes. There are also many interesting connections between finance, statistical […]