CIO Bulletin

BluWave-ai – Developing state-of-the-art techniques like supercomputing and edge computing to improve Clean Energy

Global energy demands are growing every year. And, fossil fuels won’t be able to fulfill our energy needs in the future. Carbon emissions from fossil fuels have already hit an all-time high due to increased energy consumption. On the other hand, renewable energy is emerging out as a reliable alternative to fossil fuels. It is much safer and cleaner than conventional sources. With the advancements in technology, the renewable energy sector has made significant progress in the last decade. However, there are still a few challenges in this sector that can be addressed with the help of emerging technologies. Technologies like AI and Machine Learning can analyze the past, optimize the present, and predict the future. And, AI in the renewable energy sector can resolve most of the challenges. While the biggest goal of AI in renewable energy is to manage the intermittency, it can also offer improved safety, efficiency, and reliability. It can help you understand the energy consumption patterns, identify the energy leakage and health of the devices.

BluWave-ai is one such company that brings state-of-the-art techniques from supercomputing, artificial Intelligence, and edge computing to the world of distributed renewable energy. With distributed resources, clean energy can be produced anywhere by anyone, moving the world away from centralized carbon-based emitting sources. But real-time computing is needed to predict production and optimize how to use these resources. Electrical output from renewable energy sources like wind and solar fluctuates and is inherently difficult for utilities to manage. This results in renewables generation often being under-utilized, with operators relying on fossil fuels as a fallback. Its grid energy optimization platform balances the cost, availability, and carbon footprint of different energy sources - renewable and non-renewable - with energy demand in real-time. BluWave-ai is building the world's premier renewable energy AI company and has won regional, national and international awards. Its team includes top researchers and innovators from ten different countries, all committed to helping drive the energy transition to a decarbonized economy around the planet.

Cutting-Edge AI Services and Solutions Offered to Advance in Clean Energy Sector

Energy Optimization Platform: BluWave-ai offers an AI-enabled software-as-a-service (SaaS) solution allowing for rapid deployment with a low upfront cost and immediate operating savings. BluWave-ai’s platform uses the latest power systems and machine-learning theory, and is tailored to the most up-to-date needs of smart grids, microgrids and electric vehicle fleets. It is purpose-built for these energy industry applications, and is free of the limitations other legacy products may have. The platform consumes data from grid IoT devices (sensors, meters) and delivers quasi-real-time dispatch commands. It is predictive, performing analytics on incoming data, discovering patterns, and improving its performance as it operates and, unlike conventional optimization systems, adapts to changing situations.

EV Fleet Orchestrator: It’s a highly complex task to effectively manage the operation and charging of EV fleets, along with building energy management, local generation and storage, and energy purchases, plus meeting service levels and turnaround time requirements. It requires the intelligent coordination of separate but inter-related systems and the ability to do so in real-time. No one system or human operator is up to the full task. This is where the BluWave-ai EV Fleet Orchestrator offers a novel solution. Built on BluWave-ai’s distributed AI-enabled platform, the EV Fleet Orchestrator optimizes energy costs in real-time by consolidating the many parameters of energy and fleet operations, providing a holistic view and coordinated energy dispatch/control.

BluWave-ai Atlas: It manages, standardizes, and curates the vast amounts of dynamic data from IoT sensors and meters, weather services, and other live data from customer operations, and provides tools to view and display both historical and current data. Atlas' visualization tools turns data into valuable insights to improve operations and inform planning activities. BluWave-ai Atlas includes ready-to-deploy AI models and a database of historical climate, weather, renewable generation, and forecast data from multiple sources at locations worldwide, making available this data to train BluWave-ai models for new sites where customers may not have their own available. This greatly reduces deployment time so that customers can quickly benefit from improved operational performance.

The Visionary Leader

Devashish Paul is the founder and Chief Executive Officer if BluWave-ai. After an extensive career in the semiconductor industry focused on supercomputing, artificial intelligence, and networking. He is a life-long cyclist and nature enthusiast using human powered energy for personal transportation to explore the world. Devashish founded the company combining his interest in clean energy technologies with advanced computing and networking technologies.

Devashish earned a Bachelor of Engineering degree from Royal Military College followed by a Masters in Electrical Engineering (Digital Signal Processing) and an MBA in Marketing, both from the University of Ottawa. He is a veteran of the Royal Canadian Air Force. Besides, he is a 31-time Ironman triathlon finisher, has coached master’s athletes to 100+ finishes, was a coach for 14 years with the Kanata Nordic Ski Club, and has raced for Canada in 10 world championships.