AI Powered Renewables

Data scientists for green energy assets, p2x applications, green hydrogen and electrolyser plants
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Cost competitive Renewables with best locations

Find ideal locations for your renewable sources maximising return on investments, reach carbon emissions reduction goals faster and reduce the cost of each unit of renewable energy produced for your solar, wind and biogas applications. Scale up and optimise with higher costs efficiencies in comparison to fossil fuels.

Cost competitive renewables compared to fossil fuels

Reduce the cost of per unit of renewable energy produced through your solar generators, wind energy farms and biogas plants. Become cost competitive much faster in renewable hydrogen production, in comparison to the cost of fossil fuels. Dramatically reduce the cost of electrolytic hydrogen with reduction in material costs.

Identify ideal locations for your renewable plants

Leverage on the best renewable resources in the world, with ideal locations, for solar and wind energy plants, maximising sun-hours and ensuring minimised rainfall, resulting in the low-cost, high-capacity renewables that is essential for low-cost power-to-gas, hydrogen production, or other power-to-x applications with higher return on investments.

Demo plants for green hydrogen or other emerging applications

Data-driven, automated or semi-automated demo plants or pilot projects for further use of green hydrogen in oil & refinery industry to desulphurise fuels, as feed stock in chemicals or fertilisers manufacturing, energy efficient steel production through DRI, cement factories, and carbon neutral data centres. Production of synthetic fuels, natural gas (SNG), via electrolytic production of hydrogen, using renewable energy sources.

Low cost giga-watt scale and industrial electrolysers

Optimise and scale up electrolysis processes for industrial scale production of renewable hydrogen. Increase the capacity utilisation through high-efficiency electrolysis, thereby decreasing variable per unit costs of hydrogen production. Deliver bulk, low-cost and zero-carbon hydrogen through gigawatt-scale PEM electrolysis processes.

Cost efficient renewable storage solutions

Faster prototyping of storage solutions in the smallest space, cost-efficient transportation of hydrogen and establishing end-to-end hydrogen networks connected to the utilities grid, with an integrated value chain that includes industrial customers, hydrogen filling stations and end users.

High capacity utilisation and investor transparency

Identify system faults and restore failure faster with predictive diagnostic models. With higher capacity utilisation you can reduce the cost of running your power-to-x (p2x) applications and electrolysis plants, and also build innovative storage solutions for renewables. Get higher transparency for the banks, investment funds and asset owners with changing environmental, operational, trading, market, demand and supply data.
Predictive Maintenance
Speed up system fault identification, restore failures faster at the most critical points, do real-time maintenance and identification of ideal maintenance schedules, through predictive diagnostics, enabled by rich data, for renewable plants and hydrogen production facilities. Get all the information necessary to support the management of an asset. For example, its precise location, operational data, information about work carried out and its existing condition.
Low cost Transmission and Distribution
Innovative storage, transmission and distribution solutions, for renewable electricity or p2x plants, managing times of high generation, that can be used later at times of low generation. End-to-end logistics for power-to-gas projects, use of green hydrogen in mobility, injection into the gas grid via retrofitted existing gas pipelines.
High Capacity Utilisation & Forecasting
Improved parameters estimation and net load forecasting with high energy efficiency in renewable energy operations and hydrogen electrolysis process. Realise the full cost-reduction potential for electrolysers on partial-load as per intermittent power from renewables. Efficient cost dynamics as per enhanced ramp rates, different designs, operating conditions.
Trading, Markets & Investments
Higher transparency, minimizing investment risks and maximizing returns for investors, financing banks and asset owners through real-time insights into portfolio performance. Higher profits in intraday trading as per quickly changing weather and unplanned shortfall or surplus of power from solar or wind power plants. Predict asset availability and balancing mechanism market prices in near real time to successfully bid in the frequency response markets.

Smart inter-connected green grids with deep analytics and edge AI

Through millions of data points acquired from inter-connected systems in your renewable plants and green hydrogen production facilities, monitor and predict with confidence. You can pro-actively optimise processes, deploy IIoT and IoT wireless networks, and create AI models for managing smart transmission and distribution operations. Integrate your financial and investment models with macro data and plant level micro-data for maximum return on investment.
Data required for maintenance and monitoring of systems is already in the plants. With a connected renewable plant and related power-to-x applications, eliminate the time associated with traditional data acquisition and analysis. Reduce faults, monitor & predict wear and tear in renewable assets, wind turbines, PV projects, vibration analytics in the rotating equipment, and corrosion analytics in offshore plants. Take split seconds decisions regarding anomalies and defined system malfunctions.

AI driven, adaptive, pro-active process control optimization, plant floor intelligence, by integrating real-time operational data, and minimizing downtime with regards to industrial machinery at plants, logistics facilities, and construction sites. With number of skilled engineers declining, utilize digital technologies for optimization and greater sophistication in repair services for machinery and OEM products. Detect any unwanted machine behaviour using an anomaly detection process, which is an example of “unsupervised” machine learning. An algorithm learns the typical data patterns of normal machine behaviour based on historical data.

Smart delivery systems for gas units, with wireless communicating sensors at different points of the grids, managing pressure data for the local balance between consumption and production. Deep analytics through data obtained from robotic inspection devices that can inspect the inside of live, high-pressure gas pipelines. Minimise the time and cost of connecting to the transmission system.
Optimisation through big data analytics and faster pre-processing of data through Edge AI. Get higher Electrolsyer capacity utilisation and load factor, for cheaper cost of hydrogen production. Inflow forecasting models to help predict future water resource availability for hydro turbination and pumping optimization. Manage placement and topology of Distributed Renewable Energy in the distributed system.
Maximise return on investments by balancing needs between buying electricity at times of low prices. Bidding autobots to allow the project to capture the best revenue streams and increase the revenues of a battery. Get data from solar plants and integrating electricity markets for daily insights into global energy spot markets. Better predictions about the success of investments and the achievement of financial targets in solar through AI and IoT. By aggregating, structuring, analyzing, and consolidating technical and financial data, create maximum transparency.
Machine Learning for Renewable Energy

Get intelligent machine learning models to drive efficient green energy solutions by integrating data from sensors, drones, laser scanners, robotics applications, virtual reality, augmented reality, IIoT platform, edge devices, cloud, IoT. Run the AI models to power up your Deep Analytics, Mobile Apps, Web Apps, Remote Plant Access, Process Control solutions.

Digital Transformation for Power-to-X Applications and Green Hydrogen
Digital energy services platform focused on autonomy, machine-learning, advanced data analytics and control systems – aiming to unlock flexibility to provide cost and carbon savings for renewable customers, generators, operators and application providers.

For renewable plants, industrial power-to-x applications and green hydrogen production, the prime markets are ammonia, oil refining, iron and steel making, liquids for aviation, feedstock for synthetic organic materials production (for example electrofuels or e-fuels that are part of a power-to-X strategy), but there are huge cost and efficiency barriers that need to be overcome. Hydrogen can help tackle many critical energy challenges and decarbonise a range of sectors, where it is proving difficult to meaningfully reduce emissions. In addition, it increases flexibility in power systems, help reduce curtailment in grids with a high share of variable renewable electricity. For the costs to be lowered, plants must run at a higher utilisation rate, have better predictive capabilities, and strike a balance with daily market prices.

With a digitally powered, reliable, sustainable, resilient and modern green energy infrastructure accelerate your climate change goals and achieve cost feasibility faster.