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Offer grid-scale storage for energy transition

Overview

A responsive ecosystem for utility-scale storage empowers AI-first power plants to accelerate energy transition. Further, system-level modeling of storage integration with the energy network helps aggregate renewables capacity for reliable grid services.

Infosys Utilities orchestrate a clean energy ecosystem, powered by AI, for seamless renewables and storage integration and adaptive control. It empowers utilities to manage variable power generation from low-carbon sources while maintaining grid stability. Our learning systems and AI agents not only optimize decentralized generation and storage to minimize grid dependence, but also support R&D strategies for integrating material-level advancements and addressing system-level requirements.

Infosys supports diverse types of storage systems – mechanical, electrical, thermal, chemical, electromagnetic, and electrochemical such as flow batteries and Battery Energy Storage Systems (BESS). Our highly configurable digital energy platforms integrate distributed energy resource management and energy storage management with Supervisory Control and Data Acquisition (SCADA) systems via gateway converters. This provides high-frequency operational telemetry for real-time distribution network management.

Infosys capabilities:

Cloud-based energy management platforms support grid-side, front-of-the-meter storage farms as well as behind-the-meter residential photovoltaic systems and domestic batteries

Autonomous AI agents for BESS management optimize battery charging / discharging cycles based on real-time grid and market parameters such as price trends, weather forecasts, and consumption

AI / ML-driven solutions sanitize datasets generated by microgrids and distributed systems, thereby ensuring accurate forecasting

Our multi-agent reinforcement learning solutions autonomously resolve the challenges in optimizing power flow in renewable-intensive distribution systems.

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Accelerate renewables and storage integration

  • Techno-economic, financial and environmental feasibility assessment of storage installations, including supercapacitors and industrial-grade as well as utility-scale battery packs.
  • Grid infrastructure modernization programs support community inverter systems, neighborhood-level storage hubs, and grid-level storage management.
  • AI solutions facilitate load balancing via optimal dispatch of stored energy.
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Challenges & Solutions

Machine learning (ML) algorithms predict wind speed and solar irradiance 36-48 hours in advance, which enables accurate power output forecasting and grid planning.

AI platforms boost grid stability and reliability by optimizing power flow distribution and redirecting stored energy automatically.

The modular design and rapid response capability of battery storage systems effectively manages variations in grid conditions, including voltage, frequency and power flow.

Resource Center

White paper

Battery storage and contract management: Creating a renewable future

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Point of view

Scaling vehicle-to-grid (V2G) with a platform-based solution

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Brochure

Resource Innovations-Infosys Electric Vehicle Supply Equipment Onboarding Solution

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Article

Charging station configurator for electric vehicles

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