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AI-Powered Smart Grid Optimization System for Renewable Energy Provider

apriorit.com

Energy & natural resources

Utilities

Operational Inefficiencies in Renewable Energy Management

The client faces challenges in manual energy trading operations, suboptimal battery utilization, and reliance on third-party forecasting services. Current processes lead to energy waste, missed profit opportunities during market fluctuations, and increased operational costs due to lack of real-time automation.

About the Client

Mid-sized renewable energy company operating solar farms with battery storage systems in the US market

Key Project Goals

Automate energy trading and battery management operations
Optimize energy sales profitability through AI-driven market predictions
Reduce dependency on external forecasting services
Enhance grid stability through intelligent surplus/deficit management
Improve operational efficiency by 40% through automation

Core System Capabilities

Solar energy production forecasting module using site-specific weather data
Energy demand/supply analysis module with market price prediction
Automated dispatch agent for battery charging/discharging and energy trading
Real-time analytical dashboard for operational monitoring
Integration with existing ERP and energy exchange platforms

Technology Stack

JavaScript-based dispatch agent

AWS cloud infrastructure

AI/ML algorithms for predictive analytics

Real-time data processing frameworks

Secure API integrations

System Integrations

Client's existing ERP system
Energy exchange trading platform APIs
Weather data sources (satellite, ground stations)
Solar farm IoT monitoring systems
Battery management systems

System Requirements

High-availability architecture (99.9% uptime)
Real-time processing with <5-minute latency
Data security with private network implementation
Scalable infrastructure for future expansion
Regulatory compliance with energy market standards

Expected Business Outcomes

Implementation of this solution is expected to reduce operational costs by 35%, increase energy sales profitability by optimizing 30% of total production pricing, eliminate third-party service dependencies, and enhance grid stability through intelligent battery management. The system will enable full automation of trading decisions while maintaining compliance with regulatory requirements.