Cloud-Based Asset Management
Cloud-Based Asset Management for Renewable Energy Plants
Cloud-Based Asset Management for Renewable Energy Plants
Cloud-Based Asset Management for Renewable Energy Plants
For this project, Meteocontrol wanted to develop a cloud-based asset management platform (mc Assetpilot) that could optimize renewable energy operations, streamline financial tracking, and enhance operational decision-making.
For this project, Meteocontrol wanted to develop a cloud-based asset management platform (mc Assetpilot) that could optimize renewable energy operations, streamline financial tracking, and enhance operational decision-making.
For this project, Meteocontrol wanted to develop a cloud-based asset management platform (mc Assetpilot) that could optimize renewable energy operations, streamline financial tracking, and enhance operational decision-making.
Renewable Energy
Cloud
Microservices
Cloud-Based Asset Management
Cloud-Based Asset Management
Cloud-Based Asset Management
Client overview
Client overview
Client overview
Meteocontrol is a global leader in photovoltaic (PV) monitoring and control systems, specializing in independent energy management solutions for solar plants, wind farms, and battery storage systems. With over two decades of experience in the renewable energy sector, Meteocontrol's software and hardware solutions provide real-time monitoring, data analytics, and predictive maintenance for renewable energy operators across Europe, North America, and Asia.
For this project, Meteocontrol wanted to develop a cloud-based asset management platform (mc Assetpilot) that could optimize renewable energy operations, streamline financial tracking, and enhance operational decision-making. The goal was to build a scalable, all-in-one platform that integrates seamlessly with their existing monitoring systems while providing advanced analytics, financial reporting, and contractor management features.
Meteocontrol is a global leader in photovoltaic (PV) monitoring and control systems, specializing in independent energy management solutions for solar plants, wind farms, and battery storage systems. With over two decades of experience in the renewable energy sector, Meteocontrol's software and hardware solutions provide real-time monitoring, data analytics, and predictive maintenance for renewable energy operators across Europe, North America, and Asia.
For this project, Meteocontrol wanted to develop a cloud-based asset management platform (mc Assetpilot) that could optimize renewable energy operations, streamline financial tracking, and enhance operational decision-making. The goal was to build a scalable, all-in-one platform that integrates seamlessly with their existing monitoring systems while providing advanced analytics, financial reporting, and contractor management features.
Meteocontrol is a global leader in photovoltaic (PV) monitoring and control systems, specializing in independent energy management solutions for solar plants, wind farms, and battery storage systems. With over two decades of experience in the renewable energy sector, Meteocontrol's software and hardware solutions provide real-time monitoring, data analytics, and predictive maintenance for renewable energy operators across Europe, North America, and Asia.
For this project, Meteocontrol wanted to develop a cloud-based asset management platform (mc Assetpilot) that could optimize renewable energy operations, streamline financial tracking, and enhance operational decision-making. The goal was to build a scalable, all-in-one platform that integrates seamlessly with their existing monitoring systems while providing advanced analytics, financial reporting, and contractor management features.
Challenges
Challenges
Challenges
Disparate Energy Asset Management Systems
• Existing monitoring platforms provided real-time operational data but lacked financial and contractor management tools, requiring users to manage assets manually across multiple platforms • A fragmented data landscape resulted in inefficiencies in asset tracking, budgeting, and revenue forecasting • Operators needed a unified view across diverse renewable energy assets (solar, wind, battery storage)
Complex Integration Requirements
• The new system needed to seamlessly integrate with Meteocontrol's existing cloud platform without disrupting core monitoring capabilities
• Real-time synchronization of asset performance data required robust API architecture and data transformation logic
• Compatibility with multiple asset types required flexible data models capable of handling diverse IoT sensor feeds and performance metrics
Enterprise-Grade Cloud Architecture Needs
• The platform required multilingual support and high scalability to support users across Europe, North America, and Asia
• Data sovereignty and regulatory compliance across multiple jurisdictions necessitated a sophisticated security architecture
• High-volume data processing from thousands of sensor inputs demanded efficient database design and query optimization
Disparate Energy Asset Management Systems
• Existing monitoring platforms provided real-time operational data but lacked financial and contractor management tools, requiring users to manage assets manually across multiple platforms • A fragmented data landscape resulted in inefficiencies in asset tracking, budgeting, and revenue forecasting • Operators needed a unified view across diverse renewable energy assets (solar, wind, battery storage)
Complex Integration Requirements
• The new system needed to seamlessly integrate with Meteocontrol's existing cloud platform without disrupting core monitoring capabilities
• Real-time synchronization of asset performance data required robust API architecture and data transformation logic
• Compatibility with multiple asset types required flexible data models capable of handling diverse IoT sensor feeds and performance metrics
Enterprise-Grade Cloud Architecture Needs
• The platform required multilingual support and high scalability to support users across Europe, North America, and Asia
• Data sovereignty and regulatory compliance across multiple jurisdictions necessitated a sophisticated security architecture
• High-volume data processing from thousands of sensor inputs demanded efficient database design and query optimization
Disparate Energy Asset Management Systems
• Existing monitoring platforms provided real-time operational data but lacked financial and contractor management tools, requiring users to manage assets manually across multiple platforms • A fragmented data landscape resulted in inefficiencies in asset tracking, budgeting, and revenue forecasting • Operators needed a unified view across diverse renewable energy assets (solar, wind, battery storage)
Complex Integration Requirements
• The new system needed to seamlessly integrate with Meteocontrol's existing cloud platform without disrupting core monitoring capabilities
• Real-time synchronization of asset performance data required robust API architecture and data transformation logic
• Compatibility with multiple asset types required flexible data models capable of handling diverse IoT sensor feeds and performance metrics
Enterprise-Grade Cloud Architecture Needs
• The platform required multilingual support and high scalability to support users across Europe, North America, and Asia
• Data sovereignty and regulatory compliance across multiple jurisdictions necessitated a sophisticated security architecture
• High-volume data processing from thousands of sensor inputs demanded efficient database design and query optimization
Financial & KPI Tracking Complexity
• Asset managers required customizable financial dashboards with KPI tracking, revenue calculations, cash flow analysis, and budget comparisons
• The system needed to automate financial reporting while maintaining accuracy across multiple currencies and accounting standards
• Performance benchmarking across diverse asset types required standardized metrics with configurable thresholds
Advanced User Management Requirements
• Asset managers, contractors, and stakeholders needed centralized access to documents, maintenance logs, and user authorizations
• Security measures required strict role-based access control, preventing unauthorized modifications to financial and operational data
• Document workflow automation needed to support approval processes while maintaining audit trails
Financial & KPI Tracking Complexity
• Asset managers required customizable financial dashboards with KPI tracking, revenue calculations, cash flow analysis, and budget comparisons
• The system needed to automate financial reporting while maintaining accuracy across multiple currencies and accounting standards
• Performance benchmarking across diverse asset types required standardized metrics with configurable thresholds
Advanced User Management Requirements
• Asset managers, contractors, and stakeholders needed centralized access to documents, maintenance logs, and user authorizations
• Security measures required strict role-based access control, preventing unauthorized modifications to financial and operational data
• Document workflow automation needed to support approval processes while maintaining audit trails
Solution
Solution
Solution
Brightgrove assembled a specialized development team to design, build, and deploy Meteocontrol's new cloud-based asset management platform. The project followed an Agile Scrum methodology, ensuring rapid development cycles, continuous integration, and seamless collaboration with Meteocontrol's internal teams.
Unified Asset Management Platform
• Developed mc Assetpilot, a customized ERP solution designed specifically for renewable energy asset management
• Implemented a microservices architecture to enable modular development and incremental feature deployment
• Built a single sign-on (SSO) authentication system with OAuth 2.0, allowing users to access multiple applications within the Meteocontrol ecosystem without repeated logins
Advanced Integration Architecture
• Engineered a multi-protocol API gateway with OAuth 2.0 security and comprehensive OpenAPI documentation
• Implemented event-driven architecture using Apache Kafka with exactly-once processing guarantees
• Developed protocol-specific adapters (MQTT, Modbus, OPC-UA) for 15+ IoT device types with edge preprocessing
• Created a canonical data model with standardized metrics across solar, wind, and battery storage assets
• Implemented real-time data streaming with Kafka Streams for complex event processing (CEP)
• Built a service mesh architecture with circuit breakers and resilience patterns for high availability
Financial Analytics Engine
• Developed a real-time financial analytics pipeline with materialized views for sub-second dashboard rendering
• Implemented time-series forecasting models using statistical methods (ARIMA, Prophet) with 94% accuracy
• Created a parametric simulation engine for Monte Carlo analysis of financial scenarios with confidence intervals
• Built regulatory reporting automation with XBRL export supporting multiple accounting standards (IFRS, GAAP)
• Designed a custom ETL pipeline for daily financial data aggregation and reconciliation
• Implemented anomaly detection algorithms for early identification of performance deviations and revenue impacts
Secure Document & User Management
• Implemented RBAC (Role-Based Access Control) with granular permission settings
• Created a secure document repository with version control and audit logging
• Developed automated workflow engines for maintenance scheduling and contractor management
• Integrated digital signature capabilities for contract approvals and compliance documentation
Enterprise-Grade Cloud Infrastructure
• Architected a multi-region Kubernetes deployment with 99.99% SLA and automated failover capabilities
• Implemented blue-green deployment strategy with canary testing for zero-downtime updates
• Designed a comprehensive observability stack with distributed tracing (Jaeger), metrics collection (Prometheus), and centralized logging (ELK)
• Built GDPR-compliant data handling with pseudonymization, configurable retention policies, and automated data subject request handling
• Implemented infrastructure-as-code using Terraform with modular, reusable components for deployment consistency
• Created custom Kubernetes operators for automated database maintenance operations
• Established automated security scanning pipeline with vulnerability remediation workflows
• Deployed multilingual capabilities with server-side i18n supporting 12 languages and region-specific formatting
Brightgrove assembled a specialized development team to design, build, and deploy Meteocontrol's new cloud-based asset management platform. The project followed an Agile Scrum methodology, ensuring rapid development cycles, continuous integration, and seamless collaboration with Meteocontrol's internal teams.
Unified Asset Management Platform
• Developed mc Assetpilot, a customized ERP solution designed specifically for renewable energy asset management
• Implemented a microservices architecture to enable modular development and incremental feature deployment
• Built a single sign-on (SSO) authentication system with OAuth 2.0, allowing users to access multiple applications within the Meteocontrol ecosystem without repeated logins
Advanced Integration Architecture
• Engineered a multi-protocol API gateway with OAuth 2.0 security and comprehensive OpenAPI documentation
• Implemented event-driven architecture using Apache Kafka with exactly-once processing guarantees
• Developed protocol-specific adapters (MQTT, Modbus, OPC-UA) for 15+ IoT device types with edge preprocessing
• Created a canonical data model with standardized metrics across solar, wind, and battery storage assets
• Implemented real-time data streaming with Kafka Streams for complex event processing (CEP)
• Built a service mesh architecture with circuit breakers and resilience patterns for high availability
Financial Analytics Engine
• Developed a real-time financial analytics pipeline with materialized views for sub-second dashboard rendering
• Implemented time-series forecasting models using statistical methods (ARIMA, Prophet) with 94% accuracy
• Created a parametric simulation engine for Monte Carlo analysis of financial scenarios with confidence intervals
• Built regulatory reporting automation with XBRL export supporting multiple accounting standards (IFRS, GAAP)
• Designed a custom ETL pipeline for daily financial data aggregation and reconciliation
• Implemented anomaly detection algorithms for early identification of performance deviations and revenue impacts
Secure Document & User Management
• Implemented RBAC (Role-Based Access Control) with granular permission settings
• Created a secure document repository with version control and audit logging
• Developed automated workflow engines for maintenance scheduling and contractor management
• Integrated digital signature capabilities for contract approvals and compliance documentation
Enterprise-Grade Cloud Infrastructure
• Architected a multi-region Kubernetes deployment with 99.99% SLA and automated failover capabilities
• Implemented blue-green deployment strategy with canary testing for zero-downtime updates
• Designed a comprehensive observability stack with distributed tracing (Jaeger), metrics collection (Prometheus), and centralized logging (ELK)
• Built GDPR-compliant data handling with pseudonymization, configurable retention policies, and automated data subject request handling
• Implemented infrastructure-as-code using Terraform with modular, reusable components for deployment consistency
• Created custom Kubernetes operators for automated database maintenance operations
• Established automated security scanning pipeline with vulnerability remediation workflows
• Deployed multilingual capabilities with server-side i18n supporting 12 languages and region-specific formatting
Brightgrove assembled a specialized development team to design, build, and deploy Meteocontrol's new cloud-based asset management platform. The project followed an Agile Scrum methodology, ensuring rapid development cycles, continuous integration, and seamless collaboration with Meteocontrol's internal teams.
Unified Asset Management Platform
• Developed mc Assetpilot, a customized ERP solution designed specifically for renewable energy asset management
• Implemented a microservices architecture to enable modular development and incremental feature deployment
• Built a single sign-on (SSO) authentication system with OAuth 2.0, allowing users to access multiple applications within the Meteocontrol ecosystem without repeated logins
Advanced Integration Architecture
• Engineered a multi-protocol API gateway with OAuth 2.0 security and comprehensive OpenAPI documentation
• Implemented event-driven architecture using Apache Kafka with exactly-once processing guarantees
• Developed protocol-specific adapters (MQTT, Modbus, OPC-UA) for 15+ IoT device types with edge preprocessing
• Created a canonical data model with standardized metrics across solar, wind, and battery storage assets
• Implemented real-time data streaming with Kafka Streams for complex event processing (CEP)
• Built a service mesh architecture with circuit breakers and resilience patterns for high availability
Financial Analytics Engine
• Developed a real-time financial analytics pipeline with materialized views for sub-second dashboard rendering
• Implemented time-series forecasting models using statistical methods (ARIMA, Prophet) with 94% accuracy
• Created a parametric simulation engine for Monte Carlo analysis of financial scenarios with confidence intervals
• Built regulatory reporting automation with XBRL export supporting multiple accounting standards (IFRS, GAAP)
• Designed a custom ETL pipeline for daily financial data aggregation and reconciliation
• Implemented anomaly detection algorithms for early identification of performance deviations and revenue impacts
Secure Document & User Management
• Implemented RBAC (Role-Based Access Control) with granular permission settings
• Created a secure document repository with version control and audit logging
• Developed automated workflow engines for maintenance scheduling and contractor management
• Integrated digital signature capabilities for contract approvals and compliance documentation
Enterprise-Grade Cloud Infrastructure
• Architected a multi-region Kubernetes deployment with 99.99% SLA and automated failover capabilities
• Implemented blue-green deployment strategy with canary testing for zero-downtime updates
• Designed a comprehensive observability stack with distributed tracing (Jaeger), metrics collection (Prometheus), and centralized logging (ELK)
• Built GDPR-compliant data handling with pseudonymization, configurable retention policies, and automated data subject request handling
• Implemented infrastructure-as-code using Terraform with modular, reusable components for deployment consistency
• Created custom Kubernetes operators for automated database maintenance operations
• Established automated security scanning pipeline with vulnerability remediation workflows
• Deployed multilingual capabilities with server-side i18n supporting 12 languages and region-specific formatting
Technical implementation
Technical implementation
The Brightgrove team implemented a cloud-native architecture based on microservices and event-driven design principles. The platform's multi-layered architecture ensures separation of concerns while enabling scalability and resilience:
The Brightgrove team implemented a cloud-native architecture based on microservices and event-driven design principles. The platform's multi-layered architecture ensures separation of concerns while enabling scalability and resilience:
Data Ingestion layer
• Edge Gateway Integration. Custom-built adapters for various IoT protocols (MQTT, Modbus, OPC-UA)
• Data Normalization Pipeline. Stream processing with Kafka Streams for real-time data transformation
• Legacy System Connectors. REST/SOAP adapters for integration with existing SCADA systems
Core Services
• Backend Framework. Kotlin/Java microservices built on Spring Boot 2.7 with reactive programming patterns
• API Gateway. Spring Cloud Gateway with circuit breakers and rate limiting
• Authentication. OAuth 2.0/OIDC implementation with JWT tokens and RBAC
• Event Bus. Apache Kafka cluster for inter-service communication and event sourcing
Data Layer
• Relational Data. PostgreSQL 14 with partitioning for asset metadata
• Time-Series Data. TimescaleDB for high-performance telemetry storage
• Document Storage. S3-compatible object storage
• Analytics. Data warehouse implementation for historical analysis and reporting
• Caching. Redis for API response and calculation caching
Data Ingestion layer
• Edge Gateway Integration. Custom-built adapters for various IoT protocols (MQTT, Modbus, OPC-UA)
• Data Normalization Pipeline. Stream processing with Kafka Streams for real-time data transformation
• Legacy System Connectors. REST/SOAP adapters for integration with existing SCADA systems
Core Services
• Backend Framework. Kotlin/Java microservices built on Spring Boot 2.7 with reactive programming patterns
• API Gateway. Spring Cloud Gateway with circuit breakers and rate limiting
• Authentication. OAuth 2.0/OIDC implementation with JWT tokens and RBAC
• Event Bus. Apache Kafka cluster for inter-service communication and event sourcing
Data Layer
• Relational Data. PostgreSQL 14 with partitioning for asset metadata
• Time-Series Data. TimescaleDB for high-performance telemetry storage
• Document Storage. S3-compatible object storage
• Analytics. Data warehouse implementation for historical analysis and reporting
• Caching. Redis for API response and calculation caching
Frontened
• Web Application. Angular 15 SPA with lazy-loading modules
• Component Library. Custom component library with Material Design foundations
• State Management. NgRx for predictable state management
• Visualization. Custom charting components built on D3.js
Devops & Infrastructure
• Container Orchestration. Kubernetes with Helm charts for deployment
• CI/CD Pipeline. Jenkins with automated testing and deployment gates
• Infrastructure as Code. Terraform for cloud resource provisioning
• Monitoring. Prometheus and Grafana for metrics, ELK stack for logging
• Security Scanning. SonarQube for code quality and OWASP dependency scanning
Frontened
• Web Application. Angular 15 SPA with lazy-loading modules
• Component Library. Custom component library with Material Design foundations
• State Management. NgRx for predictable state management
• Visualization. Custom charting components built on D3.js
Devops & Infrastructure
• Container Orchestration. Kubernetes with Helm charts for deployment
• CI/CD Pipeline. Jenkins with automated testing and deployment gates
• Infrastructure as Code. Terraform for cloud resource provisioning
• Monitoring. Prometheus and Grafana for metrics, ELK stack for logging
• Security Scanning. SonarQube for code quality and OWASP dependency scanning
Technical achievements & Business Impact
Technical achievements & Business Impact
Technical achievements & Business Impact
The implementation delivered significant technical improvements with measurable business impact:
The implementation delivered significant technical improvements with measurable business impact:
Data Processing Capacity
Data Processing Capacity
Data Processing Capacity
System handles 50,000+ IoT data points per second with sub-100ms latency
System handles 50,000+ IoT data points per second with sub-100ms latency
System handles 50,000+ IoT data points per second with sub-100ms latency
Database Performance
Database Performance
Database Performance
Achieved 99.7th percentile query response time under 250ms for financial dashboards
Achieved 99.7th percentile query response time under 250ms for financial dashboards
Achieved 99.7th percentile query response time under 250ms for financial dashboards
API Throughput
API Throughput
API Throughput
REST API gateway sustains 1,200+ requests per second with 99.99% availability
REST API gateway sustains 1,200+ requests per second with 99.99% availability
REST API gateway sustains 1,200+ requests per second with 99.99% availability
Elastic Scaling
Elastic Scaling
Elastic Scaling
Auto-scaling infrastructure adjusts to 5x load variation with no performance degradation
Auto-scaling infrastructure adjusts to 5x load variation with no performance degradation
Data Compression
Data Compression
Data Compression
Implemented specialized time-series compression reducing storage requirements by 73%
Implemented specialized time-series compression reducing storage requirements by 73%
Implemented specialized time-series compression reducing storage requirements by 73%
85% Improvement in Data Quality
85% Improvement in Data Quality
85% Improvement in Data Quality
Anomaly detection and validation pipelines significantly reduced data errors
Anomaly detection and validation pipelines significantly reduced data errors
Conclusion
Conclusion
Conclusion
This solution demonstrates how modern cloud architecture can address complex challenges in the renewable energy sector:
• IoT Integration at Scale. The platform shows how diverse sensor networks can be unified into a coherent data platform
• Financial-Technical Integration. Bridges the gap between operational technology (OT) and information technology (IT)
• Global SaaS Deployment. Illustrates best practices for multilingual, multi-region cloud applications
• Security Compliance. Demonstrates how to maintain strict data security while enabling collaboration across stakeholder groups
• Modular Architecture. Shows how microservices can enable flexible, adaptable enterprise applications
This solution demonstrates how modern cloud architecture can address complex challenges in the renewable energy sector:
• IoT Integration at Scale. The platform shows how diverse sensor networks can be unified into a coherent data platform
• Financial-Technical Integration. Bridges the gap between operational technology (OT) and information technology (IT)
• Global SaaS Deployment. Illustrates best practices for multilingual, multi-region cloud applications
• Security Compliance. Demonstrates how to maintain strict data security while enabling collaboration across stakeholder groups
• Modular Architecture. Shows how microservices can enable flexible, adaptable enterprise applications
This solution demonstrates how modern cloud architecture can address complex challenges in the renewable energy sector:
• IoT Integration at Scale. The platform shows how diverse sensor networks can be unified into a coherent data platform
• Financial-Technical Integration. Bridges the gap between operational technology (OT) and information technology (IT)
• Global SaaS Deployment. Illustrates best practices for multilingual, multi-region cloud applications
• Security Compliance. Demonstrates how to maintain strict data security while enabling collaboration across stakeholder groups
• Modular Architecture. Shows how microservices can enable flexible, adaptable enterprise applications
Download extended case study in .pdf