
Worked on the Houjio/HarmoniQ repository to build and enhance wind energy analytics infrastructure, focusing on scalable data processing and park-level reporting. Developed core features including wind turbine and wind farm data models, a Flask-based weather data interface, and aggregation logic for wind production at the farm level. Leveraged Python, SQL, and CSS to implement robust backend systems, integrate external data sources, and refine database schemas. Addressed data accuracy by improving weather data handling and correcting power calculation logic. Emphasized maintainability through code refactoring, dependency management, and removal of obsolete components, supporting reliable analytics and streamlined onboarding of new data sources.
April 2025 (Houjio/HarmoniQ): Delivered park-level aggregation for wind turbine production and refactored calculations to operate at wind-farm level, accompanied by updates to the database schema and data loading scripts to support park-centric analytics. Implemented a bug fix for ice_loss_factor by converting temperatures to Kelvin and adjusting wind power calculation to ignore wind direction, ensuring correct temperature handling and accurate power estimates. These changes enhance reporting scalability across wind farms and improve data accuracy for forecasting and decision-making.
April 2025 (Houjio/HarmoniQ): Delivered park-level aggregation for wind turbine production and refactored calculations to operate at wind-farm level, accompanied by updates to the database schema and data loading scripts to support park-centric analytics. Implemented a bug fix for ice_loss_factor by converting temperatures to Kelvin and adjusting wind power calculation to ignore wind direction, ensuring correct temperature handling and accurate power estimates. These changes enhance reporting scalability across wind farms and improve data accuracy for forecasting and decision-making.
March 2025 (Houjio/HarmoniQ) delivered enhancements to wind energy modeling and maintained code quality. Key business value: enabling accurate wind energy production simulations in the QC region for better planning and optimization, while preserving stable functionality. Activities focused on feature delivery with a minimal risk of regression.
March 2025 (Houjio/HarmoniQ) delivered enhancements to wind energy modeling and maintained code quality. Key business value: enabling accurate wind energy production simulations in the QC region for better planning and optimization, while preserving stable functionality. Activities focused on feature delivery with a minimal risk of regression.
February 2025 monthly summary for Houjio/HarmoniQ: Delivered foundational data models and data infrastructure enhancements for wind turbine and wind farm management, launched a Flask-based weather data interface, and integrated external data sources. Notable improvements include robust wind turbine weather data handling, removal of obsolete components, and dependency updates enabling web scraping and Env Canada data. These efforts improve data accuracy, enable farm-level analytics, and expand data sources, driving operational efficiency and informed decision-making.
February 2025 monthly summary for Houjio/HarmoniQ: Delivered foundational data models and data infrastructure enhancements for wind turbine and wind farm management, launched a Flask-based weather data interface, and integrated external data sources. Notable improvements include robust wind turbine weather data handling, removal of obsolete components, and dependency updates enabling web scraping and Env Canada data. These efforts improve data accuracy, enable farm-level analytics, and expand data sources, driving operational efficiency and informed decision-making.
Monthly summary for 2025-01: Completed Wind Energy Analytics Groundwork in Houjio/HarmoniQ, establishing the foundation for wind data processing and analytics. Implemented core dependencies (nrel-pysam, windpowerlib, geopandas), integrated PySAM, and added initial wind turbine data processing capabilities and data import scaffolding from the NREL toolkit. Refactored the data import flow to prepare for future data sources and removed an obsolete NREL data query file to clean the repository. These changes position the team for scalable wind energy analytics and faster onboarding of new data sources.
Monthly summary for 2025-01: Completed Wind Energy Analytics Groundwork in Houjio/HarmoniQ, establishing the foundation for wind data processing and analytics. Implemented core dependencies (nrel-pysam, windpowerlib, geopandas), integrated PySAM, and added initial wind turbine data processing capabilities and data import scaffolding from the NREL toolkit. Refactored the data import flow to prepare for future data sources and removed an obsolete NREL data query file to clean the repository. These changes position the team for scalable wind energy analytics and faster onboarding of new data sources.

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