Grid-Connected Solar-WECS: A Database Performance Analysis

Abstract

Background: Integrating hybrid grid-connected Solar Photovoltaic (PV) and Wind Energy Conversion Systems (WECS) is critical for mitigating the intermittency of standalone renewable energy sources and improving grid stability. Objective: This paper presents a database-driven framework to analyze the performance, seasonal dynamics, and database storage optimization of a co-located Solar-WECS using 12 months of high-resolution operational and meteorological data. Methodology: Utilizing time-coincident datasets from NSRDB, NREL WIND Toolkit, and BC-HRRR, the framework evaluates key performance indicators (KPIs) like energy generation, capacity factor, and inverter efficiency. The data pipeline benchmarks multiple storage architectures—including HDF5 and optimized relational/NoSQL schemas—for query latency and throughput. Results: Statistical analysis confirms that the complementary nature of solar and wind resources yields higher annual energy output and improved capacity factors compared to standalone PV systems. Furthermore, the established normalized database framework effectively tracks KPI deviations, offering a scalable foundation for predictive maintenance and intelligent energy management