From Load Profiling to Resilient Solar Availability: An Engineering Management Framework for Optimizing Distributed PV Systems in U.S. Facilities

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@article{1719878,
      author = {Godsave Archford Sajanga, Gladman Nhamoinesu Machekera, Patronella Siphatisiwe Mtemeli, Malvern Munashe Dongo, Munashe Naphtali Mupa},
      title = {From Load Profiling to Resilient Solar Availability: An Engineering Management Framework for Optimizing Distributed PV Systems in U.S. Facilities},
      journal = {Iconic Research And Engineering Journals},
      year = {2026},
      volume = {10},
      number = {1},
      pages = {2688-2703},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1719878.pdf},
      abstract = {Distributed photovoltaic (PV) systems have become central to decarbonisation, facility resilience, and electricity-cost management in the United States. Yet many facility-scale installations underperform because design decisions are made around nominal capacity rather than operational load shape, inverter availability, thermal behaviour, commissioning quality, maintenance discipline, and lifecycle risk. This paper develops an engineering-management framework that links load profiling, component selection, commissioning protocols, preventive maintenance, performance validation, documentation, and lifecycle cost-risk analysis into a single operating model for resilient solar availability in U.S. facilities. The paper uses secondary data from the Kaggle Solar Power Generation Data dataset, which contains inverter-level PV generation and weather-sensor data collected at two solar plants over a 34-day period, and triangulates those data with published PV reliability, O&M, and performance literature. The analysis shows that PV availability is not merely a generation problem; it is a management-system problem involving demand forecasting, conversion efficiency, module-temperature exposure, inverter variation, sensor quality, maintenance scheduling, and evidence-based documentation. The Kaggle-based evidence indicates that daily yield may appear similar across plants while DC-to-AC conversion performance, cumulative yield, and maintenance-event signatures differ materially. Published analysis of the same dataset reports mean daily yields of approximately 3,295.97 kWh and 3,294.89 kWh for Plants 1 and 2, respectively, while also identifying strong correlations between module temperature and ambient temperature, and between module temperature and irradiation. The proposed framework converts these findings into a practical facility protocol: profile the load before sizing, select components against operating conditions, commission against measurable acceptance criteria, maintain based on risk and performance evidence, validate availability continuously, and document lifecycle decisions for auditability. The study contributes an applied model for engineers, facility managers, energy consultants, and public-interest energy practitioners seeking to improve solar reliability, resilience, and return on investment in distributed PV systems.},
      keywords = {Distributed Photovoltaic Systems, Load Profiling, Solar PV Availability, Preventive Maintenance, Commissioning; Engineering Management, Energy Resilience, Lifecycle Cost-Risk Analysis, Facility Energy Optimization},
      month = {July},
      doi = {https://doi.org/10.64388/IREV10I1-1719878}
  }