Methodology for the Physical Validation and Optimal Sizing of Photovoltaic Generation Systems to Estimate Firm Energy for the Reliability Charge (ENFICC)

Unofficial AI-generated summary based on the public title and abstract. Not an official translation.

🔬研究者:Offers a reproducible, data-driven framework for PV firm energy estimation that can be adapted to other regions.

🏢実務担当者:Provides a step-by-step workflow for validating and sizing PV systems to meet reliability requirements, potentially reducing curtailment risk.

🏛政策担当者:Highlights the need for physical validation in capacity mechanisms, informing regulatory design for renewable integration.

The integration of photovoltaic (PV) generation into power systems requires design methods that evaluate not only annual energy yield or installed capacity, but also the dependable contribution of the plant under critical supply conditions. This paper presents a prototype-driven methodology for the physical validation and optimal sizing of a grid-connected PV generation system aimed at estimating, auditing, and evaluating ENFICC-oriented photovoltaic sizing alternatives under the Colombian reliability framework. The workflow integrates three input databases: a ten-year hourly meteorological database from NASA POWER for 2016--2025, a filtered and expanded PV module catalog based on the CEC database, and a filtered and expanded inverter catalog based on the Sandia database. These inputs feed a sequential modeling chain that estimates clearness index, irradiance decomposition, plane-of-array irradiance, cell temperature, DC power, AC power, monthly equivalent daily energy, net effective capacity, regulatory upper bound, and final ENFICC. The methodology was first validated using the installed PV system in La Tebaida, Colombia, as a local physical reference. For the validation case, the model used 252 Jinko Tiger Neo JKM625N-78HL4-BDV modules, two Solis 60K-LV-5G inverters, 157.5 kWp DC, 120 kW AC, fixed topology, and an hourly local validation dataset derived from the installed system. The NASA-based physical validation produced a critical-month energy of 548.5~kWh/day and a final ENFICC of 438.8~kWh/day after applying the secondary-data factor $f_{\mathrm{sec}}=0.8$. After applying the corrected physical filters and monthly coverage checks to the NASA POWER physical irradiance series, ten independent GA runs produced final ENFICC values between 283.5 and 384.2 kWh/day, with a mean of 349.7 kWh/day. The fitness function in all GA runs was evaluated using the corrected NASA POWER physical irradiance series, not an alternative irradiance series. These corrected results do not support the previously inflated optimization values; instead, they show that the local physical validation stage is essential before interpreting GA outputs. The proposed methodology contributes to clean-energy planning by linking renewable-energy integration, physical validation, reproducible computation, and regulatory firm-energy estimation within a single engineering workflow.

• Research Square https://doi.org/10.20944/preprints202607.1380.v1first seen 2026-07-25 04:38:27