Aug 2026· Journal of Technical Education Science· 0 citations· 15 references
Abstract
High short-term variability in photovoltaic (PV) output causes inverter clipping, curtailment, and revenue loss in grid-export-only solar plants. This paper presents a forecast-guided operational framework that integrates an hour-ahead Gradient Boosted Trees (GBT) model with a receding-horizon mixed-integer linear programming (MILP) dispatch strategy for Battery Energy Storage Systems (BESS). A dataset of 30,579 hourly samples, combining NASA POWER meteorological variables and AC-side PV measurements from March 2022 to September 2024, is used to train and evaluate the forecasting model. The GBT achieves strong performance with an RMSE of 0.152 kW and a MAPE of 6.65%. These forecasts drive the MILP scheduler, which incorporates inverter limits, state-of-charge dynamics, non-simultaneous charge/discharge constraints, and throughput-based degradation. A techno-economic comparison of BESS capacities from 250 to 1,000 kWh under fixed PPA and Time-of-Use tariffs shows that all capacities ≥ 250 kWh fully eliminate curtailment, while the TOU–750 kWh configuration maximizes economic returns. The results highlight the importance of moderate BESS sizing for cost-effective deployment in grid-export-only PV systems.
The variability of photovoltaic (PV) generation poses significant challenges to the reliable and efficient operation of grid-connected microgrids. Accurate PV output power forecasting and efficient energy scheduling strategies are essential not only for optimizing PV system operation but also for improving the overall...
Forecast errors in direct normal irradiance (DNI) and load demand can reduce the economic performance of concentrated solar power (CSP) plants with thermal energy storage (TES). This study compares a day-ahead-only strategy (DA-only), rolling particle swarm optimization (DA + RollPSO), and model predictive control (DA...
The increasing integration of decentralised photovoltaic (PV) systems and electric vehicles into low-voltage (LV) distribution networks introduces significant variability in net-load patterns, exemplified by the “duck curve” (daytime overgeneration) and sharp peak demands. Addressing these challenges is critical to mai...
A. Faustine, Lucas Pereira· The 12th International Confe...· 0 citations
Introduction Radial distribution grids require renewable planning methods that jointly account for meteorological generation, WT/PV capacity allocation, and smart-inverter voltage support. Methods An ANN-PSO-VoltVAR framework was developed using 2012-2021 NASA POWER irradiance, wind-speed, and temperature data for In S...
Selman Djeffal, Badreddine Bendriss, Abdelhamid Ghoul et al.· Frontiers in Artificial Inte...· 0 citations
Wind power forecasts are commonly trained to minimize statistical errors, although the thermal schedule based on a forecast ultimately incurs asymmetric recourse costs. To connect forecast training with this dispatch consequence, a dispatch-value-oriented forecasting (DVOF) framework is developed by coupling a Mamba-st...
Sen Wang, Wenjie Zhang, Yonghui Sun et al.· Energies· 0 citations
Battery energy storage systems (BESS) paired with rooftop photovoltaics (PVs) can deliver measurable cost savings under time-of-use (TOU) electricity tariffs; however, the relative performance of model-based and model-free dispatch strategies remains insufficiently benchmarked on full-year, real-world commercial datase...
Hafiz Majid Hussain, Wajiha Samar, L. Klein et al.· 0 citations
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