相关论文: Day-Ahead PV Power Forecasting Based on MSTL-TFT

Short term load forecasts will play a key role in the implementation of smart electricity grids. They are required to optimise a wide range of potential network solutions on the low voltage (LV) grid, including integrating low carbon…

This paper presents a classical estimation problem for calculating the energy generated by photovoltaic solar energy systems in the Netherlands, on a daily, annual and regional basis. We identify two data sources to construct our…

Accurate intraday forecasts of the power output by PhotoVoltaic (PV) systems are critical to improve the operation of energy distribution grids. We describe a neural autoregressive model that aims to perform such intraday forecasts. We…

Accurate prediction of non-dispatchable renewable energy sources is essential for grid stability and price prediction. Regional power supply forecasts are usually indirect through a bottom-up approach of plant-level forecasts, incorporate…

The paper proposes an optimal management strategy for a system composed by a battery and a photovoltaic power plant. This integrated system is called to deliver the photovoltaic power and to simultaneously provide droop-based primary…

Rooftop solar photovoltaic (PV) power generator is a widely used distributed energy resource (DER) in distribution systems. Currently, the majority of PVs are installed behind-the-meter (BTM), where only customers' net demand is recorded by…

Distributed solar photovoltaic (PV) systems are projected to be a key contributor to future energy landscape, but are often poorly represented in energy models due to their distributed nature. They have higher costs compared to utility PV,…

We provide a methodology for estimating the losses due to soiling for photovoltaic (PV) systems. We focus this work on estimating the losses from historical power production data that are unlabeled, i.e. power measurements with time stamps,…

Predicting the short-term power output of a photovoltaic panel is an important task for the efficient management of smart grids. Short-term forecasting at the minute scale, also known as nowcasting, can benefit from sky images captured by…

Electricity price forecasting (EPF) is essential for energy markets stakeholders (e.g. grid operators, energy traders, policymakers) but remains challenging due to the inherent volatility and nonlinearity of price signals. Traditional…

Distributed Generation (DG) is an effective way of integrating renewable energy sources to conventional power grid, which improves the reliability and efficiency of power systems. Photovoltaic (PV) systems are ideal DGs thanks to their…

Effective utilization of photovoltaic (PV) plants requires weather variability robust global solar radiation (GSR) forecasting models. Random weather turbulence phenomena coupled with assumptions of clear sky model as suggested by Hottel…

The inherent intermittency and high-frequency variability of solar irradiance, particularly during rapid cloud advection, present significant stability challenges to high-penetration photovoltaic grids. Although multimodal forecasting has…

The residential electrical energy scheduling of solar Photovoltaics (PV) is an important research area of the modern green buildings. On the demand side, factors such as building load, and the renewable PV energy resources are integrated…

The decomposition of time series into components is an important task that helps to understand time series and can enable better forecasting. Nowadays, with high sampling rates leading to high-frequency data (such as daily, hourly, or…

Solar power harbors immense potential in mitigating climate change by substantially reducing CO$_{2}$ emissions. Nonetheless, the inherent variability of solar irradiance poses a significant challenge for seamlessly integrating solar power…

The variability of the solar resource is mainly caused by cloud passing, causing rapid power fluctuations on the output of photovoltaic (PV) systems. The fluctuations can negatively impact the electric grid, and smoothing techniques can be…

Ensuring grid stability in the transition to renewable energy sources requires accurate power demand forecasting. This study addresses the need for precise forecasting by differentiating among industrial, commercial, and residential…

In PV-rich power distribution systems, over-voltage issues are often addressed by curtailing excess generation from PV plants (in addition to reactive power control), raising fairness concerns. Existing fairness-aware control schemes tackle…

The increasing installation of Photovoltaics (PV) cells leads to more generation of renewable energy sources (RES), but results in increased uncertainties of energy scheduling. Predicting PV power generation is important for energy…