When performing wind integration studies, synthetic wind power forecasts are key elements. Historically, data from operational forecasting systems have been used sparsely, likely due to the high costs involved. Purely statistical methods for simulati...
Very short-term forecasts of wind power provide electricity market participants with extremely valuable information, especially in power systems with high penetration of wind energy. In very short-term horizons, statistical methods based on historica...
Wind energy and wind power forecast errors have a direct impact on operational decision problems involved in the integration of this form of energy into the electricity system. As the relationship between wind and the generated power is highly nonlin...
Power generation forecasts for wind farms, especially with a short-term horizon, have been extensively researched due to the growing share of wind farms in total power generation. Detailed forecasts are necessary for the optimization of power systems...
Weather variables are an important driver of power generation from renewable energy sources. However, accurately predicting such variables is a challenging task, which has a significant impact on the accuracy of the power generation forecasts. In thi...
Accurate and efficient medium- and long-term forecasts of wind power can provide technical support for the efficient development and utilization of wind resources. Considering the regional characteristics of wind resources, the regional-similarity fa...
Climate change poses a significant threat to humanity. Achieving net-zero emissions is a key goal in many countries. Among various energy resources, solar power generation is one of the prominent renewable energy sources. Previous studies have demons...
The main objective of this study was to conduct multi-stage and multi-variant prognostic research to assess the impact of e-mobility development on the Polish power system for the period 2022–2027. The research steps were as follows: forecast t...
Accurate probabilistic forecasts of renewable generation are drivers for operational and management excellence in modern power systems and for the sustainable integration of green energy. The combination of forecasts provided by different individual...
Renewable energy sources are being expanded globally in response to global warming. Solar power generation is closely related to solar radiation and typically experiences significant fluctuations in solar radiation hours during periods of high solar...
Energy policies of the European Union, the United States, China, and many other countries are focused on the growth in the number of and output from renewable energy sources (RES). That is because RES has become increasingly more competitive when com...
Accurate day-ahead wind speed forecasting is essential for wind power forecasting and electricity market participation under increasing renewable energy penetration. This study proposes a hybrid forecasting framework that combines raw global forecast...
To realize the safety control of electric power systems under high penetration of photovoltaic power systems, accurate global horizontal irradiance (GHI) forecasts using numerical weather prediction models (NWP) are becoming increasingly important. T...
Power system stability (PSS) refers to the capacity of an electrical system to maintain a consistent equilibrium between the generation and consumption of electric power. In this paper, the PSS is evaluated for a “hybrid power plant” (HPP...
This study introduces a novel hybrid forecasting model for wind power generation. It integrates Artificial Neural Networks, data clustering, and Particle Swarm Optimization algorithms. The methodology employs a systematic framework: initial clusterin...
We introduce firm solar forecasts as a strategy to operate optimally overbuilt solar power plants in conjunction with optimally sized storage systems so as to make up for any power prediction errors, and hence entirely remove load balancing uncertain...
Photovoltaic (PV) power forecasts are typically evaluated using aggregate error metrics computed over an entire test period, which may conceal condition-dependent accuracy differences. We evaluate whether forecasting error varies systematically with...
Availability of effective estimation of the power profiles of photovoltaic systems is essential for studying how to increase the share of intermittent renewable sources in the electricity mix of many countries. For this purpose, weather forecasts, to...
Wind energy has increasingly played a vital role in mitigating conventional resource shortages. Nevertheless, the stochastic nature of wind poses a great challenge when attempting to find an accurate forecasting model for wind power. Therefore, preci...
High-quality short-term forecasts of electrical energy generation in solar power plants are crucial in the dynamically developing sector of renewable power generation. This article addresses the issue of selecting appropriate (preferred) methods for...
As the relative importance of renewable energy in electric power systems increases, the prediction of photovoltaic (PV) power generation has become a crucial technology, for improving stability in the operation of next-generation power systems, such...
Wind power forecasting techniques have received substantial attention recently due to the increasing penetration of wind energy in national power systems. While the initial focus has been on point forecasts, the need to quantify forecast uncertainty...
It is widely considered that solar energy will be one of the most competitive energy sources in the future, and solar energy currently accounts for high percentages of power generation in developed countries. However, its power generation capacity is...
The paper conducts a literature review of applications of autoregressive methods to short-term forecasting of power demand. This need is dictated by the advancement of modern forecasting methods and their achievement in good forecasting efficiency in...
The power-generation capacity of grid-connected photovoltaic (PV) power systems is increasing. As output power forecasting is required by electricity market participants and utility operators for the stable operation of power systems, several methods...
The prediction of wind power output is part of the basic work of power grid dispatching and energy distribution. At present, the output power prediction is mainly obtained by fitting and regressing the historical data. The medium- and long-term power...
Solar energy penetration has been on the rise worldwide during the past decade, attracting a growing interest in solar power forecasting over short time horizons. The increasing integration of these resources without accurate power forecasts hinders...
The fast growth of photovoltaic (PV) power generation requires dependable forecasting methods to support efficient integration of solar energy into power systems. This study conducts an up-to-date, systematized analysis of different models and method...
The accuracy of wind power forecasting depends a great deal on the data quality, which is so susceptible to cybersecurity attacks. In this paper, we study the cybersecurity issue of short-term wind power forecasting. We present one class of data atta...
Studies have demonstrated that changes in the climate affect wind power forecasting under different weather conditions. Theoretically, accurate prediction of both wind power output and weather changes using statistics-based prediction models is diffi...
Solar power has rapidly become an increasingly important energy source in many countries over recent years; however, the intermittent nature of photovoltaic (PV) power generation has a significant impact on existing power systems. To reduce this unce...
This review examines advancements and methodologies in long-term wind-speed and -power forecasting. It emphasizes the importance of these techniques in integrating wind energy into power systems. Covering a range of forecasting timeframes from monthl...
Forecast errors in significant wave height and dominant wave period can propagate differently to wave energy converter (WEC) power, depending on error direction and the device response. Hourly records from NDBC Station 46014 (2019–2020) were us...
In recent years, wind energy has become a competitively priced source of energy around the world, which has created increasing challenges for system operators. Accurate wind power generation forecasting plays an important role in power systems to imp...
The integration of wind energy into power systems has intensified as a result of the urgency for global energy transition. This requires more accurate forecasting techniques that can capture the variability of the wind resource to achieve better oper...
Local power changes, weak-output states, and changing interval coverage complicate ultra-short-term wind power forecasting. This study develops power-increment enhancement and signed adaptive conformal inference (PIE-SACI) to address these challenges...
Analysis of urban saturated power loads is helpful to coordinate urban power grid construction and economic social development. There are two different kinds of forecasting models: the logistic curve model focuses on the growth law of the data itself...
As the penetration rate of photovoltaic power generation continues to increase within new power systems, accurately forecasting regional PV power output has become critical to ensuring the safe and stable operation of power grids. Photovoltaic power...
Wind power forecasting is critical to renewable energy generation, as accurate predictions are essential for the efficient and reliable operation of power systems. However, wind power output is inherently unstable and is strongly affected by meteorol...
The volatility and intermittency of wind energy result in highly unpredictable wind power output, which poses challenges to the stability of the intact power system when integrating large-scale wind power. The accuracy of wind power prediction is cri...
A benchmarking exercise was organized within the framework of the European Action Weather Intelligence for Renewable Energies (“WIRE”) with the purpose of evaluating the performance of state of the art models for short-term renewable energy forecasti...
Accurate forecasting of photovoltaic (PV) power is essential for grid scheduling and energy management. In recent years, deep learning technology has made significant progress in time-series forecasting, offering new solutions for PV power forecastin...
The number of wind-generating resources has increased considerably, owing to concerns over the environmental impact of fossil-fuel combustion. Therefore, wind power forecasting is becoming an important issue for large-scale wind power grid integratio...
Accurately predicting wind power is crucial for the large-scale grid-connected of wind power and the increase of wind power absorption proportion. To improve the forecasting accuracy of wind power, a hybrid forecasting model using data preprocessing...
The forecasting of electricity demands is important for planning for power generator sector improvement and preparing for periodical operations. The prediction of future electricity demand is a challenging task due to the complexity of the available...
Existing works in photovoltaic (PV) power generation focus on accurately predicting the PV power output on a forecast horizon. As the solar power generation is heavily influenced by meteorological conditions such as solar radiation, the weather forec...
An accurate forecast of the power generated by a wind turbine is of paramount importance for its optimal exploitation. Several forecasting methods have been proposed either based on a physical modeling or using a statistical approach. All of them rel...
The purpose of this study is to design a novel custom power demand forecasting algorithm based on the LSTM Deep-Learning method regarding the recent power demand patterns. We performed tests to verify the error rates of the forecasting module, and to...
The need to turn to more environmentally friendly sources of energy has led energy systems to focus on renewable sources of energy. Wind power has been a widely used source of green energy. However, the wind’s stochastic and unpredictable behav...
To address the nonlinear amplification of numerical weather prediction (NWP) errors and the difficult trade-off between coverage and sharpness in short-term offshore wind power forecasting, this paper proposes PRWind, a physics-guided framework for s...
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