How do meteorological features affect wind and solar power output?
Spearman’s rank correlation, mutual information entropy, and Pearson correlation are employed to investigate the relationship between meteorological features and power output. Through evidence theory, meteorological features with a cumulative contribution exceeding 85% are selected as inputs for the wind and solar power forecasting model.
Why is accurate solar and wind generation forecasting important?
Accurate solar and wind generation forecasting along with high renewable energy penetration in power grids throughout the world are crucial to the days-ahead power scheduling of energy systems. It is difficult to precisely forecast on-site power generation due to the intermittency and fluctuation characteristics of solar and wind energy.
Can on-site solar and wind generation data be used for forecasting?
Solar and wind generation data from on-site sources are beneficial for the development of data-driven forecasting models. In this paper, an open dataset consisting of data collected from on-site renewable energy stations, including six wind farms and eight solar stations in China, is provided.
How is evidence theory used in wind and solar power forecasting?
Through evidence theory, meteorological features with a cumulative contribution exceeding 85% are selected as inputs for the wind and solar power forecasting model. The TCN-ATT-LSTM network is pre-trained to extract common knowledge, and transfer learning is applied to fine-tune (FT) the model through network parameter adjustments.
Where are solar power generation data stored?
Solar power generation data are in the solar_stations folder, which includes eight Excel files. The weather condition data and real-time power generation data were recorded in these files. The power generation and PV panel information of each solar station are listed in Table 4.
Can a transfer learning-based forecasting approach be used for wind and solar power?
Multiple requests from the same IP address are counted as one view. To address the issue of declining prediction accuracy caused by the lack of data in newly constructed wind and solar power stations, this paper introduces a transfer learning-based forecasting approach for wind and photovoltaic power.
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Modeling and sizing optimization of hybrid photovoltaic/wind power ...
The rapid industrialization and growth of world''s human population have resulted in the unprecedented increase in the demand for energy and in particular electricity. Depletion of fossil fuels and impacts of global warming caused widespread attention using renewable energy sources, especially wind and solar energies. Energy security under varying weather conditions …
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Optimal sizing of a wind/solar/battery/diesel hybrid microgrid based on typical scenarios considering meteorological variability ... It is, thus, important to determine the appropriate sizes of PV, WT, diesel generator, and associated energy storage system (ESS) for efficient, economic, and reliable operation of electric power system in ...
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In the 21st century, wind and solar power have rapidly increase worldwide, as efforts are made to reduce the use of fossil energy, such as coal, oil, and natural gas, and mitigate carbon emissions [1], [2] and corresponding pollution problems [3] the next few decades, the installed wind and photovoltaic (PV) capacity is expected to grow substantially, while the …
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On April 21, 2025, the Global Energy Internet Development Cooperation Organization and the National Climate Center jointly released the 2025 Global New Energy …
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Measurement(s) renewable energy generation Technology Type(s) supervisory control and data acquisition system Sample Characteristic - Location China
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Persistent and significant curtailment has cast concern over the prospects of wind power in China. A comprehensive assessment of the production of energy from wind has identified grid-integrated ...
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The system can also make full use of new energy sources, such as wind power, PV energy, and other forms of energy, thereby reducing the environmental pollution caused by the coal chemical industry and minimizing the industry''s ecological impact. In addition, hydrogen energy storage can also be applied to the new energy automotive industry.
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The expansion of renewable energies is at a high priority in policy strategies for energy transition and climate change mitigation at national and international levels [5].There is therefore a great need for improved siting schemes for renewable energy systems, as has been reported for wind turbine siting in Germany [6] would be even more desirable and also much …
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LPSP is the probability that an insufficient power supply results when the hybrid system (PV, wind power and energy storage) is not able to satisfy the load demand. The LPSP is considered to be the implemented criteria for a hybrid PV–wind system employing a battery bank. ... (TMY) provides a standard for hourly data for solar radiation and ...
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Here, we present a database of time series of wind and solar power generation, hydropower inflow, heating demand, and cooling demand developed using an internally consistent modeling framework...
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Compared to the traditional LSTM that ignores the inverse-time correlation between power and meteorological features and is sensitive to the model hyper-parameters, a power prediction model based on PSO-BiLSTM is developed. ... for wind and PV power are imperative for integrating large-scale RESs into the power grid and effectively managing ...
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This paper studies the regional complementarity of offshore wind power (OWP) and inland solar PV technologies to satisfy the corresponding regional electric demand from 2016 to 2020. ... Meteorological modeling has become a useful tool for studying renewable energy generation, as it provides information on the main physical variables that ...
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The outcomes of this research have been applied in the formulation of the "14th Five-Year Plan" energy storage development plan and the medium- to long-term energy storage development strategy of the State Grid Corporation of China …
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We optimize the location, capacity, and construction period of PV and wind power plants built at the utility scale (> 10 megawatt (MW)) for 2021–2070 to minimize LCOE in the …
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Virtual power plants (VPPs) have emerged as an innovative solution for modern power systems, particularly for integrating renewable energy sources. This study proposes a novel prediction approach combining improved K-means clustering with Time Convolutional Networks (TCNs), a Bi-directional Gated Recurrent Unit (BiGRU), and an attention mechanism …
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The uncontrollable photovoltaic (PV) and wind power leads to increasing demands on the grid regulation capacity, and can even lead to security and stability issues with the rapid growth of installed renewable energy sources. ... Considering future energy tariffs and meteorological conditions, this real-time predictive control strategy resulted ...
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Ma et al. [13] introduced the pumped storage power station as the energy storage system and the new energy system to form the wind/photovoltaic/ pumped storage combined power generation system ...
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Application of superconducting magnetic energy storage system- SMES wind power system of network forming. Proc CSEE, 21 (12) (2001), pp. 63-66 [in Chinese] Google Scholar [3] ... An optimal coordination control of Hybrid Wind/Photovoltaic/Energy Storage System. China Acad J Electron Publ House, 36 (14) (2012), pp. 96-100 [in Chinese] Google ...
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The PV + energy storage system with a capacity of 50 MW represents a certain typicality in terms of scale, which is neither too small to show the characteristics of the system nor too large to simulate and manage. This study builds a 50 MW "PV + energy storage" power generation system based on PVsyst software.
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Micro-meteorology plays a crucial role in the collection and storage processes of various energy sources such as wind power, photovoltaic power, hydropower, and thermal power . Monitoring meteorological changes …
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Activities related to energy production and consumption are the most significant contributors to CO 2 emissions. In pursuit of the ambitious goals of carbon peak and carbon neutrality, and with an emphasis on ensuring the sustainable development of resources and the environment, the Chinese government has devised a series of top-down policies aimed at …
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A statistical approach for hybrid energy storage system sizing based on capacity distributions in an autonomous PV/Wind power generation system. ... it is necessary to integrate energy storage batteries. Due to fluctuations of meteorological data (wind speed, temperature, irradiance), these storage batteries are obviously susceptible to ...
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The reliability and efficiency enhancement of energy storage (ES) technologies, together with their cost are leading to their increasing participation in the electrical power system [1].Particularly, ES systems are now being considered to perform new functionalities [2] such as power quality improvement, energy management and protection [3], permitting a better …
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Hybrid PV–Wind systems (Fig. 1) offer the most adequate solutions for the electrification of remote areas; the combination and the ratio of the two types of energy depending greatly on the resources locally available in each geographical area.These resources can be evaluated only after a period typically one year of monitoring of the basic parameters (wind …
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Sustainable energy management hinges on precise forecasting of renewable energy sources, with a specific focus on solar power. To enhance resource allocation and grid …
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As photovoltaic solar energy depends on meteorological variables such as irradiance, air temperature and wind speed, they are used in artificial intelligence mo
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Forecasting of large-scale renewable energy clusters composed of wind power generation, photovoltaic and concentrating solar power (CSP) generation encounters complex uncertainties due to spatial scale dispersion and time scale random fluctuation. In response to this, a short-term forecasting method is proposed to improve the hybrid forecasting accuracy of …
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To combat the worsening global energy shortage, global photovoltaic (PV) installation capacity has been increasing rapidly every year. Since the instability and intermittence of PV power output have great impacts on utility grids, accurate PV power output prediction is crucial. This paper proposes the use of machine learning approaches, combined with a …
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Second, we optimize the spatiotemporal distributions of PV and wind-power plants, energy storage, and power transmission based on the hourly variations of solar radiation, wind speed, temperature ...
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In this research, the multi-step ahead PV power forecasting (PVPF) problem is dealt with for predicting the next day''s hourly power generation, which have different applications, such as making an energy storage policy and deciding the system marginal price by comparing the energy forecasts with the next day''s energy consumption.
Learn More →Experimental investigation of a 10 kW photovoltaic power …
Currently, several photovoltaic-wind power systems coupled with hydrogen energy storage projects are under construction or in trial operation worldwide [[16], [17], [18]].As shown in Table 1, it is a comparative analysis between this paper and related works.With the rapid growth of new energy installations and power generation under China''s Carbon Peaking and Carbon …
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