Jie Yan

North China Electric Power University | NCEPU · School of Renewable Energy

Relevance vector machine, a sparse probabilistic learning machine based on the kernel function, has excellent ability of prediction and generalization. It is proposed by this paper that the optimized relevance vector machine (ORVM) is a wind power interval forecasting model which is able to provide a certain prediction value and its possible fluctu...

The intermittency of wind generation creates nonlinear uncertainties in wind power forecasting (WPF). Thus, additional operating costs can be incurred for balancing these forecasting deviations. Normally, large wind power penetration requires accurate quantification of the uncertainty-induced costs. This paper defines this type of costs as wind pow...

Battery swapping station (BSS) is a new mode of supplying power to electric vehicles (EVs). As distributed and flexible energy storage as well as demand response (DR) sources, BSSs have great potentials to tackle both high penetration of variable renewable energy (VRE) sources and real-time EV charging. However, these potentials have not been fully...

Highly wind penetrated future power system will couple to the variabilities and nonlinear correlations of wind. Reliable wind power forecasting (WPF) for a region is critical to the security and economics of the power system operation. Therefore, this paper proposes a multi-scale WPF method by establishing a multi-to-multi (m2m) mapping network and...

Utilizing renewable energy for hydrogen production and blending it into natural gas networks is recognized as a promising approach to promote a low-carbon transformation of power systems and enhance the integration of renewable energy sources. However, the temporal and geographical availability of renewable energy and natural gas operation conditio...

The threat of long‐term low wind output processes (LWOP) on the supply ability of the power system is escalating with the increasing integration of wind power. Accurate prediction of LWOP is crucial for maintaining the stable operation of the power system. However, the occurrence probability of LWOP is low and the available samples are lacking, lim...

As the proportion of installed photovoltaic power generation continues to increase, low output under the influence of large-scale weather systems has an increasingly significant influence on the power grid. There is an urgent need to improve photovoltaic power generation forecasting accuracy and reduce the risk of insufficient output in forecast re...

The deployment of energy storage on the supply side effectively addresses the challenge posed by the intermittency and fluctuation of renewable energy. Optimizing capacity configuration is vital for maximizing the efficiency of wind/photovoltaic/storage hybrid power generation systems. Firstly, a deep learning-based Wasserstein GAN-gradient penalty...

Ultra-short-term wind power forecasting plays a vital role in real-time scheduling, frequency regulation, and intraday market transactions. Due to the complexity of weather systems, unit aging, wind farm control strategies, etc., the temporal dependency relationship in wind power series changes from time to time (known as concept drift), which lead...

Carbon neutrality has become the global consensus, and wind power is one of the key technologies to achieve carbon neutrality in the power system. However, the randomness and fluctuation of wind energy pose a great challenge to the safe and stable operation of the power system. Accurate wind power prediction results can effectively reduce the adver...

In recent years, the development and utilization of China’s wind energy resources have been greatly developed, but the large-scale wind power grid connection has brought threats to the safe and stable operation of the power grid. In order to ensure the stability of the power grid, it is necessary to reduce wind power output fluctuation and improve...

The dynamic charging behavior of electric vehicles (EVs) is causing frequent line-overloading problems and serious power security issues. Controlled and smart charging mechanisms for EVs incorporating demand response (DR) may provide significant operational flexibility to the grid operators and reduce charging costs for EV users. However, controlli...

Affected by the shortage of water resources and land degradation, the sustainable development of agriculture in more and more arid areas will face serious obstacles. The combinations of agricultural photovoltaic, water transportation and irrigation systems are considered as a potential choice to solve above problem. This study aims to investigate t...

The issue of renewable energy curtailment poses a crucial challenge to its effective utilization. To address this challenge, mitigating the impact of the intermittency and volatility of wind and solar energy is essential. In this context, this paper employs scenario analysis to examine the complementary features of wind and solar hybrid systems. Fi...

Large scale random and intermittent wind power integration will significantly increase the additional operation cost of power system, and the variation characteristics are complex and difficult to accurately quantify. Different from the existing work, this paper first proposes a double-layer clustering method for wind power fluctuation scenarios. S...

Building a new power system with renewable energy as the main body is the only way to solve the problem of global climate change and achieve the dual carbon goal. However, the increasing penetration rate of renewable energy and large-scale electric vehicles have brought great challenges to the safe and reliable operation of traditional power system...

In the process of wind power generation, the random fluctuation of wind speed affects the smooth operation of the wind turbine and the stability of the output power of the wind turbine. Aiming at the influence of wind speed random fluctuation on the stable operation of wind turbines, this paper regards wind speed random fluctuation as bounded distu...

This paper focuses on how to identify normal, derated power and abnormal data in operation data, which is key to intelligent operation and maintenance applications such as wind turbine condition diagnosis and performance evaluation. Existing identification methods can distinguish normal data from the original data, but usually remove power curtailm...

In this fourth part, guidance for the selection, deployment and mainte-nance of meteorological sensors, power measurements and associated data quality control relevant to real-time forecasting is provided. The full version is available online as OpenAccess here: https://www.sciencedirect.com/book/9780443186813/iea-wind-recommended-practice-for-...

Traditional assessment indexes could not fully describe offshore wind resource for the meteorological properties of offshore are more complex than onshore. And as a result, the uncertainty of offshore wind power projects would be increased and final economic benefits would be affected. Therefore, a study on offshore wind resource assessment is carr...

Wind power forecasting has supported operational decision-making for power system and electricity markets for 30 years. Efforts of improving the accuracy and/or certainty of deterministic or probabilistic wind power forecasts are continuously exerted by academics and industries. Forecast errors and associated uncertainties propagating through the w...

The idea behind this chapter is to provide teachers and students with material that can be used while studying renewable energy sources with special attention paid to their complementary characteristics. The questions and exercises included below refer to chapters presented in the book. In case of any questions, we provide the readers with contact...

The actuator disc model (ADM) incorporated into the k-ε turbulence model of EI Kasmi is able to simulate the wind farm wakes with high fidelity, which is essential for layout optimization and the evaluation of power production in modern wind farms. However, the effects of the parameter C4ε in the k-ε model of EI Kasmi on turbulent kinetic energy (T...

Numerical Weather Prediction (NWP) is a necessary input for short-term wind power forecasting. Existing NWP models are all based on purely physical models. This requires mainframe computers to perform large-scale numerical calculations and the technical threshold of the assimilation process is high. There is a need to further improve the timeliness...

The wind farm flow (WFF) models, which are enabled to predict the power output of downstream, located turbines within a wind farm. A WFF model consists of two main model components: a single wake model and a superposition model. Two WFF models, the Root Sum Square (RSS) superposition model incorporated into the single wake models (e.g. Bastankah an...

The simulation of wind power time series is a key process in renewable power allocation planning, operation mode calculation, and safety assessment. Traditional single-point modeling methods discretely generate wind power at each moment; however, they ignore the daily output characteristics and are unable to consider both modeling accuracy and effi...

Wind power, solar power, and electrical load forecasting are essential works to ensure the safe and stable operation of the electric power system. With the increasing permeability of new energy and the rising demand response load, the uncertainty on the production and load sides are both increased, bringing new challenges to the forecasting work an...

The wake model for stand-alone turbine is an essential ingredient of wind farm wake research, which is of great concern for optimization of wind turbine layout, power generation simulation, and operation control on a wind farm. One-dimensional wake models (e.g., Jensen model and Frandsen model) based on single conservation theorem were approximatel...

Wind turbine power curve is an indicator of wind turbine performance and important input of wind farm design or power prediction, therefore can serve the system planning and operation. However, a good power curve model is difficult to obtain because of the uncertain relationship between wind speed and its power output. Existing works focus on a det...

Abstract Accessibility estimation is significant to the offshore wind farm operation and maintenance (O&M) due to the extremely limited weather window and its sensitive effects on O&M tasks. Wave forecasting can be one solution to help maintenance decision‐making. However, the uncertain and dynamic properties of wave forecasts are seldom considered...

The temporal dependencies of wind power are significant to be involved in the modeling of short-term wind power forecasts. However, different time series inputs will contribute differently to the forecasting performance and bring in challenges to the selection of the relevant driving information. In this paper, a Multi-Source and Temporal Attention...

Distributed energy systems (DES) with hybrid sources has become a more effective way to increase the flexibility of energy supply. Current relevant research on the design optimization of DES strives to improve the efficiency and sustainability of energy systems through independent application of subsystem interconnection and demand response. This p...

Accurate medium- and long-term power consumption forecast is the premise and foundation of secure scheduling and layout planning of power system, which are conducive to the coordinated development of various power generation channels so that renewable energy generation can be improved. In view of this problem, this paper analyzes power consumption...

Wind speed spatial variation in the whole wind wheel rotation plane caused by wind shear and tower shadow effect becomes more obvious with the increase of rotor diameter and tower height, thus the hub height wind speed is not sufficient to represent the actual wind speed effect and the rotor equivalent wind speed should be used. However, the existi...

随着风光场站集群化发展，大规模的风光电力接入电力系统会威胁电力系统的安全稳定运行。精准的风光功率预测能有效缓解这一问题，但是现有的风光功率预测方法多集中在场站级别，区域总出力对电力系统制定调度计划、安排旋转备用容量具有重要的意义。为此，提出了基于堆叠降噪自编码器的风光功率预测模型实现场站 区域风光功率预测。以分布在我国某省的风光场群的运行数据为例，验证所提模型的有效性。结果表明：与场站原有预测系统精度相比，平坦地形风电场功率预测精度平均提高了15.56%，光伏场站功率预测精度平均提高了21.75%；复杂地形风电场功率预测精度平均提高了3.28%。

通过识别不同风电机组的相似性将风电场内各机组区分为不同的机组群，对每组机群分别建立功率预测模型，既提高了计算效率，又改善了大型风电场短期功率预测精度，较好解决了风电波动性和间歇性对电力系统安全运行的影响。提出了一种基于戴维森堡丁指数与聚类算法的风电场机组分组功率预测方法，以实际测量风速，测量功率以及两者的组合作为机组分组模型输入，分析其对聚类精度的影响程度。首 先，采用经验模态分解方法将风电功率序列分解后，将与原信号具有高相关性的固有模态函数 （ｉｎｔｒｉｎｓｉｃｍｏｄｅｆｕｎｃｔｉｏｎ，ＩＭＦ）分量重构，作为 Ｋ－ｍｅａｎｓ聚类算法的输入重新进行场内机组分组。然后，对每组机群分别构建经验模态分解相关向量机 （ｅｍｐｉｒｉｃａｌｍｏｄｅｄｅｃｏｍｐｏｓｉｔｉｏｎ－ｒｅｌｅｖａｎｃｅｖｅｃｔｏ...

With the continuous development of offshore wind power and clean oil fields, the introduction of wind power into the offshore oil and gas field energy system has attracted much more attention. As an oil and gas production platform with both production capacity and energy consumption, on the premise of ensuring stable production, the adoption of an...

To achieve a high penetration of renewable energy, wind power development in China has gradually moved to diverse manifestation (e.g., centralized onshore, low wind speed, and offshore wind power). However, preexisting studies regarding wind power cost neglect to consider the respective characteristics of different development scenarios. In this pa...

Understanding ageing transition caused fine-grained changes of electricity profile is the significant insight for coping with future threatens in grid flexibility management. The research gaps for the hourly-basis knowledge exist due to challenges in microanalysis on user-side behavior. Based on billions of users’ behavior data, we investigated the...

The shared mobility, as an emerging shared economy business mode, has been changing the travelling style of Chinese citizens. This study draws the annual data in year 2018 from DiDi Chuxing, as well as other survey and statistical data, to evaluate the shared mobility influence on energy consumption, emission and transportation structure, in the co...

Accurate real -time prediction of second -level wind speed can improve the operating conditions and control quality of wind turbines and provide auxiliary information for the power grid to make optimal dispatch decisions. At present， the time resolution of real -time wind speed prediction is usually on the minute level， and the model's generalizati...

Travel pattern of an electric vehicle (EV) user and the accuracy of their probability distribution models are the key factors affecting the simulation and prediction of EV charging load. Most of the existing works utilized the travel data for all kinds of populations and ignored the influence of people social attributes on their travel pattern, whi...

The traditional ultra-short-term wind speed prediction often utilizes the wind speed signals at a single location within the wind farm, ignoring the correlation of the wind speed among wind turbines. It is difficult to consider the spatial distribution characteristics of the wind speed under the influence of terrain and wake, thus affecting the imp...

The accurate description of the complementarity of wind and solar power is of great significance for guiding the planning and the safe and stable operation of the combined wind-solar power system. However, the internal continuity of the output series is disrupted when correlation coefficients are applied, and the difference among the volatility of...

With the rapid development of electric vehicles (EVs), EV charging load simulation is of significance to tackle the challenges for planning and operating a highly-penetrated power system. However, the lack of historical charging data, as well as consideration on the temperature and traffic, pose obstacles to establish an accurate model. This paper...

Distributed energy systems (DESs) are considered to be the future of energy systems because of their inherent high efficiency, cost-effectiveness, energy-saving capability, and environmentally friendly characteristics. Although there are many reports on the design optimization of DESs, few of them focus on the classification and siting optimization...