Bin Chen¹, Ziyang Li¹, Shipeng Li¹, Qingzhou Zhao¹, Xingdou Liu^2,*

Energy Engineering, Vol.121, No.5, pp. 1291-1307, 2024, DOI:10.32604/ee.2024.046374

Abstract To reduce carbon emissions, clean energy is being integrated into the power system. Wind power is connected to the grid in a distributed form, but its high variability poses a challenge to grid stability. This article combines wind turbine monitoring data with numerical weather prediction (NWP) data to create a suitable wind power prediction framework for distributed grids. First, high-precision NWP of the turbine range is achieved using weather research and forecasting models (WRF), and Kriging interpolation locates predicted meteorological data at the turbine site. Then, a preliminary predicted power series is obtained based on the fan’s wind speed-power conversion… More >

Zhongping Liu¹, Enhui Sun^2,*, Jiahao Shi², Lei Zhang², Qi Wang¹, Jiali Dong¹

Energy Engineering, Vol.121, No.4, pp. 913-932, 2024, DOI:10.32604/ee.2023.043973

Abstract There is a growing need to explore the potential of coal-fired power plants (CFPPs) to enhance the utilization rate of wind power (wind) and photovoltaic power (PV) in the green energy field. This study developed a load regulation model for a multi-power generation system comprising wind, PV, and coal energy storage using real-world data. The power supply process was divided into eight fundamental load regulation scenarios, elucidating the influence of each scenario on load regulation. Within the framework of the multi-power generation system with the wind (50 MW) and PV (50 MW) alongside a CFPP (330 MW), a lithium-iron phosphate… More > Graphic Abstract

Fan Xiao¹, Xiong Ping¹, Yeyang Li^2,*, Yusen Xu², Yiqun Kang¹, Dan Liu¹, Nianming Zhang¹

Energy Engineering, Vol.121, No.2, pp. 359-376, 2024, DOI:10.32604/ee.2023.040887

Abstract The fluctuation of wind power affects the operating safety and power consumption of the electric power grid and restricts the grid connection of wind power on a large scale. Therefore, wind power forecasting plays a key role in improving the safety and economic benefits of the power grid. This paper proposes a wind power predicting method based on a convolutional graph attention deep neural network with multi-wind farm data. Based on the graph attention network and attention mechanism, the method extracts spatial-temporal characteristics from the data of multiple wind farms. Then, combined with a deep neural network, a convolutional graph… More >

Baogang Chen¹, Fenglin Miao^2,*, Jing Yang¹, Chen Qi², Wenyan Ji¹

Energy Engineering, Vol.121, No.2, pp. 541-555, 2024, DOI:10.32604/ee.2023.028327

Abstract Energy storage systems (ESS) and permanent magnet synchronous generators (PMSG) are speculated to be able to exhibit frequency regulation capabilities by adding differential and proportional control loops with different control objectives. The available PMSG kinetic energy and charging/discharging capacities of the ESS were restricted. To improve the inertia response and frequency control capability, we propose a short-term frequency support strategy for the ESS and PMSG. To this end, the weights were embedded in the control loops to adjust the participation of the differential and proportional controls based on the system frequency excursion. The effectiveness of the proposed control strategy was… More >

Shumin Sun¹, Peng Yu¹, Jiawei Xing¹, Yan Cheng¹, Song Yang¹, Qian Ai^2,*

Energy Engineering, Vol.120, No.12, pp. 2761-2782, 2023, DOI:10.32604/ee.2023.042635

Abstract Wind power prediction is very important for the economic dispatching of power systems containing wind power. In this work, a novel short-term wind power prediction method based on improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) and (long short-term memory) LSTM neural network is proposed and studied. First, the original data is prepossessed including removing outliers and filling in the gaps. Then, the random forest algorithm is used to sort the importance of each meteorological factor and determine the input climate characteristics of the forecast model. In addition, this study conducts seasonal classification of the annual data where… More >

Yanshan Lu¹, Binbin He¹, Jun Jiang¹, Ruixiao Lin^2,*, Xinzhen Zhang², Zaimin Yang³, Zhi Rao³, Wenchuan Meng³, Siyang Sun³

Energy Engineering, Vol.120, No.12, pp. 2803-2818, 2023, DOI:10.32604/ee.2023.042328

Abstract To solve the problem of residual wind power in offshore wind farms, a hydrogen production system with a reasonable capacity was configured to enhance the local load of wind farms and promote the local consumption of residual wind power. By studying the mathematical model of wind power output and calculating surplus wind power, as well as considering the hydrogen production/storage characteristics of the electrolyzer and hydrogen storage tank, an innovative capacity optimization allocation model was established. The objective of the model was to achieve the lowest total net present value over the entire life cycle. The model took into account… More >

Tusongjiang Kari¹, Sun Guoliang², Lei Kesong¹, Ma Xiaojing^1,*, Wu Xian¹

Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 1437-1452, 2023, DOI:10.32604/iasc.2023.037012

Abstract Wind power volatility not only limits the large-scale grid connection but also poses many challenges to safe grid operation. Accurate wind power prediction can mitigate the adverse effects of wind power volatility on wind power grid connections. For the characteristics of wind power antecedent data and precedent data jointly to determine the prediction accuracy of the prediction model, the short-term prediction of wind power based on a combined neural network is proposed. First, the Bi-directional Long Short Term Memory (BiLSTM) network prediction model is constructed, and the bi-directional nature of the BiLSTM network is used to deeply mine the wind… More >

Enhui Sun^1,2, Jiahao Shi^1,2, Lei Zhang^1,2,*, Hongfu Ji^1,2, Qian Zhang^1,2, Yongyi Li^1,2

Energy Engineering, Vol.120, No.7, pp. 1583-1602, 2023, DOI:10.32604/ee.2023.027790

Abstract This paper studies the feasibility of a supply-side wind-coal integrated energy system. Based on grid-side data, the load regulation model of coal-fired power and the wind-coal integrated energy system model are established. According to the simulation results, the reasons why the wind-coal combined power supply is difficult to meet the grid-side demand are revealed through scenario analysis. Based on the wind-coal combined operation, a wind-coal-storage integrated energy system was proposed by adding lithium-iron phosphate battery energy storage system (LIPBESS) to adjust the load of the system. According to the four load adjustment scenarios of grid-side instructions of the wind-coal system,… More >

Zeyu Wu¹, Bo Sun^1,2, Qiang Feng^2,*, Zili Wang¹, Junlin Pan¹

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.1, pp. 527-554, 2023, DOI:10.32604/cmes.2023.027124

Abstract Due to the high inherent uncertainty of renewable energy, probabilistic day-ahead wind power forecasting is crucial for modeling and controlling the uncertainty of renewable energy smart grids in smart cities. However, the accuracy and reliability of high-resolution day-ahead wind power forecasting are constrained by unreliable local weather prediction and incomplete power generation data. This article proposes a physics-informed artificial intelligence (AI) surrogates method to augment the incomplete dataset and quantify its uncertainty to improve wind power forecasting performance. The incomplete dataset, built with numerical weather prediction data, historical wind power generation, and weather factors data, is augmented based on generative… More > Graphic Abstract

Weijun Li¹, Xin Die², Zhicheng Ma³, Jinping Zhang³, Haiying Dong^1,*

Energy Engineering, Vol.120, No.4, pp. 1001-1022, 2023, DOI:10.32604/ee.2023.024426

Abstract Aiming at the problems of large-scale wind and solar grid connection, how to ensure the economy of system operation and how to realize fair scheduling between new energy power stations, a two-stage optimal dispatching model of wind power-photovoltaic-solar thermal combined system considering economic optimality and fairness is proposed. Firstly, the first stage dispatching model takes the overall economy optimization of the system as the goal and the principle of maximizing the consumption of wind and solar output, obtains the optimal output value under the economic conditions of each new energy station, and then obtains the maximum consumption space of the… More > Graphic Abstract