Huan Ma¹, Linlin Ma², Zengwei Wang^3,*, Zhendong Li³, Yuanzhen Zhu¹, Yutian Liu³

Energy Engineering, Vol.121, No.11, pp. 3133-3160, 2024, DOI:10.32604/ee.2024.055051 - 21 October 2024

Abstract With the increasing penetration of renewable energy in power system, renewable energy power ramp events (REPREs), dominated by wind power and photovoltaic power, pose significant threats to the secure and stable operation of power systems. This paper presents an early warning method for REPREs based on long short-term memory (LSTM) network and fuzzy logic. First, the warning levels of REPREs are defined by assessing the control costs of various power control measures. Then, the next 4-h power support capability of external grid is estimated by a tie line power prediction model, which is constructed based More > Graphic Abstract

Jiachang Liu^1,*, Zhengwei Huang², Junfeng Xiang¹, Lu Liu¹, Manlin Hu¹

Energy Engineering, Vol.121, No.11, pp. 3461-3486, 2024, DOI:10.32604/ee.2024.054514 - 21 October 2024

Abstract To enhance the refinement of load decomposition in power systems and fully leverage seasonal change information to further improve prediction performance, this paper proposes a seasonal short-term load combination prediction model based on modal decomposition and a feature-fusion multi-algorithm hybrid neural network model. Specifically, the characteristics of load components are analyzed for different seasons, and the corresponding models are established. First, the improved complete ensemble empirical modal decomposition with adaptive noise (ICEEMDAN) method is employed to decompose the system load for all four seasons, and the new sequence is obtained through reconstruction based on the… More >

Weigang Jin¹, Lei Chen^2,*, Shencong Zheng², Yuqi Jiang², Yifei Li², Hongkun Chen²

Energy Engineering, Vol.121, No.11, pp. 3161-3179, 2024, DOI:10.32604/ee.2024.054068 - 21 October 2024

Abstract Investigating flexibility and stability boosting transmission expansion planning (TEP) methods can increase the renewable energy (RE) consumption of the power systems. In this study, we propose a bi-level TEP method for voltage-source-converter-based direct current (VSC-DC), focusing on flexibility and stability enhancement. First, we established the TEP framework of VSC-DC, by introducing the evaluation indices to quantify the power system flexibility and stability. Subsequently, we propose a bi-level VSC-DC TEP model: the upper-level model acquires the optimal VSC-DC planning scheme by using the improved moth flame optimization (IMFO) algorithm, and the lower-level model evaluates the flexibility More >

Jingjing Bai¹, Yunpeng Cheng¹, Shenyun Yao^2,*, Fan Wu¹, Cheng Chen¹

Energy Engineering, Vol.121, No.11, pp. 3381-3400, 2024, DOI:10.32604/ee.2024.053683 - 21 October 2024

Abstract To mitigate the impact of wind power volatility on power system scheduling, this paper adopts the wind-storage combined unit to improve the dispatchability of wind energy. And a three-level optimal scheduling and power allocation strategy is proposed for the system containing the wind-storage combined unit. The strategy takes smoothing power output as the main objectives. The first level is the wind-storage joint scheduling, and the second and third levels carry out the unit combination optimization of thermal power and the power allocation of wind power cluster (WPC), respectively, according to the scheduling power of WPC and… More >

Caifeng Wen^1,2, Boxin Zhang^1,*, Yuanjun Dai³, Wenxin Wang⁴, Wanbing Xie¹, Qian Du¹

Energy Engineering, Vol.121, No.10, pp. 2961-2979, 2024, DOI:10.32604/ee.2024.041677 - 11 September 2024

Abstract Power quality improvements help guide and solve the problems of inefficient energy production and unstable power output in wind power systems. The purpose of this paper is mainly to explore the influence of different energy storage batteries on various power quality indicators by adding different energy storage devices to the simulated wind power system, and to explore the correlation between system entropy generation and various indicators, so as to provide a theoretical basis for directly improving power quality by reducing loss. A steady-state experiment was performed by replacing the wind wheel with an electric motor,… More >

He Wang, Xingyu Tong, Huanan Yu^*, Xiao Hu, Jing Bian

Energy Engineering, Vol.121, No.9, pp. 2525-2542, 2024, DOI:10.32604/ee.2024.050594 - 19 August 2024

Abstract Cyber-physical power system (CPPS) has significantly improved the operational efficiency of power systems. However, cross-space cascading failures may occur due to the coupling characteristics, which poses a great threat to the safety and reliability of CPPS, and there is an acute need to reduce the probability of these failures. Towards this end, this paper first proposes a cascading failure index to identify and quantify the importance of different information in the same class of communication services. On this basis, a joint improved risk-balanced service function chain routing strategy (SFC-RS) is proposed, which is modeled as More >

Zeyi Wang¹, Mingxi Jiao¹, Daliang Wang¹, Minxu Liu¹, Minglei Jiang², He Wang³, Shiqiang Li^3,*

Energy Engineering, Vol.121, No.8, pp. 2275-2291, 2024, DOI:10.32604/ee.2024.028223 - 19 July 2024

Abstract This paper addresses the problem of complex and challenging disturbance localization in the current power system operation environment by proposing a disturbance localization method for power systems based on group sparse representation and entropy weight method. Three different electrical quantities are selected as observations in the compressed sensing algorithm. The entropy weighting method is employed to calculate the weights of different observations based on their relative disturbance levels. Subsequently, by leveraging the topological information of the power system and pre-designing an overcomplete dictionary of disturbances based on the corresponding system parameter variations caused by disturbances,… More >

Ying Qu¹, Jinhao Wang¹, Xueting Cheng¹, Jie Hao¹, Weiru Wang¹, Zhewen Niu², Yuxiang Wu^2,*

Energy Engineering, Vol.121, No.7, pp. 1847-1863, 2024, DOI:10.32604/ee.2024.048300 - 11 June 2024

Abstract The data-driven transient stability assessment (TSA) of power systems can predict online real-time prediction by learning the temporal features before and after faults. However, the accuracy of the assessment is limited by the quality of the data and has weak transferability. Based on this, this paper proposes a method for TSA of power systems based on an improved extreme gradient boosting (XGBoost) model. Firstly, the gradient detection method is employed to remove noise interference while maintaining the original time series trend. On this basis, a focal loss function is introduced to guide the training of… More >

Yuping Bian^*, Xiu Wan, Xiaoyu Zhou

Energy Engineering, Vol.121, No.6, pp. 1637-1656, 2024, DOI:10.32604/ee.2024.047678 - 21 May 2024

Abstract To address uncertainty as well as transient stability constraints simultaneously in the preventive control of wind farm systems, a novel three-stage optimization strategy is established in this paper. In the first stage, the probabilistic multi-objective particle swarm optimization based on the point estimate method is employed to cope with the stochastic factors. The transient security region of the system is accurately ensured by the interior point method in the second stage. Finally, the verification of the final optimal objectives and satisfied constraints are enforced in the last stage. Furthermore, the proposed strategy is a general More >

Tao Bao^*, Xiyuan Ma, Zhuohuan Li, Duotong Yang, Pengyu Wang, Changcheng Zhou

Energy Engineering, Vol.121, No.6, pp. 1713-1737, 2024, DOI:10.32604/ee.2023.046150 - 21 May 2024

Abstract The stability problem of power grids has become increasingly serious in recent years as the size of novel power systems increases. In order to improve and ensure the stable operation of the novel power system, this study proposes an artificial emotional lazy Q-learning method, which combines artificial emotion, lazy learning, and reinforcement learning for static security and stability analysis of power systems. Moreover, this study compares the analysis results of the proposed method with those of the small disturbance method for a stand-alone power system and verifies that the proposed lazy Q-learning method is able More >