Journal Article10.1016/j.compeleceng.2023.108769
Gray wolf optimization-based wind power load mid-long term forecasting algorithm
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TL;DR: In this paper , a wind power mid-long-term load forecasting method considering different wind energy characteristics for effective future climate information prediction is proposed, and an adaptive prediction model is constructed based on the Gray wolf optimization algorithm (GWO) and the long short-term memory network (LSTM).
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About: This article is published in Computers & Electrical Engineering. The article was published on 01 Aug 2023. The article focuses on the topics: Computer science & Adaptability.
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References
Improved Deep Mixture Density Network for Regional Wind Power Probabilistic Forecasting
TL;DR: An Improved Deep Mixture Density Network is proposed for short-term WPPF of multiple wind farms and the entire region and a laconic and accurate probabilistic expression of predicted power at each time step is produced by the proposed model.
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An Intelligent Dynamic Security Assessment Framework for Power Systems With Wind Power
TL;DR: An intelligent framework for real-time DSA of power systems with large penetration of wind power with high DSA efficiency and accuracy can be an ideal candidate for advanced security monitoring in the future SmartGrid control centres.
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A Wind Speed Correction Method Based on Modified Hidden Markov Model for Enhancing Wind Power Forecast
TL;DR: In this article , a novel hidden Markov model (HMM) is developed to explore both the temporal autocorrelation of WSF error and the nonlinear correlation between the WSF result and the error.
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Temporal-Spatial Quantum Graph Convolutional Neural Network Based on Schrödinger Approach for Traffic Congestion Prediction
Zhiguo Qu,Xinzhuo Liu,Min Zheng +2 more
TL;DR: In this paper , a new quantum algorithm that can capture temporal and spatial features of traffic data simultaneously for traffic congestion prediction is presented, which is called temporal-spatial quantum graph convolutional neural network (QGCNN).
87
Energy Storage in Microgrids: Compensating for Generation and Demand Fluctuations While Providing Ancillary Services
Mostafa Farrokhabadi,Bharatkumar V. Solanki,Claudio A. Canizares,Kankar Bhattacharya,Sebastian Koenig,Patrick S. Sauter,Thomas Leibfried,Sören Hohmann +7 more
TL;DR: In this article, a large number of wind turbines and photovoltaic (PV) panels are connected to medium- (1-69 kV) and low-voltage (1kV) grids, with traditional integrated bulk power systems becoming decentralized in the presence of active distribution networks.
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