Accurate solar PV power prediction interval method based on frequency-domain decomposition and LSTM model

L Wang, M Mao, J **e, Z Liao, H Zhang, H Li - Energy, 2023 - Elsevier
The stability operation and real-time control of the integrated energy system with distributed
energy resources determines the higher and higher requirements for the accuracy of solar …

Fractional multivariate grey Bernoulli model combined with improved grey wolf algorithm: Application in short-term power load forecasting

C Yin, S Mao - Energy, 2023 - Elsevier
The accurate prediction of power load is helpful to make reasonable power generation plans
and scientific dispatching schemes and achieve the goal of energy saving and emission …

基于人工智能技术的新型电力系统负荷预测研究综述

**富佳, 王晓辉, 乔骥, 史梦洁, 蒲天骄 - **电机工程学报, 2023 - epjournal.csee.org.cn
在“双碳” 目标的驱动下, 构建以新能源为主体的新型电力系统是促进现代电力系统低碳转型发展
的重要前提与必然趋势. 由于复杂易变的多元负荷是新型电力系统的重要组成部分 …

[HTML][HTML] Probabilistic forecasting method for mid-term hourly load time series based on an improved temporal fusion transformer model

D Li, Y Tan, Y Zhang, S Miao, S He - … Journal of Electrical Power & Energy …, 2023 - Elsevier
The growth of distributed renewable energy and demand-side responsiveness has
increased the difficulty of mid-term hourly load time-series forecasting. This study presents a …

[HTML][HTML] Short-term electric net load forecasting for solar-integrated distribution systems based on Bayesian neural networks and statistical post-processing

G Tziolis, C Spanias, M Theodoride, S Theocharides… - Energy, 2023 - Elsevier
The increasing integration of variable renewable technologies at distribution feeders, mainly
solar photovoltaic (PV) systems, presents new challenges to grid operators for accurately …

Decomposition strategy and attention-based long short-term memory network for multi-step ultra-short-term agricultural power load forecasting

F Yang, X Fu, Q Yang, Z Chu - Expert Systems with Applications, 2024 - Elsevier
Accurate forecasting of the agricultural power load is important for rural electricity networks'
safe and stable operation. But it is more uncertain and difficult to forecast than industrial …

Combined electricity load-forecasting system based on weighted fuzzy time series and deep neural networks

Z Cao, J Wang, Y **a - Engineering Applications of Artificial Intelligence, 2024 - Elsevier
With continuous industrialization, the demand for electrical energy in various countries has
increased dramatically, posing significant challenges to the safe operation of power …

[HTML][HTML] Forecasting transmission and distribution system flexibility needs for severe weather condition resilience and outage management

M Zafeiropoulou, I Mentis, N Sijakovic, A Terzic… - Applied Sciences, 2022 - mdpi.com
With the increase in the complexity of the topology of transmission and distribution systems,
associated with the predictability in the management of the dispatch of prosumers, new …

[HTML][HTML] SSA-LSTM: Short-Term photovoltaic power prediction based on feature matching

Z Huang, J Huang, J Min - Energies, 2022 - mdpi.com
To reduce the impact of volatility on photovoltaic (PV) power generation forecasting and
achieve improved forecasting accuracy, this article provides an in-depth analysis of the …

Direct short-term net load forecasting based on machine learning principles for solar-integrated microgrids

G Tziolis, A Livera, J Montes-Romero… - Ieee …, 2023 - ieeexplore.ieee.org
Accurate net load forecasting is a cost-effective technique, crucial for the planning, stability,
reliability, and integration of variable solar photovoltaic (PV) systems in modern power …