China's flexibility challenge in achieving carbon neutrality by 2060

J Li, MS Ho, C Xie, N Stern - Renewable and Sustainable Energy Reviews, 2022 - Elsevier
China, with a heavy dependence on coal power, has announced a clear goal of carbon
neutrality by 2060. Electrification of final energy use and high penetration of renewable …

A systematic review of building energy sufficiency towards energy and climate targets

S Hu, X Zhou, D Yan, F Guo, T Hong, Y Jiang - Renewable and Sustainable …, 2023 - Elsevier
Among the sufficiency, efficiency, and renewable frameworks for reducing energy use and
energy-related carbon emissions, Building Energy Sufficiency (BES) is gaining attention …

A day-ahead PV power forecasting method based on LSTM-RNN model and time correlation modification under partial daily pattern prediction framework

F Wang, Z Xuan, Z Zhen, K Li, T Wang, M Shi - Energy Conversion and …, 2020 - Elsevier
Photovoltaic (PV) power generation is an effective means to realize solar energy utilization.
Due to the natural characteristics of random fluctuations in solar energy, the applications of …

Photovoltaic power forecast based on satellite images considering effects of solar position

Z Si, M Yang, Y Yu, T Ding - Applied Energy, 2021 - Elsevier
The rapid variation of clouds is the main factor that causes the fluctuation of photovoltaic
power. 1 The satellite images contain plenty of information about clouds, applicable for …

Day-ahead building-level load forecasts using deep learning vs. traditional time-series techniques

M Cai, M Pipattanasomporn, S Rahman - Applied energy, 2019 - Elsevier
Load forecasting problems have traditionally been addressed using various statistical
methods, among which autoregressive integrated moving average with exogenous inputs …

Generative adversarial networks and convolutional neural networks based weather classification model for day ahead short-term photovoltaic power forecasting

F Wang, Z Zhang, C Liu, Y Yu, S Pang, N Duić… - Energy conversion and …, 2019 - Elsevier
Accurate solar photovoltaic power forecasting can help mitigate the potential risk caused by
the uncertainty of photovoltaic out power in systems with high penetration levels of solar …

Deep learning based surface irradiance mapping model for solar PV power forecasting using sky image

Z Zhen, J Liu, Z Zhang, F Wang, H Chai… - IEEE Transactions …, 2020 - ieeexplore.ieee.org
With the increase of solar photovoltaic (PV) penetration in power system, the impact of
random fluctuation of PV power on the secure operation of power grid becomes more and …

A novel peer-to-peer local electricity market for joint trading of energy and uncertainty

Z Zhang, R Li, F Li - IEEE Transactions on Smart Grid, 2019 - ieeexplore.ieee.org
In the future power system, an increasing number of distributed energy resources will be
integrated including intermittent generation like photovoltaic (PV) and flexible demand like …

A review of the role of distributed generation (DG) in future electricity systems

L Mehigan, JP Deane, BPÓ Gallachóir, V Bertsch - Energy, 2018 - Elsevier
The traditional paradigm of centralised electricity systems is being disrupted by increasing
levels of distributed generation. It is unclear as to what level of distributed generation is …

Smart households' aggregated capacity forecasting for load aggregators under incentive-based demand response programs

F Wang, B Xiang, K Li, X Ge, H Lu, J Lai… - IEEE Transactions …, 2020 - ieeexplore.ieee.org
The technological advancement in the communication and control infrastructure helps those
smart households (SHs) that more actively participate in the incentive-based demand …