Houseec: Day-ahead household electrical energy consumption forecasting using deep learning
Short-term load forecasting is integral to the energy planning sector. Various techniques
have been employed to achieve effective operation of power systems and efficient market …
have been employed to achieve effective operation of power systems and efficient market …
Short-term electricity demand forecasting using autoregressive based time varying model incorporating representative data adjustment
This paper presents the development of an autoregressive based time varying (ARTV)
model to forecast electricity demand in a short-term period. The ARTV model is developed …
model to forecast electricity demand in a short-term period. The ARTV model is developed …
Short-term load forecasting for a single household based on convolution neural networks using data augmentation
SK Acharya, YM Wi, J Lee - Energies, 2019 - mdpi.com
Advanced metering infrastructure (AMI) is spreading to households in some countries, and
could be a source for forecasting the residential electric demand. However, load forecasting …
could be a source for forecasting the residential electric demand. However, load forecasting …
Bottom-up load forecasting with Markov-based error reduction method for aggregated domestic electric water heaters
X Gong, JL Cardenas-Barrera… - IEEE Transactions …, 2019 - ieeexplore.ieee.org
Domestic electric water heaters (DEWHs) can provide operational flexibility for load control
due to their energy storage capacity. Load forecasting for aggregated DEWHs is important …
due to their energy storage capacity. Load forecasting for aggregated DEWHs is important …
Load forecasting under changing climatic conditions for the city of Sydney, Australia
In the current context, climate change has become an unequivocal phenomenon. Although it
primarily encompasses change in temperature, nevertheless other weather variables such …
primarily encompasses change in temperature, nevertheless other weather variables such …
Short-term forecasting of electricity spot prices containing random spikes using a time-varying autoregressive model combined with kernel regression
Forecasting spot prices of electricity is challenging because it not only contains seasonal
variations, but also random, abrupt spikes, which depend on market conditions and network …
variations, but also random, abrupt spikes, which depend on market conditions and network …
[PDF][PDF] Aggregated load forecast and control for creating alternative power system resources using thermostatically controlled loads
X Gong - 2021 - unbscholar.lib.unb.ca
Power systems are evolving and are trying to use loads and communication infrastructure as
a way to compensate the system generation for peak load shaving and ancillary services …
a way to compensate the system generation for peak load shaving and ancillary services …
Integrated multi-horizon power and energy forecast for aggregated electric water heaters
Domestic electric water heaters (DEWH) are common residential loads and good candidates
for direct load control owing to their energy storage capacity. Power prediction for …
for direct load control owing to their energy storage capacity. Power prediction for …
[CITATION][C] Forecasting Electricity Demand and Price Spike for Improving Electricity Market Operation
DH Vu - 2017