Fundamentals and business model for resource aggregator of demand response in electricity markets
Demand response (DR) is an effective means to help maintain the balance between power
supply and demand, promote energy conservation and emission reduction. Nevertheless …
supply and demand, promote energy conservation and emission reduction. Nevertheless …
[HTML][HTML] A review of data mining technologies in building energy systems: Load prediction, pattern identification, fault detection and diagnosis
With the advent of the era of big data, buildings have become not only energy-intensive but
also data-intensive. Data mining technologies have been widely utilized to release the …
also data-intensive. Data mining technologies have been widely utilized to release the …
Generative adversarial networks and convolutional neural networks based weather classification model for day ahead short-term photovoltaic power forecasting
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 …
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 …
random fluctuation of PV power on the secure operation of power grid becomes more and …
Smart households' aggregated capacity forecasting for load aggregators under incentive-based demand response programs
The technological advancement in the communication and control infrastructure helps those
smart households (SHs) that more actively participate in the incentive-based demand …
smart households (SHs) that more actively participate in the incentive-based demand …
Capacity and output power estimation approach of individual behind-the-meter distributed photovoltaic system for demand response baseline estimation
Accurate customer baseline load (CBL) estimation is critical for implementing incentive-
based demand response (DR) programs. The increasing penetration of grid-tied distributed …
based demand response (DR) programs. The increasing penetration of grid-tied distributed …
Day-ahead optimal bidding and scheduling strategies for DER aggregator considering responsive uncertainty under real-time pricing
This paper addresses the optimal decision problem of a distributed energy resources (DER)
aggregator who manages wind turbines, solar PV systems and battery energy storage (BES) …
aggregator who manages wind turbines, solar PV systems and battery energy storage (BES) …
A comparative study of clustering techniques for electrical load pattern segmentation
Smart meters have been widely deployed in power networks since the last decade. This
trend has resulted in an enormous volume of data being collected from the electricity …
trend has resulted in an enormous volume of data being collected from the electricity …
A minutely solar irradiance forecasting method based on real-time sky image-irradiance mapping model
Accurate minutely solar irradiance forecasting is the basis of minute-level photovoltaic (PV)
power forecasting. In this paper, a minutely solar irradiance forecasting method based on …
power forecasting. In this paper, a minutely solar irradiance forecasting method based on …
Improving the efficiency of multistep short-term electricity load forecasting via R-CNN with ML-LSTM
Multistep power consumption forecasting is smart grid electricity management's most
decisive problem. Moreover, it is vital to develop operational strategies for electricity …
decisive problem. Moreover, it is vital to develop operational strategies for electricity …