Deep neural network-based impacts analysis of multimodal factors on heat demand prediction
Prediction of heat demand using artificial neural networks has attracted enormous research
attention. Weather conditions, such as direct solar irradiance and wind speed, have been …
attention. Weather conditions, such as direct solar irradiance and wind speed, have been …
Design and development of a three-phase Net Meter for V2G enabled charging stations of electric vehicles
AP Kaur, M Singh - Sustainable Energy, Grids and Networks, 2022 - Elsevier
In today's scenario, the estimated exponential growth of Electric vehicles (EVs) has raised
the concern about the spike in electricity demand. Vehicle-to-Grid (V2G) technology has …
the concern about the spike in electricity demand. Vehicle-to-Grid (V2G) technology has …
A container-driven service architecture to minimize the upgrading requirements of user-side smart meters in distribution grids
Advances in information and communication technologies have significantly influenced the
operation of low-voltage distribution grids. As essential elements of distribution grids, user …
operation of low-voltage distribution grids. As essential elements of distribution grids, user …
A Secure and Resilient Smart Energy Meter
The expansion of the Internet of Things (IoT), Smart Grids (SG), and renewable energy
sources has created a greater need for effective cybersecurity measures. These systems …
sources has created a greater need for effective cybersecurity measures. These systems …
Event‐based non‐intrusive load identification algorithm for residential loads combined with underdetermined decomposition and characteristic filtering
X Wu, X Han, KX Liang - IET Generation, Transmission & …, 2019 - Wiley Online Library
For intelligent power utilisation of demand side management, the implementation of non‐
intrusive load identification is an important technology. This study proposed an event‐based …
intrusive load identification is an important technology. This study proposed an event‐based …
Improved artificial neural network method for predicting photovoltaic output performance
S Wang, Y Zhang, C Zhang, M Yang - Global Energy Interconnection, 2020 - Elsevier
To ensure the safety and stability of power grids with photovoltaic (PV) generation
integration, it is necessary to predict the output performance of PV modules under varying …
integration, it is necessary to predict the output performance of PV modules under varying …
[HTML][HTML] Testing of electrical energy meters subject to realistic distorted voltages and currents
This paper presents a study on revenue active electrical energy meters. The huge
installation along the distribution network of these devices made them a key element for …
installation along the distribution network of these devices made them a key element for …
Research on short-term optimization for integrated hydro-PV power system based on genetic algorithm
The combination of hydropower and PV power could make full use of the advantages of
water and solar energy, which forms the integrated hydro-PV system. In this paper, a short …
water and solar energy, which forms the integrated hydro-PV system. In this paper, a short …
Analysis of key factors in heat demand prediction with neural networks
The development of heat metering has promoted the development of statistic models for the
prediction of heat demand, due to the large amount of available data, or big data. Weather …
prediction of heat demand, due to the large amount of available data, or big data. Weather …
Domestic demand-side management: analysis of microgrid with renewable energy sources using historical load data
This paper provides a high-accuracy assessment of domestic demand-side management
(DSM) approach in the context of distributed renewable energy sources (RES). To determine …
(DSM) approach in the context of distributed renewable energy sources (RES). To determine …