Data management in industry 4.0: State of the art and open challenges

TP Raptis, A Passarella, M Conti - IEEE Access, 2019 - ieeexplore.ieee.org
Information and communication technologies are permeating all aspects of industrial and
manufacturing systems, expediting the generation of large volumes of industrial data. This …

Demand response application in industrial scenarios: A systematic mapping of practical implementation

SAB dos Santos, JM Soares, GC Barroso… - Expert Systems with …, 2023 - Elsevier
The industrial sector is the one that consumes the most energy in the world, whereas
manufacturing activities play an important role in the energy consumption in the industry …

Incentive-based demand response for smart grid with reinforcement learning and deep neural network

R Lu, SH Hong - Applied energy, 2019 - Elsevier
Balancing electricity generation and consumption is essential for smoothing the power grids.
Any mismatch between energy supply and demand would increase costs to both the service …

Demand response for home energy management using reinforcement learning and artificial neural network

R Lu, SH Hong, M Yu - IEEE Transactions on Smart Grid, 2019 - ieeexplore.ieee.org
Ever-changing variables in the electricity market require energy management systems
(EMSs) to make optimal real-time decisions adaptively. Demand response (DR) is the latest …

A dynamic pricing demand response algorithm for smart grid: Reinforcement learning approach

R Lu, SH Hong, X Zhang - Applied energy, 2018 - Elsevier
With the modern advanced information and communication technologies in smart grid
systems, demand response (DR) has become an effective method for improving grid …

Multi-agent deep reinforcement learning based demand response for discrete manufacturing systems energy management

R Lu, YC Li, Y Li, J Jiang, Y Ding - Applied Energy, 2020 - Elsevier
With advances in smart grid technologies, demand response has played a major role in
improving the reliability of grids and reduce the cost for customers. Implementing the …

Demand response for industrial micro-grid considering photovoltaic power uncertainty and battery operational cost

C Huang, H Zhang, Y Song, L Wang… - … on Smart Grid, 2021 - ieeexplore.ieee.org
An intelligent demand response (DR) program is developed for multi-energy industrial micro-
grid consisting of manufacturing facilities, photovoltaic (PV) panels, and battery energy …

Data-driven real-time price-based demand response for industrial facilities energy management

R Lu, R Bai, Y Huang, Y Li, J Jiang, Y Ding - Applied Energy, 2021 - Elsevier
Recent advances in smart grid technologies have highlighted demand response (DR) as an
important tool to alleviate electricity demand–supply mismatches. In this paper, a real-time …

Optimal behavior of a hybrid power producer in day-ahead and intraday markets: A bi-objective CVaR-based approach

H Khaloie, M Mollahassani-Pour… - IEEE Transactions …, 2020 - ieeexplore.ieee.org
Coordinated operation of various energy sources has drawn the attention of many power
producers worldwide. In this paper, a Concentrating Solar Power Plant (CSPP) along with a …

Modified deep learning and reinforcement learning for an incentive-based demand response model

L Wen, K Zhou, J Li, S Wang - Energy, 2020 - Elsevier
Incentive-based demand response (DR) program can induce end users (EUs) to reduce
electricity demand during peak period through rewards. In this study, an incentive-based DR …