Management and Control of Domestic Smart Grid Technology

By A. Molderink, V. Bakker, M. Bosman, J. Hurink, G. Smit. IEEE Transactions on Smart Grid, 2010

677 citations recorded by the source corpus.

Subfields: Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/016969e097b466e97a4e0f221e772f9457b57c49

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In Electrical and Electronic Engineering

Citations in the corpus

Energy-Efficient Information and Communication Infrastructures in the Smart Grid: A Survey on Interactions and Open Issues (2015, background): “Several studies apply optimization models [38]–[40] while others use neural networks [41], [42] or game-theory [43]–[46].”
Smart Grid — The New and Improved Power Grid: A Survey (2012, neutral): “We encourage the readers to refer back to this classification in case of any confusion while reading the text.”
Wireless Sensor Networks for Cost-Efficient Residential Energy Management in the Smart Grid (2011, methodology): “Our optimization-based residential energy management is different than [6] since we aim to minimize the cost of electricity based on TOU rates.”
Wireless Architectures for Heterogeneous Sensing in Smart Home Applications: Concepts and Real Implementation (2013, methodology): “Automatic demand scheduling has been implemented using particle swarm optimization [75], neural-network-based prediction [77], or game theory approaches [78].”
The role of communication systems in smart grids: Architectures, technical solutions and research challenges (2013, background): “For instance, there will be home EMSs (HEMSs) to monitor and control the electricity usage in households , and building EMSs (BEMSs) coordinating multiple HEMSs to maximize the energy efficiency of entire buildings [77].”
MOD-DR: Microgrid optimal dispatch with demand response (2017, background): “[1], who proposed the three-step control methodology of prediction, planning, and real-time control, though their approach is iterative dynamic programming with agent-based load scheduling, and their test case is conducted in a single house as compared to district level planning in the present study”
A Review on Microgrids’ Challenges & Perspectives (2021, neutral): “Utilizing ICT devices in residentials has become ubiquitous due to customers’ active participation in demand management [146].”
Uncertainty-Aware Household Appliance Scheduling Considering Dynamic Electricity Pricing in Smart Home (2013, background): “Extensive research on the demand side load management also has been performed for a neighborhood with multiple customers.”
A Survey on Demand Response in Smart Grids: Mathematical Models and Approaches (2015, methodology): “The stochastic inputs in [77] and [78] are derived from uncertain electricity price and the random nature of renewable production.”