Optimal and autonomous incentive-based energy consumption scheduling algorithm for smart grid

By Amir-Hamed Mohsenian-Rad, Vincent W. S. Wong, Juri Jatskevich, Robert Schober. IEEE PES Innovative Smart Grid Technologies Conference, 2010

527 citations recorded by the source corpus.

Subfields: Control and Systems Engineering, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/4fcf03f74cdbec8fc56e5578478604e2acca6988

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In Control and Systems Engineering

In Electrical and Electronic Engineering

Citations in the corpus

Uncertainty-Aware Household Appliance Scheduling Considering Dynamic Electricity Pricing in Smart Home (2013, background): “The proposed framework attempts to achieve a desired trade-off between minimizing the monetary expense and minimizing the waiting time for the operation of each appliance in a household.”
Review on Home Energy Management System Considering Demand Responses, Smart Technologies, and Intelligent Controllers (2018, methodology): “An optimal approach based on game theory is used to determine the optimal consumption schedule for subscribers in a neighborhood to reduce electricity cost [113].”
A Distributed Demand Response Algorithm and Its Application to PHEV Charging in Smart Grids (2012, background): “We note that some appliances like refrigerator and heating have hard consumption scheduling requirements, while others such as washing machine have soft requirements [8].”
A Survey on Demand Response in Smart Grids: Mathematical Models and Approaches (2015, background): “The objective in [36] and [37] is to minimize the cost function imposed to the power utility.”
Wireless Sensor Networks for Cost-Efficient Residential Energy Management in the Smart Grid (2011, background): “We compare iHEM with RLC [4], DsT [5], and OCS [7] in terms of savings and peak load reduction in Table III. iHEM provides similar savings with DsT and RLC while OCS is able to provide more savings.”
Optimal Real-Time Pricing Algorithm Based on Utility Maximization for Smart Grid (2010, unknown): “In this paper, we consider quadratic cost functions [10]:”
A Survey on Demand Response Programs in Smart Grids: Pricing Methods and Optimization Algorithms (2015, unknown): “Finally, in [159], a distributed incentive-based”
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].”
Demand-Side Management via Distributed Energy Generation and Storage Optimization (2013, background): “The capacity indicates how much energy the storage device can accumulate.”
An Optimal Power Scheduling Method for Demand Response in Home Energy Management System (2013, background): “Index Terms—Demand response, energy management system, genetic algorithm, inclining block rate, real-time pricing, smart grid.”
Autonomous Demand-Side Management Based on Game-Theoretic Energy Consumption Scheduling for the Future Smart Grid (2010, result): “The discussions and analysis in this paper extend the preliminary results in our earlier conference paper in [26] in various directions.”
Distributed Internet-Based Load Altering Attacks Against Smart Power Grids (2011, background): “From this and knowing that some demand side management programs encourage message exchanges not only between utility and users but also among users themselves [21], [23], there is a need to implement an efficient group key management between the utility and its corresponding users.”
Smart Grid Communications: Overview of Research Challenges, Solutions, and Standardization Activities (2011, methodology): “For example, the work in [75] uses convex optimization techniques for the power consumption scheduling of appliances to minimize peak-to-average load ratio.”
Optimal Residential Load Control With Price Prediction in Real-Time Electricity Pricing Environments (2010, background): “Clearly, the user is interested in reducing its charges while the utility is interested in having a balanced load demand with a low PAR.”