Non-preemptive Scheduling in a Smart Grid Model and Its Implications on Machine Minimization

@article{Liu2016NonpreemptiveSI,
  title={Non-preemptive Scheduling in a Smart Grid Model and Its Implications on Machine Minimization},
  author={Fu-Hong Liu and Hsiang-Hsuan Liu and Prudence W. H. Wong},
  journal={Algorithmica},
  year={2016},
  pages={1-43}
}
We study a scheduling problem arising in demand response management in smart grid. Consumers send in power requests with a flexible feasible time interval during which their requests can be served. The grid controller, upon receiving power requests, schedules each request within the specified interval. The electricity cost is measured by a convex function of the load in each timeslot. The objective is to schedule all requests with the minimum total electricity cost. Previous work has studied… 

Greedy is Optimal for Online Restricted Assignment and Smart Grid Scheduling for Unit Size Jobs

This analysis studies online scheduling of unit-sized jobs in two related problems, namely, restricted assignment problem and smart grid problem, and proves the optimality without giving the exact bounds on competitive ratio.

Approximation Algorithms for Demand Strip Packing

The main result is a (5/3 + ε)approximation algorithm for any constant ε > 0.5, which achieves best-possible approximation factors for some relevant special cases.

References

SHOWING 1-10 OF 59 REFERENCES

Peak demand scheduling in the Smart Grid

A general version of the problem scheduling power jobs so as to minimize peak demand in which the job intervals can be staggered is considered and an effective new heuristic algorithm is provided.

Online Scheduling for Electricity Cost in Smart Grid

This paper proposes a greedy algorithm of the online scheduling problem in the smart grid, which is arised in demand response management under the scenario with real-time communication between the grid operator and consumers, and proves it is optimal.

Control and optimization meet the smart power grid: scheduling of power demands for optimal energy management

This work designs a stochastic model for the case when demands are generated continually and scheduling decisions are taken online, and focuses on long-term average cost.

An Exact Algorithm for Non-preemptive Peak Demand Job Scheduling

Simulation results using household power usage data show that peak power demand can be significantly reduced by allowing some flexibility in job execution times and applying scheduling.

Power strip packing of malleable demands in smart grid

A simple linear time algorithm is introduced that almost perfectly arranges all the demands in a rectangle [0, A/A̅] × [ 0, A̅], and it is shown that it is asymptotically optimal.

Competitive Algorithms for Demand Response Management in Smart Grid

A scheduling problem which abstracts a model of demand-response management in Smart Grid, where each job j is characterized by a release date, and a power request function representing its request demand at specific times.

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

Simulation results confirm that the proposed distributed algorithm significantly reduces the peak-to-average-ratio (PAR) in load demand and the total cost in the system.

Multi-Objective Optimal Energy Consumption Scheduling in Smart Grids

Two evolutionary algorithms (EAs) are developed to obtain the Pareto-front solutions and the ε-Pareto front solutions to the CMOP, respectively, which are validated by extensive simulation results.

A Communication-Based Appliance Scheduling Scheme for Consumer-Premise Energy Management Systems

A joint access and scheduling approach for appliances is developed to enable in-home appliances to coordinate power usage so that the total energy demand for the home is kept below a target value.

Incentive-Based Energy Consumption Scheduling Algorithms for the Smart Grid

  • S. CaronG. Kesidis
  • Engineering
    2010 First IEEE International Conference on Smart Grid Communications
  • 2010
A dynamic pricing scheme incentivizing consumers to achieve an aggregate load profile suitable for utilities, and how close they can get to an ideal flat profile depending on how much information they share is studied.
...