Efficient Scheduling of Nonpreemptive Appliances for Peak Load Optimization in Smart Grid

Existing electrical grid systems have a limited amount of real-time monitoring and controlling capabilities of energy generation and consumption facilities, which trigger various technical issues including voltage overloading, demand-supply mismatch, peak load consumption, etc. Some of the primary r...

Full description

Saved in:
Bibliographic Details
Published in:IEEE transactions on industrial informatics 2018-08, Vol.14 (8), p.3447-3458
Main Authors: Chakraborty, Nilotpal, Mondal, Arijit, Mondal, Samrat
Format: Article
Language:English
Subjects:
Algorithms
Approximation algorithms
Computer simulation
Consumption
demand side management (DSM)
Direct load control (DLC)
Electric appliances
Electricity consumption
Energy consumption
Energy utilization
Home appliances
Job shop scheduling
nonpreemptive scheduling
Overloading
Peak load
peak load minimization
Power consumption
Power demand
Production scheduling
Schedules
Scheduling
Smart grid
Stability
strip packing (SP)
Strips
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Existing electrical grid systems have a limited amount of real-time monitoring and controlling capabilities of energy generation and consumption facilities, which trigger various technical issues including voltage overloading, demand-supply mismatch, peak load consumption, etc. Some of the primary reasons for these key issues have been identified to be the inefficient utilization of energy infrastructure and uncoordinated power consumption pattern among the consumers. In this paper, we propose a coordinated load scheduling and controlling algorithm to schedule controllable appliances with the objective to minimize peak load consumption. For this purpose, we model the problem into the strip packing problem, a well-known NP-hard problem, and discuss the applicability of existing heuristics in our problem setup. We then discuss a new offline heuristic solution, named MinPeak, specifically designed for load scheduling problem. We have conducted comprehensive simulation studies using available benchmark data sets and have performed extensive comparative analyses of the proposed algorithm with some of the well-known heuristics for strip packing problem. Furthermore, experiments have been carried out using practical electricity consumption data to evaluate the performance of the algorithm in real life. The results obtained are very encouraging in terms of reducing peak load consumption and overall efficiency of the system.
ISSN:1551-3203
1941-0050
DOI:10.1109/TII.2017.2781284