Paper Info
Title
Evolutionary scheduling of flexible offers for balancing electricity supply and demand
Abstract
To address the needs of rapidly changing energy markets, an energy data management system capable of supporting higher utilization of renewable energy sources is being developed. The system receives flexible offers from producers and consumers of energy, aggregates them on a regional level and schedules the aggregated flexible offers to balance forecast energy supply and demand. This paper focuses on formulating and solving the optimization problem of scheduling aggregated flexible offers within such a system. Three metaheuristic scheduling algorithms (a randomized greedy search, an evolutionary algorithm and a hybrid between the two) tailored to this problem are introduced and their performance is assessed on a benchmark test problem and two realistic problems. The best results are achieved by the evolutionary algorithms, which can efficiently handle thousands of aggregated flex-offers.
Year
DOI
Venue
2012
10.1109/CEC.2012.6256494
IEEE Congress on Evolutionary Computation
Keywords
Field
DocType
evolutionary computation,optimization,schedules,benchmark testing,scheduling
Mathematical optimization,Evolutionary algorithm,Scheduling (computing),Computer science,Evolutionary computation,Greedy algorithm,Schedule,Energy supply,Optimization problem,Metaheuristic
Conference
ISBN
Citations 
PageRank 
978-1-4673-1508-1
9
0.85
References 
Authors
0
3
Name
Order
Citations
PageRank
Tea Tusar118119.91
Erik Dovgan2709.74
Bogdan Filipic336126.93