Title :
Benefits of chronological optimization in capacity planning for electricity markets
Author :
Nweke, C.I. ; Leanez, F. ; Drayton, G.R. ; Kolhe, Mohan
Author_Institution :
UCL SERAus, London, UK
fDate :
Oct. 30 2012-Nov. 2 2012
Abstract :
The applications of optimization techniques in planning exercises with the aid of decision-support tools has benefited from improvements in computing performance over the years. Multi-processing and distributed high performance computing systems, developed in recent times, is waiting to be harnessed by modelling tools and techniques. Long-term Capacity Expansion Planning is constrained by computing performance; hence the load duration curve (LDC) approach is commonly adopted for such long-term models. In this paper chronology is retained in deterministic modelling of long-term investment decisions along with an accurate production cost model co-optimization that accounts for inter-temporal constraints of thermal plants. The South Australian system has been modelled in the PLEXOS® simulation software. Results reveal that investment decisions from the LDC optimization favours high penetration of renewable intermittent generation incurring significant future operational cost; this outcome is shown to be handled by the use of chronological optimization techniques, which provide superior solutions.
Keywords :
power markets; power system planning; PLEXOS simulation software; South Australian system; capacity planning; chronological optimization techniques; decision-support tools; distributed high performance computing systems; electricity markets; inter-temporal constraints; load duration curve; long-term capacity expansion planning; multi-processing computing systems; thermal plants; Computational modeling; Indexes; Load modeling; Random access memory; Capacity Planning; High Performance Computing (HPC); PLEXOS; Wind energy; generation expansion; load slicing; optimization;
Conference_Titel :
Power System Technology (POWERCON), 2012 IEEE International Conference on
Conference_Location :
Auckland
Print_ISBN :
978-1-4673-2868-5
DOI :
10.1109/PowerCon.2012.6401421