Benefits of Chronological Optimization in Capacity Planning for Electricity Markets

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 (R) 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.