Mathematical modelling and methodology for cost optimization of variable renewable electricity integration
Licentiate thesis, 2021
The models developed in this thesis concern optimization of long-term investments in the electricity system. They aim at minimizing investment and production costs under electricity production constraints, using different spatial resolutions and technical detail, while meeting the electricity demand.
Furthermore, they are able to capture some of the variation management strategies necessary for electricity systems that include a large share of variable renewable electricity. These models are very large in nature due to the high temporal resolution needed to capture the wind variations, and thus different decomposition methods are applied to reduce solution times. We develop two different decomposition methods: 1) Lagrangian relaxation combined with variable splitting solved using a subgradient algorithm, and 2) a heuristic decomposition approach using a consensus algorithm. In both cases, the decomposition is done with respect to the temporal resolution by dividing the year into 2-week periods. The decomposition methods are tested and evaluated for cases involving regions with different energy mixes and conditions for wind power. Numerical results show faster computation times compared to the non-decomposed models and capacity investment options similar to the optimal solutions given by the latter models.
variable renewable electricity
electricity system modelling
wind power integration
long-term investment models
Chalmers, Mathematical Sciences, Applied Mathematics and Statistics
Granfeldt, C., Strömberg, A.-B., Göransson, L. Managing the temporal resolution in electricity system investment models with a large share of wind power: An approach using Lagrangian relaxation and variable splitting
Management of Wind Power Variations in Electricity System Investment Models. A Parallel Computing Strategy
SN Operations Research Forum,; Vol. 2(2021)p. 1-30
Mathematical modelling of large scale integration of variable electricity generation - a new modelling paradigm
Swedish Energy Agency (39907-1), 2015-07-01 -- 2018-12-31.
Swedish Energy Agency (39907-1), 2015-07-01 -- 2020-12-31.
Areas of Advance
Chalmers University of Technology
Pascal, Chalmers tvärgata 3, och online via Zoom
Opponent: Dr. Peter Lindroth, Andra AP-fonden (AP2), Göteborg