(637h) A Mid-Term, Market-Based Power Systems Planning Model
AIChE Annual Meeting
2016
2016 AIChE Annual Meeting
Computing and Systems Technology Division
Design, Operations, and Analysis of Power Systems
Thursday, November 17, 2016 - 10:43am to 11:02am
Moreover, the expansion of grid interconnections is of paramount importance in order to facilitate the transition towards a power generation mix with very high levels of renewables penetration and lower CO2 emission content (Hasan et al., 2015). As a direct consequence, the increased transmission capacity enables the more efficient utilization of the flexibility of the power plant fleet by increasing the flexibility to balance the intermittent wind and solar output (Hadera et al., 2015). Not surprisingly, the deployment of renewable energy at regions with weak interconnections infrastructure and far from the main load consuming centres often results in overloading of transmission lines (Xiao et al., 2011).
In that context, this work presents a generic Mixed Integer Linear Programming (MILP) model integrating a Mid-term Energy Planning model, which implements generation and transmission system planning at a yearly level (Koltsaklis et al., 2014), with a Unit Commitment model (Koltsaklis and Georgiadis, 2015), which simulates the Day-Ahead Electricity Market. The proposed modelling framework identifies the implementation (or not) of the interconnection of specific autonomous power networks to the mainland electric system, as well as the optimum interconnection capacity. It also systematically quantifies the effects in the Day-Ahead electricity market and on the energy mix. The proposed model can provide useful insights into the strategic and challenging decisions to be determined by investors and/or policy makers at a national and/or regional level, by providing the optimal energy roadmap and management, as well as clear price signal on critical energy projects under real operating and design constraints.
Keywords: Mixed integer linear programming; Unit commitment problem; Mid-term energy planning; Electric interconnections; Power markets
References
Hadera, H., Harjunkoski, I., Sand, G., Grossmann, I. E. & Engell, S. 2015. Optimization of steel production scheduling with complex time-sensitive electricity cost. Computers & Chemical Engineering, 76, 117-136.
Hasan, M. M. F., First, E. L., Boukouvala, F. & Floudas, C. A. 2015. A multi-scale framework for CO2 capture, utilization, and sequestration: CCUS and CCU. Computers & Chemical Engineering, 81, 2-21.
Koltsaklis, N. E., Dagoumas, A. S., Kopanos, G. M., Pistikopoulos, E. N. & Georgiadis, M. C. 2014. A spatial multi-period long-term energy planning model: A case study of the Greek power system. Applied Energy, 115, 456-482.
Koltsaklis, N. E. & Georgiadis, M. C. 2015. A multi-period, multi-regional generation expansion planning model incorporating unit commitment constraints. Applied Energy, 158, 310-331.
Xiao, J., Hodge, B.-M. S., Pekny, J. F. & Reklaitis, G. V. 2011. Operating reserve policies with high wind power penetration. Computers & Chemical Engineering, 35, 1876-1885. References