arXiv:2504.07131v1 Announce Type: new
Abstract: Generation planning approaches face challenges in managing the incompatible mathematical structures between stochastic production simulations for reliability assessment and optimization models for generation planning, which hinders the integration of reliability constraints. This study proposes an approach to embedding reliability verification constraints into generation expansion planning by leveraging a weighted oblique decision tree (WODT) technique. For each planning year, a generation mix dataset, labeled with reliability assessment simulations, is generated. An WODT model is trained using this dataset. Reliability-feasible regions are extracted via depth-first search technique and formulated as disjunctive constraints. These constraints are then transformed into mixed-integer linear form using a convex hull modeling technique and embedded into a unit commitment-integrated generation expansion planning model. The proposed approach is validated through a long-term generation planning case study for the Electric Reliability Council of Texas (ERCOT) region, demonstrating its effectiveness in achieving reliable and optimal planning solutions.
Embedding Reliability Verification Constraints into Generation Expansion Planning
In generation planning, there is a challenge in managing the incompatible mathematical structures between stochastic production simulations and optimization models. This incompatibility creates difficulties in integrating reliability constraints into the planning process. However, an approach using a weighted oblique decision tree (WODT) technique has been proposed to solve this problem.
The proposed approach involves generating a generation mix dataset labeled with reliability assessment simulations for each planning year. This dataset is then used to train a WODT model. Using depth-first search technique, reliability-feasible regions are extracted and transformed into disjunctive constraints. These constraints are further converted into mixed-integer linear form using a convex hull modeling technique. Finally, the transformed constraints are embedded into a unit commitment-integrated generation expansion planning model.
This multi-disciplinary approach combines concepts from mathematical modeling, optimization, and reliability assessment. By leveraging the WODT technique, the proposed approach enables the integration of reliability constraints into generation expansion planning, ultimately leading to reliable and optimal planning solutions.
The effectiveness of this approach is demonstrated through a case study for the Electric Reliability Council of Texas (ERCOT) region. The long-term generation planning study validates the proposed approach, showing that it can achieve both reliability and optimality in the planning solutions.
Overall, this research contributes to the field of generation planning by addressing the challenge of integrating reliability constraints. The approach presented in this study provides a framework for effectively incorporating reliability assessment simulations into the planning process, leading to more robust and reliable generation expansion plans.