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701. Geometric Programming for Optimal Hosting Capacity Allocation in Distribution Grids
Invited abstract in session WD-19: OR in Energy III, stream OR in Energy.
Wednesday, 14:30-16:00Room: 44 (building: 116)
Authors (first author is the speaker)
| 1. | Sicheng Gong
|
| Department of Electrical Engineering, TU Eindhoven | |
| 2. | Koen Kok
|
| 3. | Sjef Cobben
|
| EES, Eindhoven University of Technology |
Abstract
The hosting capacity determines the operational threshold for each integrated energy unit. During hosting capacity allocation, mixed load/generation profiles and intrinsic non-convex network models pose significant computational challenges. This paper introduces an alternative approach for optimal capacity allocation, drawing inspiration from constraint conversion and geometric programming. This approach promises to achieve superior computational speed and a high-quality optimal solution. By initially assessing the multidimensional operational feasible region for involved units, the model simplifies by excluding voltage and current variables, thus reducing complexity. Through model reformulation guided by geometric programming, the model convexity will be established, thus further improving both the speed and solution quality of this solving process.
Relevant case studies reveal that the computation time could be reduced at most by 88.3% by adopting the proposed approach. Due to model convexity, even a higher-quality solution can be achieved accordingly, which yields a better objective function value compared to that using the Gurobi benchmark solver. These findings underscore the penitential of this approach on computation performance enhancement when determining optimal hosting capacity allocation in electricity networks.
Keywords
- Capacity Planning
- Convex Optimization
- Energy Policy and Planning
Status: accepted
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