Abstract
Distributed generation (DG) can locally provide energies in distribution network and thus help to reduce the negative impact caused by large-scale electric vehicle (EV) charging demand. This paper proposes a two-stage robust DG investment planning model capable of accommodating uncertainty of EV charging demand and renewable generations. The DG investment location and size are optimized in the first stage and the distribution network operation feasibility in the worst case scenario is checked in the second stage to avoid constraint violations. The EV charging demand uncertainty is modeled by sampling from real-life scenarios of travel behavior. Finally, the column-and-constraint generation algorithm is adopted to solve the proposed problem. Simulations on modified IEEE 123-node distribution network demonstrate the effectiveness of the proposed model.
| Original language | English |
|---|---|
| Article number | 8267098 |
| Pages (from-to) | 4654-4666 |
| Number of pages | 13 |
| Journal | IEEE Transactions on Power Systems |
| Volume | 33 |
| Issue number | 5 |
| DOIs | |
| Publication status | Published - 1 Sept 2018 |
Keywords
- charging demand
- distributed generation
- Distributed power generation
- Distribution network
- electric vehicle
- Electric vehicle charging
- Investment
- Planning
- robust optimization
- Robustness
- Uncertainty
- Wind power generation
ASJC Scopus subject areas
- Energy Engineering and Power Technology
- Electrical and Electronic Engineering
