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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2026
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2604.19085 |
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| _version_ | 1866908982823616512 |
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| author | Sarkar, Dipayan Li, Qifeng |
| author_facet | Sarkar, Dipayan Li, Qifeng |
| contents | The electric vehicle (EV) charging demands (CD) are jointly determined by the EV owners' behavior (i.e., human factor) and the electricity prices (i.e., decisions of distribution system operators (DSO)). However, most existing studies either neglect the decision-dependent nature of EVCD uncertainty or idealistically treat EV owners as perfect decision-makers. This paper formulates the optimal operation of power distribution systems (PDS) as a distributionally robust chance-constrained (DRCC) problem considering EVCDs as endogenous uncertainty (i.e., decision-dependent uncertainty). The Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE) is introduced to capture the human factor of EV owners in the proposed ambiguity set. Case studies on IEEE test systems demonstrate that the proposed method achieves superior performance compared to deterministic and conventional DRCC approaches, thereby enhancing resilience and security in PDS operations. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2604_19085 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | PROMETHEE-based Modeling of Endogenous Behavioral Uncertainty of EV Owners Sarkar, Dipayan Li, Qifeng Systems and Control The electric vehicle (EV) charging demands (CD) are jointly determined by the EV owners' behavior (i.e., human factor) and the electricity prices (i.e., decisions of distribution system operators (DSO)). However, most existing studies either neglect the decision-dependent nature of EVCD uncertainty or idealistically treat EV owners as perfect decision-makers. This paper formulates the optimal operation of power distribution systems (PDS) as a distributionally robust chance-constrained (DRCC) problem considering EVCDs as endogenous uncertainty (i.e., decision-dependent uncertainty). The Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE) is introduced to capture the human factor of EV owners in the proposed ambiguity set. Case studies on IEEE test systems demonstrate that the proposed method achieves superior performance compared to deterministic and conventional DRCC approaches, thereby enhancing resilience and security in PDS operations. |
| title | PROMETHEE-based Modeling of Endogenous Behavioral Uncertainty of EV Owners |
| topic | Systems and Control |
| url | https://arxiv.org/abs/2604.19085 |