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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2505.19744 |
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| _version_ | 1866910968654594048 |
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| author | Shi, Shaohong Heres, Jacco Tindemans, Simon H. |
| author_facet | Shi, Shaohong Heres, Jacco Tindemans, Simon H. |
| contents | Electrical grid congestion has emerged as an immense challenge in Europe, making the forecasting of load and its associated metrics increasingly crucial. Among these metrics, peak load is fundamental. Non-time-resolved models of peak load have their advantages of being simple and compact, and among them Velander's formula (VF) is widely used in distribution network planning. However, several aspects of VF remain inadequately addressed, including year-ahead prediction, scaling of customers, aggregation, and, most importantly, the lack of probabilistic elements. The present paper proposes a quantile interpretation of VF that enables VF to learn truncated cumulative distribution functions of peak loads with multiple quantile regression under non-crossing constraints. The evaluations on non-residential customer data confirmed its ability to predict peak load year ahead, to fit customers with a wide range of electricity consumptions, and to model aggregations of customers. A noteworthy finding is that for a given electricity consumption, aggregations of customers have statistically larger peak loads than a single customer. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2505_19744 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Scalable quantile predictions of peak loads for non-residential customer segments Shi, Shaohong Heres, Jacco Tindemans, Simon H. Systems and Control Electrical grid congestion has emerged as an immense challenge in Europe, making the forecasting of load and its associated metrics increasingly crucial. Among these metrics, peak load is fundamental. Non-time-resolved models of peak load have their advantages of being simple and compact, and among them Velander's formula (VF) is widely used in distribution network planning. However, several aspects of VF remain inadequately addressed, including year-ahead prediction, scaling of customers, aggregation, and, most importantly, the lack of probabilistic elements. The present paper proposes a quantile interpretation of VF that enables VF to learn truncated cumulative distribution functions of peak loads with multiple quantile regression under non-crossing constraints. The evaluations on non-residential customer data confirmed its ability to predict peak load year ahead, to fit customers with a wide range of electricity consumptions, and to model aggregations of customers. A noteworthy finding is that for a given electricity consumption, aggregations of customers have statistically larger peak loads than a single customer. |
| title | Scalable quantile predictions of peak loads for non-residential customer segments |
| topic | Systems and Control |
| url | https://arxiv.org/abs/2505.19744 |