Commercial and Industrial Solar Self-Consumption and Curtailment Reasoning QA Dataset
#multi-step reasoning #energy balance analysis #constraint-based reasoning #solar self-consumption optimization #grid export management #solar power curtailment analysis
- 5000
- 0.3GB
- JSON
- CATL
MOBIUSI INC
Updated:2026-10-14
AI Analysis & Value Prop
This dataset presents commercial and industrial solar operating scenarios as text-based questions and answers, covering facility electricity demand, solar generation, grid export limits, and control strategies. It asks models to determine how solar power is self-consumed, exported to the grid, or curtailed, and to explain the conditions behind each conclusion. The data is suited to supervised fine-tuning for logical reasoning and multi-step analysis, as well as model development and evaluation for solar operations and energy management.
Dataset Insights
Sample Examples
{}
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| question | string | A question based on the original operating scenario that asks the model to determine the relationships among solar self-consumption, grid export, and curtailment. |
| conclusion | string | A concise and clear operating judgment in response to the question. |
| export_relation | string | Explains whether solar power is exported, whether exports are constrained by the grid export limit, and the conditions that apply. |
| reasoning_steps | array | An ordered list of the analysis steps needed to derive the conclusion. |
| source_scenario | string | Source text describing facility electricity demand, solar generation, grid export limits, control strategies, and other relevant operating conditions. |
| self_use_relation | string | Explains how solar generation relates to facility demand and states the conditions under which the self-consumption relationship holds. |
| decisive_conditions | string | Summarizes the demand, solar generation, export limit, control strategy, or other operating conditions on which the conclusion depends. |
| curtailment_relation | string | States whether solar output must be curtailed and explains the operating conditions that trigger curtailment. |
Compliance Statement
| Authorization Type | Proprietary - Commercial AI Training License (No Redistribution) |
| Commercial Use | Requires exclusive subscription or authorization contract (monthly or per-invocation charging) |
| Privacy and Anonymization | No PII, no real company names, simulated scenarios follow industry standards |
| Compliance System | Compliant with China's Data Security Law / EU GDPR / supports enterprise data access logs |
Frequently Asked Questions
- What does the dataset contain?
- The dataset consists of commercial and industrial solar operating scenarios paired with reasoning questions and answers. Scenarios cover facility demand, solar generation, grid export limits, and control strategies; annotations include reasoning steps, self-consumption and export relationships, curtailment conditions, final conclusions, and decisive conditions.
- What training tasks is it suited for?
- It is suited to supervised fine-tuning for logical reasoning and multi-step question answering. It helps models determine from operating conditions whether solar power is consumed on site, exported to the grid, or curtailed, and can also support model evaluation and energy management applications.
- What are the dataset size and quality specifications?
- Each sample pairs a specific operating scenario with a question and structured reasoning and conclusion fields, making it possible to use both the reasoning process and the final judgment. Confirm the sample count, file format, and quality acceptance criteria in the relevant product listing or delivery documentation.
- How can I obtain the data, and what licensing applies?
- Acquisition options, delivery formats, and license scope are determined by the product listing or the provider's agreement. Before use, confirm that the license covers your intended training, evaluation, research, or commercial applications.
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Verified for Enterprise UseCite this Work
@dataset{Mobiusi2026,
title={Commercial and Industrial Solar Self-Consumption and Curtailment Reasoning QA Dataset},
author={MOBIUSI INC},
year={2026},
url={https://www.mobiusi.com/datasets/e9b077938f1260fb854e744a6724ec8a},
urldate={2026-10-09},
keywords={commercial solar dataset, solar self-consumption, solar curtailment, grid export limits, solar operations, reasoning QA, reasoning SFT, energy management},
version={1.0}
}Using this in research? Please cite us.
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