| 段军红,梁 琛,李亚昕,王维洲,甄文喜,许苗苗.计及光伏不确定性的居民储荷优化调度策略[J].电力需求侧管理,2024,26(6):107-111 |
| 计及光伏不确定性的居民储荷优化调度策略 |
| Optimal storage-load dispatch strategy for residents considering photovoltaic uncertainty |
| 投稿时间：2024-09-07 修订日期：2024-10-09 |
| DOI：10. 3969 / j. issn. 1009-1831. 2024. 06. 017 |
| 中文关键词: 仿射算法 光伏预测误差 微储能 储荷优化调度 用户满意度 |
| 英文关键词: affine algorithm photovoltaic prediction error micro energy storage storage-load optimization scheduling user satisfaction |
| 基金项目:国家电网公司科技项目（52272223004T） |
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| 中文摘要: |
| 针对光伏功率预测误差对调度结果影响严重的问题,提出了计及光伏不确定性的居民储荷优化调度策略。采用仿射算法量化光伏出力不确定性,建立以居民日用电成本最小和舒适度最大为目标的储荷优化调度模型求解得到居民微储能充放电计划和日前用电计划。经仿真验证,所提算法能够充分考虑光伏出力的不确定性,有效提升调度模型的准确性,在保证用户满意度的同时缓解高峰用电压力。 |
| 英文摘要: |
| In order to solve the problem that the PV power prediction error has a serious impact on the dispatch results, an optimal storageload dispatch strategy for residents considering photovoltaic uncertainty is proposed. The affine algorithm was used to quantify the uncertainty of photovoltaic output, and a storage-load optimization scheduling model was established with the goal of minimizing the daily electricity cost and maximizing the comfort of residents, and the Gurobi solver was used to calculate the micro-energy storage charging and discharging plan and the day-ahead electricity consumption plan of residents. Through simulation verification, the proposed algorithm can fully consider the uncertainty of photovoltaic output, effectively improve the accuracy of the scheduling model, and alleviate the pressure of peak power consumption while ensuring user satisfaction. |
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