一种用于可再生能源系统的智能电池储能调度方法
By constructing a time series analysis model and an improved particle swarm optimization algorithm, combined with the operating parameters of photovoltaic, wind power and thermal power generating units, the problem of low accuracy in electricity load prediction in existing technologies has been solved, and the stability and cost optimization of the power system have been achieved.
CN119696051BActive Publication Date: 2026-07-17NANJING INST OF TECH
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- NANJING INST OF TECH
- Filing Date
- 2024-12-03
- Publication Date
- 2026-07-17
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Figure CN119696051B_ABST
Abstract
本发明涉及可再生能源调度技术领域，公开了一种用于可再生能源系统的智能电池储能调度方法，包括以下步骤：步骤S101，采集用电负荷数据；步骤S102，构建光伏序列、风力序列和火力序列；步骤S103，通过时序分析模型预测用电负荷量；步骤S104，预测光伏发电机组、风力发电机组和火力发电机组的发电量；步骤S105，发电机组发电量的总和大于等于用电负荷量，则依次进行发电，否则进入步骤S106；步骤S106，通过改进的粒子群算法生成发电计划；本发明综合考虑了天气条件和社会经济活动的影响，通过时序分析模型来预测未来用电负荷量，提高用电负荷的预测精度，并通过改进的粒子群算法生成发电计划，保证发电成本最小化。
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