| 赵安新,张智晟.考虑差异化需求响应不确定性的综合能源系统低碳经济优化调度[J].电力需求侧管理,2025,27(2):35-41 |
| 考虑差异化需求响应不确定性的综合能源系统低碳经济优化调度 |
| Low-carbon economy optimization scheduling of integrated energy system considering the uncertainty of differentiated demand response |
| 投稿时间：2024-12-03 修订日期：2025-01-16 |
| DOI：10. 3969 / j. issn. 1009-1831. 2025. 02. 006 |
| 中文关键词: 综合能源系统 差异化需求响应 混沌松鼠优化算法 低碳经济 实时电价 模糊机会约束 |
| 英文关键词: integrated energy system differentiated demand response chaotic squirrel search algorithm low carbon economy real-time electricity price fuzzy chance constraint |
| 基金项目:国网山东省电力公司科技项目（2020A-022） |
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| 摘要点击次数: 72 |
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| 中文摘要: |
| 为进一步减轻综合能源系统中峰谷时期负荷压力,提升系统运行的低碳经济性,降低系统运行风险,考虑了不同负荷需求响应的差异性及需求响应的不确定性,对需求响应的不确定性进行模糊处理,建立了考虑差异化需求响应不确定性的综合能源系统低碳经济调度模型。首先将不同类型负荷进行差异化定价处理,并利用阶梯型碳排放成本模型对碳排放进行约束；在此基础上,建立包含系统的运维成本、售能收益以及碳排放成本的系统运行总成本最小为目标的规划模型,然后对松鼠算法进行改进,利用混沌松鼠优化算法对模型进行求解。通过实际算例分析,结果表明考虑差异化需求响应不确定性可以提高系统可靠性,平缓负荷曲线,提高系统低碳经济性,验证了所建立调度模型的有效性,同时数据也表明混沌松鼠算法具有更好的寻优能力。 |
| 英文摘要: |
| In order to further reduce the load pressure during peak and valley periods in the integrated energy system, improve the low-carbon economy of system operation, and reduce system operation risks, the differences in demand response of different loads and the uncertainty of demand response are considered. The uncertainty of demand response is fuzzily processed, and a low-carbon economic dispatch model for the integrated energy system considering the uncertainty of differentiated demand response is established. Firstly, differentiate pricing for different types of loads and use a tiered carbon emission cost model to constrain carbon emissions. On this basis, a planning model is established with the goal of minimizing the total operating cost of the system, including the operation and maintenance cost, energy sales revenue, and carbon emission cost. Then, the squirrel algorithm is improved and solved using the chaotic squirrel optimization algorithm. Through actual case analysis, the results show that considering the uncertainty of differentiated demand response can improve system reliability, smooth the load curve, and improve the low-carbon economy of the system. This verifies the effectiveness of the established scheduling model, and the data also shows that the chaotic squirrel algorithm has better optimization ability. |
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