考虑负荷灵活调节潜力的分布式能源系统能量管理策略

doi:10.11930/j.issn.1004-9649.202411005

摘要/Abstract

摘要：

气候变化、电价波动及用电行为对负荷侧灵活调节边界的影响，制约了分布式能源系统日前能量管理策略的经济性。针对这一问题，提出了一种基于负荷灵活调节潜力的两阶段随机优化方法。第一阶段以最小化分布式能源系统综合运行成本为目标，涵盖设备维护、能源采购、碳排放以及电/热柔性负荷补偿成本。第二阶段引入补偿机制以修正可再生能源出力偏差与灵活负荷调节边界偏差，构建考虑日内备用成本的动态优化模型。算例分析表明，所提方法可有效降低系统总运行成本并提升可再生能源利用率。进一步的灵敏度分析表明，相较于可调电负荷的不确定性，可调热负荷的不确定性对系统运行的影响更为显著。

关键词: 分布式能源系统, 场景法, 柔性负荷, 能量管理策略

Abstract:

The impact of climate change, electricity price fluctuations, and electricity consumption behavior on the flexible regulation boundaries of the load side constrains the economic efficiency of day-ahead energy management strategies in distributed energy systems. To address this issue, a two-stage stochastic optimization method based on the potential for flexible load regulation is proposed. In the first stage, the objective is to minimize the comprehensive operating costs of the distributed energy system, encompassing equipment maintenance, energy procurement, carbon emissions, and compensation costs for flexible electric and thermal loads. The second stage incorporates a compensation mechanism to mitigate deviations in renewable energy output and flexible load regulation boundaries, formulating a dynamic optimization model that accounts for intraday reserve costs. Case study results demonstrate that the proposed method effectively reduces total system operating costs and enhances renewable energy utilization. Further sensitivity analysis indicates that, compared to adjustable electric load uncertainty, adjustable thermal load uncertainty exerts a more pronounced impact on system operation.

Key words: distributed energy system, scenario approach, flexible load, energy management strategy

郭琦, 陈孟晓, 余佳微, 黄以恒, 郭海平. 考虑负荷灵活调节潜力的分布式能源系统能量管理策略[J]. 中国电力, 2025, 58(8): 60-68.

GUO Qi, CHEN Mengxiao, YU Jiawei, HUANG Yiheng, GUO Haiping. Energy Management Strategy for Distributed Energy Systems Considering the Regulation Capability from Flexible Loads[J]. Electric Power, 2025, 58(8): 60-68.

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链接本文: https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202411005

https://www.electricpower.com.cn/CN/Y2025/V58/I8/60

图/表 9

图 1 分布式能源系统

Fig.1 Distributed energy system

表 1 分布式能源系统主要设备参数

Table 1 Main equipment parameters of distributed energy system

设备	出力上限/kW	转换效率
燃气轮机	150	0.35 0.60
燃气锅炉	150	0.95
电锅炉	150	0.90

表 2 分布式能源系统所在地区分时电价

Table 2 Time of use electricity prices in regions where distributed energy systems are located

时段		价格(元·(kW·h)^–1)
谷段（01:00—07:00, 23:00—24:00）		0.2
平段（08:00, 12:00, 19:00—22:00）		0.6
峰段（09:00—11:00, 13:00—18:00）		1.0

图 2 DES系统电能调度策略

Fig.2 Energy dispatch strategy for DES system

图 3 DES系统热能调度策略

Fig.3 Thermal energy scheduling strategy for DES system

图 4 室外温度曲线与负荷侧调节后室内温度曲线

Fig.4 Outdoor temperature curve and indoor temperature curve after load side regulation

表 3 不同方案成本组成

Table 3 Cost composition of different plans 单位：元

方案	补偿成本	运行成本	调整成本	总成本
不考虑可调负荷	0	9 357.6	1 860.2	11 217.8
考虑可调负荷	1 168.7	7 163.0	875.9	9 207.6

表 4 不同不确定性场景下的系统总成本

Table 4 Total system costs under different uncertainty scenarios 单位：元

场景	补偿成本	运行成本	调整成本	总成本
0	1 064.3	7 184.3	0	8 248.6
1	1 163.1	7 153.1	806.5	9 122.7
2	1 008.0	7 246.9	32.5	8 287.5
3	1 152.4	7 110.6	36.1	8 299.1

表 5 不同场景下的VSS

Table 5 VSS under different scenarios

场景	$ {\varGamma _{\rm S}} $/元	$ {\varGamma _{\rm D}} $/元	V_SS/%
确定性场景	8 248.7	8 248.7	0
不确定性场景	9 207.6	9 397.1	2

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