充电用能约束下工业园区负荷管控的随机优化策略

doi:10.11930/j.issn.1004-9649.202311142

摘要/Abstract

摘要：

为解决工业园区微电网在能源短缺情况下的负荷管理问题，提出一种管理用户特定负荷的新方法。首先，将用户特定负荷管理定义为一个随机预测模型控制问题，对光伏和用户电力需求进行预测建模。然后，结合两阶段随机规划和近似动态规划对其进行求解。最后，在模拟用户对负荷管理响应的环境中，通过2种控制器测试了替代解决方案的有效性。结果表明，即使没有完整的用户响应模型，控制器使用预测模型进行负荷管理也可以显著提高电力可用性和用户的消费效益。

关键词: 工业园区, 负荷管理, 随机预测模型, 两阶段随机规划, 近似动态规划

Abstract:

In order to solve the load management problem of industrial park microgrids in the event of energy shortage, this paper proposes a new method for managing user-specific loads. By defining the user-specific load management as a stochastic predictive model control problem, this method firstly establishes prediction models for photovoltaic and users’ power demand, and then solve them using two-stage stochastic programming and approximate dynamic programming. Finally, the effectiveness of the alternative solutions is tested through two controllers in an environment in which user response to the load management is simulated. The results indicate that even if the controller does not have a complete model of user response, the predictive models used for scheduling the load management can significantly improve the power availability and user consumption efficiency.

Key words: industrial park, load management, random prediction model, two stage stochastic programming, approximate dynamic programming

茹传红, 卢姬, 秦建, 张军达, 常俊晓, 蒋贝妮. 充电用能约束下工业园区负荷管控的随机优化策略[J]. 中国电力, 2025, 58(8): 130-138.

RU Chuanhong, LU Ji, QIN Jian, ZHANG Junda, CHANG Junxiao, JIANG Beini. Stochastic Optimization Strategy for Load Management of Industrial Park Under Energy Constraints[J]. Electric Power, 2025, 58(8): 130-138.

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链接本文: https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202311142

https://www.electricpower.com.cn/CN/Y2025/V58/I8/130

图/表 5

参考文献 21

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负载类型	功率/ W	最小时间/ s	最大时间/ s	完成确认/ 次	频次成本/ 万元
电器1	50	5	15	0.5	0.1
电器2	75	30	180	4	0.1
电视	50	30	240	1	0.5
灯1	300	5	260	2	1.0
灯2	450	5	30	2	0.6
微波炉	650	2	10	2	0.5
吹风机	1800	2	17	2	0.5
洗衣机	500	30	60	3	0.5
烘干机	2500	45	60	3	0.5
洗碗机	1200	60	90	3	0.5

负载类型	功率/ W	最小时间/ s	最大时间/ s	完成确认/ 次	频次成本/ 万元
电器1	50	5	15	0.5	0.1
电器2	75	30	180	4	0.1
电视	50	30	240	1	0.5
灯1	300	5	260	2	1.0
灯2	450	5	30	2	0.6
微波炉	650	2	10	2	0.5
吹风机	1800	2	17	2	0.5
洗衣机	500	30	60	3	0.5
烘干机	2500	45	60	3	0.5
洗碗机	1200	60	90	3	0.5

N	S	T	确定性优化时间/h	两阶段随机优化时间/h	近似动态规划时间/h
5	5	12	0.01	0.01	0.97
5	5	24	0.01	0.02	1.90
5	5	36	0.01	0.03	2.60
5	15	12	0.01	0.03	5.00
5	15	24	0.01	0.06	9.30
5	15	36	0.01	0.09	13.00
15	5	12	0.01	0.04	1.70
15	5	24	0.01	0.07	3.50
15	5	36	0.02	0.11	4.70
15	15	12	0.01	0.11	30.00
15	15	24	0.01	0.24	47.00
15	15	36	0.02	0.39	61.00

N	S	T	确定性优化时间/h	两阶段随机优化时间/h	近似动态规划时间/h
5	5	12	0.01	0.01	0.97
5	5	24	0.01	0.02	1.90
5	5	36	0.01	0.03	2.60
5	15	12	0.01	0.03	5.00
5	15	24	0.01	0.06	9.30
5	15	36	0.01	0.09	13.00
15	5	12	0.01	0.04	1.70
15	5	24	0.01	0.07	3.50
15	5	36	0.02	0.11	4.70
15	15	12	0.01	0.11	30.00
15	15	24	0.01	0.24	47.00
15	15	36	0.02	0.39	61.00

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