集成电动汽车的家庭电热综合能源系统负荷调度优化

doi:10.11930/j.issn.1004-9649.202305056

摘要/Abstract

摘要：

随着“碳中和”“碳达峰”等政策的提出，新能源和异质能源的调度优化成为减少碳排放的主要措施。而家庭综合能源系统在能源需求侧占比较大，如何构建合理的家庭能源系统以及实现家庭负荷优化的能量管理成为亟待解决的问题。为了实现家庭电热综合能源系统中负荷的灵活调度，充分考虑电动汽车及异质能源间设备的出力影响，提出了一种集成电转热设备热泵和电动汽车的家用燃料电池热电联产（domestic fuel cell-based combined heat and power，DFCCHP）系统综合优化调度方案。首先，根据家庭用电、用热特征将电、热负荷进行细化分类，引入热舒适度评价指标（predicted mean vote，PMV）进行室内温度的控制，建立负荷模型；其次，引入热泵和电动汽车，建立在分时电价和分时气价下以能源购买费用最小为目标的家庭综合能源系统优化调度模型，并使用Cplex求解器对模型求解；最后，通过仿真验证调度模型的合理性、可行性和环保性，以及热泵和电动汽车对系统经济性的影响。结果表明，在不同天气条件下，热泵和电动汽车的引入可有效减少系统的购能成本与碳排放，所得结论为进一步完善家庭综合能源系统拓扑及负荷优化调度提供了一定的理论分析基础。

关键词: 热电联产, 综合能源系统, PMV, 优化调度, 经济分析

Abstract:

With the introduction of such policies as "carbon neutrality" and "carbon peak", the dispatch optimization of new energy and heterogeneous energy has become the main measure to reduce carbon emissions. As the home integrated energy system accounts for a large proportion on the energy demand side, it is urgently needed to construct a reasonable home energy system to realize the energy management of home load optimization, In order to realize the flexible dispatch of load in the home electric-thermal integrated energy system, this paper proposes a comprehensive optimization dispatch scheme of domestic fuel cell-based combined heat and power (DFCCHP) system integrating heat pump and electric vehicle, with full consideration of the output influence of electric vehicles and heterogeneous energy equipment. Firstly, the electric and thermal loads are classified in detail according to the home electricity and heat characteristics, and the predicted mean vote (PMV) is introduced to control the indoor temperature, and a load model is established. Secondly, the heat pump and electric vehicle are introduced, and a home integrated energy system optimization dispatch model is established with the minimum energy purchase cost as the objective under time-of-use electricity price and time-of-use gas price, and the Cplex solver is used to solve the model. Finally, the rationality, feasibility and environmental protection of the proposed dispatch model, as well as the impact of heat pump and electric vehicle on the economic performance of the system are verified through simulation. The results show that under different weather conditions, the introduction of heat pump and electric vehicle can effectively reduce the system's energy purchase cost and carbon emissions, and the reached conclusions can provide a certain theoretical analysis basis for further improving the home integrated energy system topology and load optimization dispatch.

Key words: combined heat and power generation, integrated energy systems, PMV, optimized scheduling, economic analysis

王云龙, 韩璐, 罗树林, 吴涛. 集成电动汽车的家庭电热综合能源系统负荷调度优化[J]. 中国电力, 2024, 57(5): 39-49.

Yunlong WANG, Lu HAN, Shulin LUO, Tao WU. Load Scheduling Optimization of Home Electric Heating Integrated Energy System with Electric Vehicle[J]. Electric Power, 2024, 57(5): 39-49.

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链接本文: https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202305056

https://www.electricpower.com.cn/CN/Y2024/V57/I5/39

图/表 13

图 1 家庭综合能源系统结构

Fig.1 Structure of home integrated energy system

表 1 PMV热感觉标尺

Table 1 PMV thermal sensing scale

热感觉		热		暖		微暖		适中		微凉		凉		冷
PMV值		+3		+2		+1		0		–1		–2		–3

图 2 热水消耗量与室外温度

Fig.2 Hot water consumption and outdoor temperature

表 2 可调度负荷参数

Table 2 Schedulable load parameters

负荷类型	工作时间范围	额定功率/kW	所需工作时间（采样间隔个数）
可中断负荷1	00:00—07:00, 19:00—23:45	0.4	4, 6
可中断负荷2	07:00—10:00, 14:00—17:00	0.4	2, 5
可中断负荷3	12:00—15:00, 18:00—21:00	0.6	5, 2
不可中断负荷1	09:00—12:00	0.7	3
不可中断负荷2	15:00—18:00	0.7	3
不可中断负荷3	21:00—23:45	0.7	3
不可中断负荷4	07:00—14:00	0.5	3

图 3 不同天气下光伏预测出力数据

Fig.3 PV forecast output data under different weather conditions

表 3 算例仿真场景

Table 3 Example simulation scenarios

场景	天气	含热泵	含电动汽车
1	晴天	×	×
2	晴天	√	√
3	阴天	×	×
4	阴天	√	√

图 4 场景1与场景2电能调度结果对比

Fig.4 Comparison of power scheduling results between Scenario 1 and Scenario 2

图 5 场景1与场景2热能调度结果对比

Fig.5 Comparison of thermal energy scheduling results between Scenario 1 and Scenario 2

图 6 场景2家庭电负荷调度结果

Fig.6 Scenario 2 home electrical load scheduling result

图 7 场景4家庭电负荷调度结果

Fig.7 Scenario 4 home electrical load scheduling result

图 8 场景2与场景4电能调度结果对比

Fig.8 Comparison of power scheduling results between Scenario 2 and Scenario 4

图 9 场景2与场景4热能调度结果对比

Fig.9 Comparison of thermal energy scheduling results between Scenario 2 and Scenario 4

表 4 场景2各时段的平均室内温度及PMV 值

Table 4 Scenario 2 average indoor temperature and PMV values in each period

时段	供热温度/℃	λ_PMV	时段	供热温度/℃	λ_PMV
1	20.41	–0.50	13	20.53	–0.47
2	20.41	–0.50	14	20.41	–0.50
3	20.41	–0.50	15	20.42	–0.50
4	20.41	–0.50	16	20.87	–0.40
5	20.41	–0.50	17	23.42	–0.50
6	20.46	–0.49	18	24.18	0.34
7	20.54	–0.47	19	22.61	–0.01
8	20.41	–0.50	20	20.74	–0.43
9	20.55	–0.47	21	20.96	–0.38
10	20.44	–0.49	22	21.68	–0.22
11	20.76	–0.42	23	20.46	–0.49
12	20.54	–0.47	24	20.46	–0.49

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