Planning method of highway-traffic self-contained microgrid system orientedto multiple energy demand scenarios
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摘要: 面向交通用能绿色化、清洁化转型需求，提出了基于交通基础设施蕴含的风、光可再生资源禀赋构建绿色、弹性、自洽和可持续发展的公路交通自洽微网系统规划方法；基于公路交通基础设施空间范围内的可再生能源发电装置、储能装置、用能负荷设备及微网系统，构建了“源-网-荷-储”协同联动的公路交通自洽微网系统架构；针对中国不同地域特点、不同自然资源禀赋以及不同电网支撑条件确定的应用场景，提出了西藏、吉林、浙江3种典型场景下的公路交通自洽微网基础模型，在此基础上，考虑微网建设经济性与微网内可再生能源消纳率等因素，以最小化微网年均综合成本为目标，在各能源设备、储能装置的出力约束及微网内的功率平衡约束下构建系统规划模型，采用粒子群优化算法对微网内各能源设备的配置容量进行优化求解；为验证粒子群算法的全局搜索能力与收敛特性，减小算法求解过程中的随机因素，对3种典型场景的规划方案分别进行了50次独立求解的仿真试验。研究结果表明：利用构建的模型和求解方法，在无大电网支撑场景下公路交通自洽微网系统依靠蓄电池和氢储能协同工作，可实现可再生能源自洽率99.95%的配置效果，弃风弃光率仅为1.34%，表明合理的储能配置可以有效减少风光出力间歇性和波动性带来的问题，实现良好的可调节性，保证微网系统的供电可靠性，可为中国公路交通自洽微网系统规划设计提供决策支持。Abstract: To address the demand for green and clean energy consumption in transportation, a method for planning a green, resilient, self-contained, and sustainable highway-traffic self-contained microgrid system was proposed. Based on the endowment of wind and solar renewable resources within transportation infrastructure, initially, the architecture of a highway-traffic self-contained microgrid system was constructed around the renewable energy generation devices, energy storage devices, energy consumption loads, and the microgrid system within the spatial scope of highway transportation infrastructure. The architecture facilitated a synergistic integration of "source-grid-load-storage". Subsequently, based on varying regional characteristics, natural resource endowments, and power grid support conditions in China, the basic models of highway-traffic self-contained microgrid under three typical scenarios of Xizang, Jilin and Zhejiang were proposed. Building upon this, considering the factors such as the economic feasibility of microgrid construction and the renewable energy consumption rate within the microgrid, a system planning model was developed. The goal of the model was to minimize the average annual comprehensive cost of the microgrid, subject to the output constraints of various energy and storage devices and the power balance constraints within the microgrid. Finally, the particle swarm optimization algorithm was employed to optimize the capacity configuration of each energy device within the microgrid. To validate the global search capability and convergence characteristics of the particle swarm algorithm, and to reduce the random factors in the solving process, 50 independent simulation experiments were conducted on the planning schemes for three typical scenarios. Research results indicate that the proposed model and solution method enable a highway-traffic self-contained microgrid system without major grid support to achieve a renewable energy self-contained rate of 99.95% through the coordinated operation of batteries and hydrogen energy storage, while the abandonment rate of wind and solar energy is only 1.34%. It demonstrates that a appropriate storage configuration can effectively mitigate the intermittency and variability of wind and solar outputs, ensure adjustability and reliability of the microgrid's power supply, and provide decision supports for the planning and design of China's highway-traffic self-contained microgrid system. 5 tabs, 6 figs, 31 refs.
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图 1 公路交通自洽微网系统架构
Figure 1. Architecture of highway-traffic self-contained microgrid system
图 2 公路交通自洽微网系统求解流程
Figure 2. Solving flow of highway-traffic self-contained microgrid system
图 3 各场景下公路交通自洽微网系统基础输入数据
Figure 3. Basic input data of highway-traffic self-contained microgrid system in each scenario
图 4 场景1下自洽微网系统内各单元出力情况
Figure 4. Outputs of each unit in self-contained microgrid system in scenario 1
图 5 场景2下自洽微网系统内各单元出力情况
Figure 5. Outputs of each unit in self-contained microgrid system in scenario 2
图 6 场景3下自洽微网系统内各单元出力情况
Figure 6. Outputs of each unit in self-contained microgrid system in scenario 3
表 1 三种典型场景适配的公路交通自洽微网系统
Table 1. Highway-traffic self-contained microgrid systems adapted to three typical scenarios
场景 微网构成组分 自然资源 辅助供能 有无大电网连接 储能系统 1 风+光 无 无 蓄电池+氢储能 2 风+光 燃气轮机 无 蓄电池 3 风+光 无 有 蓄电池 
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表 2 设备参数
Table 2. Equipment parameters
设备名称 规格参数 投资成本/ (元·kW-1) 运维成本/ (元·kW-1) 寿命/年 风电机组 100 kW 11 000 0.02 20 光伏板 2 kW 8 500 0.01 20 燃气轮机 50 kW 16 000 0.09 20 蓄电池 4 kW 1 000 0.01 5 电解槽 1 kW 13 000 0.03 10 储氢罐 1 kW·h 1 800 0.00 20 燃料电池 1 kW 11 000 0.05 10
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表 3 燃气轮机污染物排放系数与治理费用
Table 3. Pollutant emission coefficients and treatment costs of gas turbine
污染物名称 排放系数/[g·(kW·h-1)] 治理费用/(元·kg-1) CO2 646.00 0.23 SO2 0.21 14.85
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表 4 三种场景下各系统优化配置结果
Table 4. Optimization configuration results of each system in three scenarios
场景 优化配置结果 风机/台 光伏板/片 燃气轮机/台 蓄电池/块 氢储能系统 电解槽/个 储氢罐/个 燃料电池/块 1 17 219 3 783 334 1 012 302 2 2 8 6 52 3 9 593 600
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表 5 三种场景下各系统相关指标计算结果
Table 5. Calculation results of relevant indicators of each system in three scenarios
场景 投资成本/元 年均成本/(元·年-1) 可再生能源自洽率/% 弃风弃光率/% 大电网交互/(元·年-1) 运维成本 惩罚成本 购电成本 售电收益 1 5 228 630 74 233 86.63 22.54 2 620 500 909 360 157 550 99.95 1.34 3 1 239 050 60 147 65.26 6.18 1 755 490 287 235
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