Assessment Method for the Construction Effect of Port Hybrid Renewable Energy Systems from a Near-Zero Carbon Perspective
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摘要: 在当前近零碳发展的要求下，港口作为海陆交汇的关键枢纽须积极承担起绿色低碳发展的责任，充分利用风能、太阳能等可再生能源，合理配置可再生能源系统规模，最大程度上实现港口的能源自洽。如何兼顾经济性与环保性，合理配置港口的综合可再生能源系统规模，在港口现阶段的建设中至关重要。论文以HOMER Pro作为搭建近零碳港口混合可再生能源系统的仿真工具，模拟实时的港口供耗电情况，并利用熵权TOPSIS方法建立评估模型，基于经济和环境指标分析和比较混合可再生能源系统建设方案。以江苏省沿江典型港口——J港为例，依据现场调研获得的风速、日辐射通量和环境温度等资源禀赋数据，基于HOMER Pro软件开展仿真分析，比较了单一光伏、单一风机与风光混合3种不同情景的系统建设方案，验证了模型的可行性。结果表明：J港在余电上网模式下，可再生能源系统3种情景下的综合最优建设规模分别为：7.8 MW光伏、5台3 MW风机以及6.2 MW光伏+15台3 MW风机；单一光伏建设起到的减排效果并不理想，仅能替代其19%的能源消耗，对电网的依赖程度大；单一风机建设可满足其40%的能耗需求，且经济和环境方面的表现均优于前者；风光混合方案能有效提高并网式系统在环境方面的表现，不仅能满足港口70%的能耗需求，亦能减少65% 的碳排放。Abstract: Under the current requirements of near-zero carbon emission goals, ports, as crucial sea-land hubs, must actively assume responsibility for green and low-carbon development. By fully utilizing renewable energy sources, such as wind and solar power, and rationally allocating the scale of renewable energy systems, ports can maximize their energy self-sufficiency. Balancing economic feasibility and environmental sustainability to reasonably configure the scale of integrated renewable energy systems is crucial for the current stage of port development. To address this challenge, this paper employs HOMER Pro as the simulation tool for constructing a near-zero carbon hybrid renewable energy system for ports, including real-time assessments of power supply and consumption. An evaluation model is established using the entropy-weighted TOPSIS method, analyzing and comparing construction scenarios of hybrid renewable energy systems based on economic and environmental indicators. Taking J port, a typical port along the Yangtze River in Jiangsu province, as an example, this study uses field survey data on resource endowments such as wind speed, daily radiation flux, and ambient temperature to conduct simulation analysis via HOMER Pro. The study compares three distinct scenarios: a standalone photovoltaic system, a standalone wind turbine system, and a wind-solar hybrid system, to validate the feasibility of the model. The results indicate the following optimal configurations for J Port under a surplus electricity grid connection mode: 7.8 MW photovoltaic panels, five 3 MW wind turbines, and a hybrid configuration of 6.2 MW photovoltaic panels with fifteen 3 MW wind turbines. Results show that the photovoltaic system demonstrates limited emission reduction potential, replacing only 19% of the port's energy consumption and exhibiting a high dependence on the national power grid. In contrast, the standalone wind turbine system satisfies 40% of the port's energy demand, outperforming the photovoltaics in both economic and environmental aspects. The wind-solar hybrid system further enhances the environmental performance of the grid-connected system, supporting 70% of the port's energy demand and achieving a 65% reduction in carbon emissions.
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图 1 近零碳港口可再生能源系统架构
Figure 1. Architectural framework for near-zero carbon port renewable energy systems
图 3 可再生能源系统建设方案综合评价模型
Figure 3. Comprehensive evaluation model for renewable energy system construction proposals
图 6 J港月平均辐射通量和净度指数
Figure 6. Monthly average radiation flux and clearness index at port J
图 11 情景1最优方案的实时购电量
Figure 11. Real-time purchased electricity quantity for optimal solution in scenario 1
图 12 情景2最优方案的实时购电量
Figure 12. Real-time purchased electricity quantity for optimal solution in scenario 2
图 13 情景3最优方案的实时购电量
Figure 13. Real-time purchased electricity quantity for optimal solution in scenario 3
图 14 售电价格对经济性指标的影响
Figure 14. The influence of sold electricity price on economic index
图 15 售电价格对环境性指标的影响
Figure 15. The influence of sold electricity price on environmental index
图 18 日辐射通量对经济性指标的影响
Figure 18. The influence of daily radiation flux on economic index
图 19 日辐射通量对环境性指标的影响
Figure 19. The influence of daily radiation flux on environmental index
表 1 可再生能源系统建模软件对比
Table 1. Comparison of renewable energy system modeling software
名称 开发者 主要构建 TRNSYS 威斯康星大学、科罗拉多大学 光伏板、风机、热能系统、发电机、储能系统 HYBRID2 美国国家可再生能源实验室 光伏板、风机、热能系统、发电机、储能系统 iHOGA 萨拉戈萨大学 光伏板、风机、水能、热能系统、发电机、储能系统 RETScreen 加拿大自然资源部 光伏板、风机、储能系统 SOMES 乌德勒支大学 光伏板、风机、生物质能、储能系统 SOLSTOR 桑迪亚国家实验室 光伏板、风机、发电机 HOMER Pro 美国国家可再生能源实验室 光伏板、风机、生物质能、水能、氢能、热能系统、发电机、储能系统 
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表 2 建设方案评价指标体系
Table 2. Evaluation index system for construction proposals
一级指标 二级指标 参数 近零碳港口可再生能源系统建设方案评价指标体系 环境 可再生能源发电比例RF/% 碳排放量CE/万t 经济 内部收益率IRR/% 贴现投资回收期DP/年 平准化度电成本LCOE/（元/kW·h）
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表 3 港口电力系统元件经济及技术参数
Table 3. Economic and technical parameters of power system components at the port
名称 连接方式 设计寿命 初始投资/元 重置成本/元 年维护成本/元 WT AC 20 $ 9600000 /$台 $ 7200000 /$台 $ 30000 /$台 PV DC 30 $ 3240 /\mathrm{kW} $ $ 3240 /\mathrm{kW} $ $ 54 /\mathrm{kW} $ 电网 AC $ \infty $ 0 0 0 变流器 $ \mathrm{AC} /\mathrm{DC} $ 20 $ 2100 /\mathrm{kW} $ $ 2100 /\mathrm{kW} $ $ 12 /\mathrm{kW} $
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表 4 单一光伏情景建设方案
Table 4. Construction plan for a single photovoltaic scenario
序号 PV/MW LCOE/（元/kW·h） IRR/% DP/年 CE/万t RF/% 1 4.7 0.554 15.2 8.07 3.42 11.3 2 5.3 0.57 15 8.18 3.38 12.5 3 6.5 0.55 14.3 8.65 3.31 14.1 4 7.8 0.545 13.8 9.1 3.28 15 5 8.7 0.549 12.6 9.99 3.23 16.3 6 10 0.551 11.5 11.03 3.19 17.3
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表 5 单一风机情景建设方案
Table 5. Construction plan for a single wind turbine scenario
序号 PV/MW LCOE/（元/kW·h） IRR/% DP/年 CE/万t RF/% 7 5 0.5304 14 8.95 2.94 24.2 8 10 0.4497 13 9.35 2.2 46 9 12 0.4175 12.7 9.53 1.98 53.2 10 14 0.39 12.3 9.87 1.78 59.6 11 15 0.377 12.1 10 1.69 62.4
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表 6 风光混合情景建设方案
Table 6. Construction plan for wind-solar hybrid scenario
序号 风机/台 光伏/MW LCOE/（元/kW·h） IRR/% DP/年 CE/万t RF/% 12 15 2 0.363 12 10.1 1.56 66.0 13 12 4 0.387 12.7 9.65 1.69 60.9 14 5 4.7 0.492 13.7 8.91 2.52 35.3 15 15 6.2 0.3369 12.1 10.06 1.36 71.1 16 10 7.3 0.4032 12.9 9.49 1.75 58.4 18 13 5.3 0.3666 12.5 9.74 1.54 65.4 19 14 7 0.354 12.1 10.13 1.43 68.9 20 14 9.5 0.3531 11.7 10.5 1.37 70.4 21 15 10 0.337 11.54 10.7 1.28 73.1
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表 7 不同情景下各指标的权重系数
Table 7. Weighting factors for various indicators under different scenarios
指标 光伏板情景 风机情景 组合情景 贴现投资回收期DP 18.61 25.25 20.17 平准化度电成本LCOE 15.07 15.62 16.87 内部收益率IRR 19.70 28.77 30.37 可再生能源发电比例RF 22.93 15.26 16.31 碳排放量CE 23.68 15.10 16.29
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表 8 不同情景下最优建设方案对比
Table 8. Comparison of optimal construction plans under different scenarios
指标 光伏板情景 风机情景 组合情景 贴现投资回收期$ \mathrm{DP} /$年 9.1 8.95 10.06 平准化度电成本$ \mathrm{LCOE} /( $元$ /\mathrm{kW} \cdot \mathrm{h}) $ 0.545 0.5304 0.3369 内部收益率$ \mathrm{IRR} /\% $ 13.8 14.0 12.1 可再生能源发电比例$ \mathrm{RF} /\%$ 15.0 24.2 71.1 碳排放量$ \mathrm{CE} /$万t 3.28 2.94 1.36
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表 9 不同情景下最优方案的售电量
Table 9. Electricity sales quantity for optimal solutions under different scenarios
月份 光能最优方案售电量/（kW·h 风能最优方案售电量/（kW·h） 风光组合最优方案售电量/（kW·h） 1 0 0 436601 2 0 0 440615 3 0 93821 2434985 4 0 61620 2213722 5 0 20060 1954815 6 0 0 395705 7 0 45562 803850 8 0 0 126681 9 0 0 75208 10 0 0 132390 11 207 728 500838 12 0 0 697805 合计 207 221791 10213214
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