Configuration optimization for transportation self-consistent energy system architectures under different operation modes
-
摘要: 为推进交通空间内的可再生能源利用，针对复杂多变的交通环境及工程建设运营条件，提出了4种运行模式及对应的交通自洽能源系统架构，并建立每种运行模式下的系统架构配置优化模型，使用改进非支配排序遗传算法对配置优化模型进行求解；结合案例对不同运行模式下的系统架构配置方案的影响因素进行分析，给出了不同运行模式下的系统架构配置方案性能特征及适应交通环境。研究结果表明：运行模式A的经济性和环保性最好，建设条件容易达到，但系统可靠性最差，无附加约束情况下模拟运行结果显示缺电概率为6.7%，低重要性负荷断电概率为23.23%；运行模式D的系统可靠性最佳，但对并网条件要求高，并网联络功率可达483.53 kW；模式B和C的特征较为均衡，可应用交通环境最多；不同优化目标的优化方向存在冲突，技术或环保性能指标每提高1%，经济投入都将增加数百万元；弃电率主要影响输出功率具有强烈波动的电源及储能的配置容量，本文案例中利用水电时弃电率超过40%；不同约束指标与优化目标之间联动影响，且根据不同约束要求的严格程度差异，存在约束遮盖现象。Abstract: In order to promote the utilization of renewable energy in transportation space, four operation modes and corresponding transportation self-consistent energy system architectures were proposed to adapt to the complex and changeable traffic environment and engineering construction and operation conditions. Configuration optimization models of system architectures were established under each operation mode, and the improved non-dominated sorting genetic algorithm was used to solve the configuration optimization models. Combined with case studies, the influencing factors of system architecture configuration schemes under different operation modes were analyzed, and the performance characteristics and adaptability of system architecture configuration schemes to the traffic environment under different operation modes were given. Research results show that operation mode A has the best economic and environmental protection performance, and it is easy to meet construction conditions, but the system reliability is the worst. The simulated operation results under no additional constraints show that the energy loss possibility is 6.7%, and the low-importance load power cut possibility is 23.23%. Operation mode D has the best system reliability, but it requires high grid connection conditions, with a grid connection power of up to 483.53 kW. The characteristics of modes B and C are more balanced and can be applied to most traffic environments. There are conflicts between the optimization directions of different optimization objectives. For every 1% increase in technical or environmental protection performance indicators, the economic investment will increase by millions. The power discard rate mainly affects the configuration capacity of power sources with strong fluctuation in output power and energy storage. In the case of this paper, when hydropower is used, the power discard rate exceeds 40%. There is a linkage effect between different constraint indicators and optimization objectives, and there is a constraint masking phenomenon based on the difference in the strictness of different constraint requirements.
-
图 1 不同运行模式下的交通自洽能源系统基础架构
Figure 1. Basic architectures of TSCES under different operation modes
图 8 不同自洽率约束下的种群优化目标标准差分布
Figure 8. Population optimization objectives standard deviation distributions under different self-consistent rate constraints
图 9 交通自洽能源系统架构配置方案成本分析
Figure 9. Cost analysis of TSCES architecture configuration scheme
图 10 不同运行模式下的系统架构性能特征
Figure 10. Performance characteristics of system architecture under different operation modes
表 1 典型可利用交通空间
Table 1. Typical utilizable transportation spaces
基础设施 可利用空间 可开发方式 服务区、收费站等服务管理设施 屋顶、棚顶 光伏 空地 储能、光伏、风力机 边坡及保护区 光伏、风力机、储能 中央分隔带 光伏、风力机、储能 道路边线 路侧风机、光伏声屏障 行车道及人行道 光伏廊道、压电 隧道出入口 中央分隔带 光伏 山坡 光伏、风力机 铁路车站 屋顶、棚顶 光伏 空地 储能、光伏、风力机 铁道轨道及路幅 轨间光伏、光伏廊道 边坡及保护区 光伏、风力机、储能 铁道边线 光伏声屏障 铁道沿线 铁道轨道及路幅 轨间光伏、光伏廊道 边坡及保护区 光伏、风力机、储能 铁道边线 光伏声屏障 码头 空地 储能 堆场及防波堤 风力机 其他 屋顶及停车棚 光伏 岸桥 光伏 堆场 风力机 河道 水轮机 
下载: 导出CSV
表 2 不同运行模式下的交通自洽能源系统架构配置优化目标及约束条件
Table 2. Configuring optimization objectives and constraint conditions for TSCES architecture under different operation modes
运行
模式离网 并网 运行模式A 运行模式B 运行模式C 运行模式D 优化
目标总净现值 总净现值 总净现值 总净现值 缺电概率 可再生能源自洽率 可再生能源自洽率 可再生能源自洽率 约束条件 系统功率平衡、设备输出功率、储能容量、设备装机数量 可再生能源弃电率临时断电概率可断电负荷比例 可再生能源弃电率 可再生能源弃电率缺电概率规律性电网停电时间 可再生能源上网售电率
下载: 导出CSV
表 3 服务区可利用空间
Table 3. Utilizable space in service area
可利用方式 空间属性 面积(长×宽×数量)/m2 最大安装数量 光伏板 边坡 100×15×4 1 200块 房屋及棚架顶 100×50×2 2 000块 停车棚 50×3×10 300块 风力机 停车区及行车道 100×100×2 8架 空地 50×25×2 1架 储能电柜 空地 50×25×2 166台 水轮机 附近河道 1处 1座
下载: 导出CSV
表 4 备用电源参数
Table 4. Parameters of backup power source
指标 数值 柴油电机单位装机成本/(元·W-1) 0.50 并网变压器单位装机成本/(元·W-1) 0.25 油价/(元·kg-1) 8.98 商业电价/[元·(kW·h)-1] 0.70 上网电价/[元·(kW·h)-1] 0.50 停电时间 14:00~17:00
下载: 导出CSV
表 5 电源及储能设施技术参数
Table 5. Technical parameters of power source and energy storage facilities
参数 光伏板 风力机 水轮机 储能电柜 额定参数 功率为540 W 功率为50 kW 功率为500 kW 容量为100 kW·h 建设成本 每块2 000元 每架20万元 每座400万元 每台16万元 年运营成本 每块24元 每架2 000元 每座10万元 每台60元 置换成本 每块270元 每架20万元 每座30万元 每台9万元 寿命/年 25 20 30 10 单位用地 5 m2 2 500 m2 间隔大于1 km 15 m2 技术参数 fp 0.9 vr/(m·s-1) 9 μ 0.9 S(t)/% 20~100 αp/(%·℃-1) -0.47 vmin/(m·s-1) 2 fh 0.9 σ/(%·h-1) 0.1 vmax/(m·s-1) 25 Qmin/(m3·s-1) 9 Pin/kW -40 Qmax/(m3·s-1) 33 Pout/kW 40 ηout、ηin 0.9
下载: 导出CSV
表 6 运行模式A下负荷临时断电概率影响
Table 6. Impacts of temporary power cut possibilities of load under operation mode A
临时断电概率/% 优化目标 性能指标 配置方案 储能电柜/台 总净现值/元 缺电概率/% 弃电率/% 光伏板/块 风力机/架 水轮机/座 10 45 196 251 12.53 1.58 3 441 9 0 166 20 30 829 112 12.60 2.83 3 493 9 0 98 30 21 641 841 14.04 5.33 3 481 9 0 55 40 14 521 055 16.85 9.70 3 441 9 0 22 50 11 799 345 19.81 9.56 2 994 9 0 14
下载: 导出CSV
表 7 运行模式A下可临时断电比例影响
Table 7. Impacts of temporary power cut ratio of load under operation mode A
断电比例/% 优化目标 性能指标 配置方案 总净现值/元 缺电概率/% 断电概率/% 弃电率/% 光伏板/块 风力机/架 水轮机/座 储能电柜/台 10 29 939 646 14.35 29.28 2.60 3 383 9 0 95 20 30 829 112 12.60 27.00 2.83 3 493 9 0 98 30 25 849 929 12.35 27.87 3.71 3 458 9 0 75 40 31 626 568 11.01 25.91 2.66 3 469 9 0 102 50 27 425 310 10.52 25.58 3.49 3 495 9 0 82
下载: 导出CSV
表 8 运行模式A下弃电率影响
Table 8. Impacts of power discard rate under operation mode A
弃电率/% 优化目标 性能指标 配置方案 总净现值/元 缺电概率/% 断电概率/% 光伏板/块 风力机/架 水轮机/座 储能电柜/台 10 30 829 112 12.60 27.04 3 493 9 0 98 40 18 291 606 2.20 8.14 2 237 9 1 28 70 12 562 911 3.54 13.50 1 592 9 1 8 100 10 219 357 5.97 17.01 1 9 1 14
下载: 导出CSV
表 9 可再生能源自洽率的影响
Table 9. Impacts of renewable energy self-consistent rate
自洽率/% 优化目标 性能指标 配置方案 总净现值/元 自洽率/% 弃电率/% 光伏板/块 风力机/架 水轮机/座 储能电柜/台 0 39 186 431 82.39 7.20 3 486 9 0 38 20 38 990 450 82.19 7.43 3 480 9 0 36 40 38 097 550 80.56 9.53 3 459 9 0 23 60 40 400 523 82.46 5.97 3 400 9 0 45 80 51 007 503 85.14 2.46 3 461 9 0 109 100 56 093 569 85.36 2.07 3 470 9 0 134
下载: 导出CSV
表 10 运行模式B下弃电率的影响
Table 10. Impacts of power discard rate under operation mode B
弃电率/% 优化目标 性能指标 配置方案 储能电柜/台 总净现值/元 自洽率/% 弃电率/% 光伏板/块 风力机/架 水轮机/座 10 51 007 503 85.14 2.46 3 461 9 0 109 40 45 343 804 83.79 3.28 3 355 9 0 76 70 23 591 463 97.81 61.72 3 399 9 1 27 100 24 999 007 98.02 61.52 3 383 9 1 35
下载: 导出CSV
表 11 运行模式C下弃电率的影响
Table 11. Impacts of power discard rate under operation mode C
弃电率/% 优化目标 性能指标 配置方案 总净现值/元 自洽率/% 缺电概率/% 弃电率/% 光伏板/块 风力机/架 水轮机/座 储能电柜/台 10 21 525 540 81.30 2.15 8.93 3 496 9 0 27 40 26 884 145 83.42 2.06 5.05 3 441 9 0 56 70 15 992 329 95.83 0.80 60.37 2 065 9 1 13 100 16 660 767 96.24 0.68 61.00 2 497 9 1 12 Ap=100%, Lp=100% 20 635 095 97.61 0.43 61.65 3 287 9 1 24
下载: 导出CSV
表 12 运行模式C下缺电概率的影响
Table 12. Impacts of energy loss possibility under operation mode C
缺电概率/% 优化目标 性能指标 配置方案 总净现值/元 自洽率/% 缺电概率/% 弃电率/% 光伏板/块 风力机/架 水轮机/座 储能电柜/台 0.0 44 662 555 99.17 0.17 60.21 3 492 9 1 137 2.5 27 885 053 83.94 1.99 4.77 3 479 9 0 61 5.0 21 525 540 81.30 2.15 8.93 3 496 9 0 27 7.5 20 458 325 80.15 2.31 9.89 3 440 9 0 21 10.0 21 175 572 81.04 2.19 9.29 3 495 9 0 25
下载: 导出CSV
表 13 运行模式D下售电率的影响
Table 13. Impacts of selling rate under operation mode D
售电率% 优化目标 性能指标 配置方案 总净现值/元 自洽率/% 售电率/% 光伏板/块 风力机/架 水轮机/座 储能电柜/台 10 31 360 074 84.60 3.48 3 462 9 0 79 40 -162 656 99.03 60.60 3 490 9 1 106 70 -18 607 577 97.50 61.84 3 352 9 1 21 100 -13 894 069 98.28 61.48 3 471 9 1 43 Ap=100%且无水电 20 088 179 80.96 8.92 3 456 9 0 26
下载: 导出CSV
表 14 无附加约束的交通自洽能源系统架构优化配置方案
Table 14. Optimal configuration scheme for TSCES architecture without additional constraints
运行模式 优化目标 配置方案 性能指标值 总净现值(优化目标1)/元 优化目标2 光伏板/块 风力机/架 水轮机/座 储能电柜/台 A 7 639 006 缺电概率为6.70% 84 9 1 1 Ap =59.06%，Rc=23.23% B 22 099 859 自洽率为97.28% 3 127 9 1 20 Ap=61.56% C 20 635 095 自洽率为97.61% 3 287 9 1 24 Ap =61.65%, Lp=0.43% D -13 679 741 自洽率为98.31% 3 477 9 1 44 Ap =61.47%
下载: 导出CSV
-
[1] 徐晓健, 杨瑞, 纪永波, 等. 氢燃料电池动力船舶关键技术综述[J]. 交通运输工程学报, 2022, 22(4): 47-67. doi: 10.19818/j.cnki.1671-1637.2022.04.004 XU Xiao-jian, YANG Rui, JI Yong-bo, et al. Review on key technologies of hydrogen fuel cell powered vessels[J]. Journal of Traffic and Transportation Engineering, 2022, 22(4): 47-67. (in Chinese) doi: 10.19818/j.cnki.1671-1637.2022.04.004 [2] OLADIMEJI D, GUPTA K, KOSE N A, et al. Smart transportation: an overview of technologies and applications[J]. Sensors, 2023, 23(8): 3880. doi: 10.3390/s23083880 [3] 李清, 孙玉伟, 吴健, 等. 船舶并网光伏电力系统稳定性[J]. 交通运输工程学报, 2021, 21(5): 177-188. doi: 10.19818/j.cnki.1671-1637.2021.05.015LI Qing, SUN Yu-wei, WU Jian, et al. Stability of ship grid-connected photovoltaic power system[J]. Journal of Traffic and Transportation Engineering, 2021, 21(5): 177-188. (in Chinese) doi: 10.19818/j.cnki.1671-1637.2021.05.015 [4] 胡田飞, 刘济华, 李天峰, 等. 铁路与新能源融合发展现状及展望[J]. 中国工程科学, 2023, 25(2): 122-132.HU Tian-fei, LIU Ji-hua, LI Tian-feng, et al. Current status and prospect of the integration of railway and new energy[J]. Strategic Study of CAE, 2023, 25(2): 122-132. (in Chinese) [5] 苏勇勇. 山西省太阳能资源评估及规划管理研究[D]. 太原: 山西财经大学, 2022.SU Yong-yong. Study on evaluation and planning management of solar energy resources in Shanxi province[D]. Taiyuan: Shanxi University of Finance and Economics, 2022. (in Chinese) [6] 陈维荣, 王璇, 李奇, 等. 光伏电站接入轨道交通牵引供电系统发展现状综述[J]. 电网技术, 2019, 43(10): 3663-3670.CHEN Wei-rong, WANG Xuan, LI Qi, et al. Review on the development status of PV power station aceessing to traction power supply system for rail transit[J]. Power System Technology, 2019, 43(10): 3663-3670. (in Chinese) [7] CHEN Zhu-jun, JIANG Ming-kun, QI Ling-fei, et al. Using existing infrastructures of high-speed railways for photovoltaic electricity generation[J]. Resources Conservation and Recycling, 2022, 178: 106091. doi: 10.1016/j.resconrec.2021.106091 [8] 刘豪, 张高峰, 周帅, 等. 高速公路"低碳"服务区建设规划中的能效管理浅析[J]. 交通节能与环保, 2023, 19(1): 110-113.LIU Hao, ZHANG Gao-feng, ZHOU Shuai, et al. Analysis of energy efficiency management in the construction planning of expressway "low carbon" service area[J]. Transport Energy Conservation and Environmental Protection, 2023, 19(1): 110-113. (in Chinese) [9] DAI Liang, ZHANG Cheng-yin, YUN Huang, et al. Feasibility analysis of supply-demand matching between highway operational energy consumption and renewable energy integration: a case study of panzhihua-dali highway withinSichuan province[C]//IEEE. 58th IEEE/IAS Industrial and Commercial Power Systems Technical Conference Asia. New York: IEEE, 2022: 1989-1993. [10] WADI M, SHOBOLE A, TUR M R, et al. Smart hybrid wind-solar street lighting system fuzzy based approach: case study Istanbul-Turkey[C]//IEEE. 6th International Istanbul Smart Grids and Cities Congress and Fair. New York: IEEE, 2018: 71-75. [11] SONG Jing, SHAN Qi-he, ZOU Tao, et al. Distributed energy management for zero-carbon port microgrid[J]. International Transactions on Electrical Energy Systems, 2022, DOI: 10.1155/2022/2752802. [12] RAHMAN M A, MUKTA M Y, ASYHARI A T, et al. Renewable energy re-distribution via multiscale IOT for 6G-oriented green highway management[J]. IEEE Transactions on Intelligent Transportation Systems, 2022, 23(12): 23771-23780. doi: 10.1109/TITS.2022.3203208 [13] 刘栋晨, 季昱, 胡岳. 交能融合V2G技术研究与实践综述[J/OL]. 上海交通大学学报, 2023, https://link.cnki.net/urlid/31.1466.U.20231103.1552.004 .LIU Dong-chen, JI Yu, HU Yue. Summary of the research and practice on V2G technology of transportation and energy fusion[J/OL]. Journal of Shanghai Jiao Tong University, 2023,https://link.cnki.net/urlid/31.1466.U.20231103.1552.004 . (in Chinese)[14] 李艳波, 李若尘, 史博, 等. 基于改进模拟退火遗传算法的高速公路服务区自洽能源系统高能效优化[J]. 西安交通大学学报, 2024, 58(1): 197-207, 216. doi: 10.7652/xjtuxb202401019LI Yan-bo, LI Ruo-chen, SHI Bo, et al. High energy efficiency optimization of self-consistent energy system in highway service area based on SA-GA[J]. Journal of Xi'an Jiaotong University, 2024, 58(1): 197-207, 216. (in Chinese) doi: 10.7652/xjtuxb202401019 [15] 李进, 蔡泽祥, 岑伯维, 等. 基于功率能量特性的含小水电微电网储能容量配置方法[J]. 电力建设, 2024, 45(4): 123-133.LI Jin, CAI Ze-xiang, CEN Bo-wei, et al. Energy storage capacity configuration method for microgrids containing small hydropower based on power-energy characteristics[J]. Electric Power Construction, 2024, 45(4): 123-133. (in Chinese) [16] ZHANG Jun-li, WEI Hua-shuai. A review on configuration optimization of hybrid energy system based on renewable energy[J]. Frontiers in Energy Research, 2022, DOI: 10.3389/fenrg.2022.977925. [17] THIRUNAVUKKARASU M, SAWLE Y, LALA H. A comprehensive review on optimization of hybrid renewable energy systems using various optimization techniques[J]. Renewable and Sustainable Energy Reviews, 2023, 176: 113192. doi: 10.1016/j.rser.2023.113192 [18] PAMUK N. Techno-economic feasibility analysis of grid configuration sizing for hybrid renewable energy system in Turkey using different optimization techniques[J]. Ain Shams Engineering Journal, 2024, 15(3): 102474. doi: 10.1016/j.asej.2023.102474 [19] 邢鹏翔, 张世泽, 曾梦迪, 等. 多能源混合微网容量优化配置研究综述[J]. 武汉大学学报(工学版), 2017, 50(3): 375-383.XING Peng-xiang, ZHANG Shi-ze, ZENG Meng-di, et al. Review of configuration optimization for hybrid microgrid with multiple energy resources[J]. Engineering Journal of Wuhan University, 2017, 50(3): 375-383. (in Chinese) [20] 刘宇翔, 陈艳波, 田昊欣, 等. 基于两阶段鲁棒优化的轨道交通自洽能源系统新能源-储能规划配置[J/OL]. 高电压技术, 2023, DOI: 10.13336/j.1003-6520.hve.20231304 LIU Yu-xiang, CHEN Yan-bo, TIAN Hao-xin, et al. New energy and energy storage planning and configuration in rail transportation self-sufficient energy systems based on two-stage robust optimization[J/OL]. High Voltage Engineering, 2023, DOI:10.13336/j.1003-6520.hve.20231304(inChinese) [21] 师瑞峰, 宁津, 高毓钦, 等. 含氢储能的公路交通风、光自洽微网系统优化调度策略研究[J]. 太阳能学报, 2023, 44(11): 513-521.SHI Rui-feng, NING Jin, GAO Yu-qin, et al. Research on optimal dispatch strategy of wind and solar self-consistent microgrid in road transportation system with hydrogen energy storage[J]. Acta Energiae Solaris Sinica, 2023, 44(11): 513-521. (in Chinese) [22] 高毓钦. 含氢储能的公路交通自洽能源系统规划设计方法研究[D]. 北京: 华北电力大学, 2023.GAO Yu-qin. Research on the planning and design method of highway self-consistent energy system with hydrogen storage[D]. Beijing: North China Electric Power University, 2023. (in Chinese) [23] ZHOU Xiao-jun, TAN Wan, SUN Yan, et al. Multi-objective optimization and decision making for integrated energy system using STA and fuzzy TOPSIS[J]. Expert Systems with Applications, 2024, 240: 122539. doi: 10.1016/j.eswa.2023.122539 [24] LI Lei, LIU Wei-dong, LI Dan, et al. Planning method for charging piles of intelligent networked electric vehicles in consideration of charging safety[J]. Journal of Physics: Conference Series, 2021, 1754: 012098. doi: 10.1088/1742-6596/1754/1/012098 [25] KOOHI-FAYEGH S, ROSEN M A. A review of energy storage types, applications and recent developments[J]. Journal of Energy Storage, 2020, DOI: 10.1016/j.est.2019.101047. [26] 成润婷, 张勇军, 李立浧, 等. 碳边境调节机制下近零碳制造体系建设研究[J]. 中国工程科学, 2024, 26(1): 68-79.CHENG Run-ting, ZHANG Yong-jun, LI Li-cheng, et al. Construction of near-zero-carbon manufacturing system under the carbon border adjustment mechanism[J]. Strategic Study of CAE, 2024, 26(1): 68-79. (in Chinese) [27] JAHANNOOSH M, NOWDEH S A, NADERIPOUR A, et al. New hybrid meta-heuristic algorithm for reliable and cost-effective designing of photovoltaic/wind/fuel cell energy system considering load interruption probability[J]. Journal of Cleaner Production, 2021, 278: 123406. doi: 10.1016/j.jclepro.2020.123406 [28] JING Zhao-xia, LUO Zi-ya. An IGDT model for capacity configuration optimization of island microgrid[J]. Energy Procedia, 2019, 158: 2774-2779. doi: 10.1016/j.egypro.2019.02.037 [29] DONG Xiao-jian, SHEN Jia-ni, LIU Cheng-wu, et al. Simultaneous capacity configuration and scheduling optimization of an integrated electrical vehicle charging station with photovoltaic and battery energy storage system[J]. Energy, 2024, 289: 129991. doi: 10.1016/j.energy.2023.129991 [30] ZHANG Yu-sheng, MA Chao, YANG Yang, et al. Capacity configuration and economic evaluation of a power system integrating hydropower, solar, and wind[J]. Energy, 2022, 259: 125012. doi: 10.1016/j.energy.2022.125012 [31] ADEFARATI T, BANSAL R C. Integration of renewable distributed generators into the distribution system: a review[J]. IET Renewable Power Generation, 2016, 10(7): 873-884. doi: 10.1049/iet-rpg.2015.0378 [32] SIDDAIAH R, SAINI R P. A review on planning, configurations, modeling and optimization techniques of hybrid renewable energy systems for off grid applications[J]. Renewable and Sustainable Energy Reviews, 2016, 58: 376-396. doi: 10.1016/j.rser.2015.12.281 [33] MAHMOUDIMEHR J, SHABANI M. Optimal design of hybrid photovoltaic-hydroelectric standalone energy system for north and south of Iran[J]. Renewable Energy, 2018, 115: 238-251. doi: 10.1016/j.renene.2017.08.054 [34] SANAJAOBA S. Optimal sizing of off-grid hybrid energy system based on minimum cost of energy and reliability criteria using firefly algorithm[J]. Solar Energy, 2019, 188: 655-666. doi: 10.1016/j.solener.2019.06.049 [35] 赵波, 包侃侃, 徐志成, 等. 考虑需求侧响应的光储并网型微电网优化配置[J]. 中国电机工程学报, 2015, 35(21): 5465-5474.ZHAO Bo, BAO Kan-kan, XU Zhi-cheng, et al. Optimal sizing for grid-connected PV-and-storage microgrid considering demand response[J]. Proceedings of the CSEE, 2015, 35(21): 5465-5474. (in Chinese) [36] 金强, 张红斌, 宋子洋, 等. 微电网规划方案的评价指标计算和空间距离评价方法[J]. 燕山大学学报, 2021, 45(3): 246-253, 261.JIN Qiang, ZHANG Hong-bin, SONG Zi-yang, et al. Index calculation and space distance based evaluation for microgrid planning[J]. Journal of Yanshan University, 2021, 45(3): 246-253, 261. (in Chinese) [37] MENNITI D, PINNARELLI A, SORRENTINO N. A method to improve microgrid reliability by optimal sizing PV/wind plants and storage systems[C]//IEEE. The 20th International Conference and Exhibition on Electricity Distribution. New York: IEEE, 2009: 1-1. [38] 王浩, 文习波, 汤浩. 官地水电站水轮机效率试验研究[J]. 人民长江, 2015, 46(18): 86-88, 96.WANG Hao, WEN Xi-bo, TANG Hao. Efficiency test of hydraulic turbine in Guandi Hydropower Station[J]. Yangtze River, 2015, 46(18): 86-88, 96. (in Chinese) [39] 李雅菲. 微网分布式电源优化配置研究[D]. 北京: 华北电力大学, 2015.LI Ya-fei. Research on the optimal allocation of distributed generations in micro-grid[D]. Beijing: North China Electric Power University, 2015. (in Chinese) [40] 谭兴国, 王辉, 张黎, 等. 微电网复合储能多目标优化配置方法及评价指标[J]. 电力系统自动化, 2014, 38(8): 7-14.TAN Xing-guo, WANG Hui, ZHANG Li, et al. Multi-objective optimization of hybrid energy storage and assessment indices in microgrid[J]. Automation of Electric Power Systems, 2014, 38(8): 7-14. (in Chinese) [41] LU Zhi-ming, GAO Yan, XU Chuan-bo, et al. Configuration optimization of an off-grid multi-energy microgrid based on modified NSGA-Ⅱ and order relation-todim considering uncertainties of renewable energy and load[J]. Journal of Cleaner Production, 2023, 383: 135312. doi: 10.1016/j.jclepro.2022.135312 [42] 盛万兴, 叶学顺, 刘科研, 等. 基于NSGA-Ⅱ算法的分布式电源与微电网分组优化配置[J]. 中国电机工程学报, 2015, 35(18): 4655-4662.SHENG Wan-xing, YE Xue-shun, LIU Ke-yan, et al. Optimalallocation between distributed generations and microgrid based on NSGA-Ⅱ algorithm[J]. Proceedings of the CSEE, 2015, 35(18): 4655-4662. (in Chinese) [43] 王瑞琪, 李珂, 张承慧. 基于混沌多目标遗传算法的微网系统容量优化[J]. 电力系统保护与控制, 2011, 39(22): 16-22.WANG Rui-qi, LI Ke, ZHANG Cheng-hui. Optimization allocation of microgrid capacity based on chaotic multi-objective genetic algorithm[J]. Power System Protection and Control, 2011, 39(22): 16-22. (in Chinese) [44] 陈志刚, 梁涤青, 邓小鸿, 等. Logistic混沌映射性能分析与改进[J]. 电子与信息学报, 2016, 38(6): 1547-1551.CHEN Zhi-gang, LIANG Di-qing, DENG Xiao-hong, et al. Performance analysis and improvement of logistic chaotic mapping[J]. Journal of Electronics and Information Technology, 2016, 38(6): 1547-1551. (in Chinese) [45] 郑凌蔚, 刘士荣, 周文君, 等. 并网型可再生能源发电系统容量配置与优化[J]. 电力系统保护与控制, 2014, 42: 31-37.ZHENG Ling-wei, LIU Shi-rong, ZHOU Wen-jun, et al. Capacity configuration and optimization of grid-connected renewable energy power generation system[J]. Power System Protection and Control, 2014, 42: 31-37. (in Chinese) [46] ZEBRA E I C, VAN D W H J, NHUMAIO G, et al. A review of hybrid renewable energy systems in mini-grids for off-grid electrification in developing countries[J]. Renewable and Sustainable Energy Reviews, 2021, 144: 111036. [47] ZAKERI B, SYRI S. Electrical energy storage systems: a comparative life cycle cost analysis[J]. Renewable and Sustainable Energy Reviews, 2015, 42: 569-596. -
点击查看大图
图(10) / 表(14)
计量
- 文章访问数: 15
- HTML全文浏览量: 6
- PDF下载量: 2
- 被引次数: 0
