|Table of Contents|

Evaluation of supply and demand fitness for highway self-consistent energy systems based on sequential Monte-Carlo(PDF)

长安大学学报（自然科学版）[ISSN:1006-6977/CN:61-1281/TN]

Issue:
2024年5期
Page:
71-88
Research Field:
交通能源融合技术专题
Publishing date:

Info

Title:
Evaluation of supply and demand fitness for highway self-consistent energy systems based on sequential Monte-Carlo
Author(s):
NING Jin;  FENG Zhang-jie;  JI Wen-tong;  YE Xiao-rong;  HUANG Xian
(School of Control and Computer Engineering, North China Electric Power University, Beijing 102206, China)
Keywords:
traffic engineering;  highway self-consistent energy systems;  sequential Monte-Carlo;  multiple microgrids;  fitness;  integrated system evaluation
PACS:
U491.54
DOI:
10.19721/j.cnki.1671-8879.2024.05.007
Abstract:
In order to address the fitness of non-carbon-based energy generation for supplying electricity to highway loads(including service areas, tunnels, bridges, toll stations, etc.), a highway self-consistent energy systems fitness index system was constructed, which includes 10 indexes including self-consistency rate, power supply reliability rate, and frequency of power shortage, etc. Secondly, the wind and light scenarios were generated based on Monte-Carlo simulation, and the wind-optical-storage model was established. Secondly, the uncertainty of both supply and demand sides of the system was fully considered, and the wind and light scenarios were generated based on Monte-Carlo simulation, and the wind-photovoltaic-storage power generation model, the time-varying reliability model of the components taking into account the factors of climate change and the time of commissioning, and the multi-microgrid operation and control strategy including the scheduling of the storage system and the interconnection between the sub-microgrids were established in turn, and the quantitative assessment method of the fitness indexes was established by the application of the sequential Monte-Carlo method. The method of quantitative assessment of the fitness indexes was applied by sequential Monte-Carlo method. Then, five indicators in the fitness index system, such as self-consistency rate, power supply reliability rate, and power shortage frequency, were selected as the main basis for rating, and a comprehensive rating method for fitness was established based on the hierarchical analysis method. Finally, arithmetic simulations were carried out to analyze the impact of different inter-microgrid power interconnection constraints and reliability models on the results of the system's fitness index assessment based on different wind-photovoltaic-storage equipment configuration schemes. The results show that the power interconnection between microgrids can effectively improve the overall system fitness, and when the interconnection constraint is set to 20% of the maximum sub-microgrid load, compared with the independent sub-microgrids without interconnection, the system self-consistency index improves by about 3% to 25%, the power supply reliability index improves by about 4% to 23%, and the fitness evaluation results improve by zero to two grades.17 tabs, 16 figs, 35 refs.

References:

[1] GB/T 2900.103—2020,电工术语:发电、输电及配电电力系统可信性及服务质量[S].
GB/T 2900.103—2020,Electrotechnical terminology-Generation,transmission and distribution of electrical energy-Dependability and quality of service of electric power systems[S].
[2]DL/T 5542—2020,配电网规划设计规程[S].
DL/T 5542—2020,Distribution network planning and design regulations[S].
[3]IEEE Std 1366—2003,IEEE guide for electric power distribution reliability[S].
[4]T/CECS G:D85-08—2021,公路直流供电系统设计标准[S].
T/CECS G:D85-08-2021,Highway DC power supply system design standard[S].
[5]TB 10621—2014,高速铁路设计规范[S].
TB 10621—2014,Code for design of high speed railway[S].
[6]GB/Z 32880.2—2016,电能质量经济性评估 第2部分:公用配电网的经济性评估方法[S].
GB/Z 32880.2—2016.Economic assessment of power quality-Part 2:Methods for economic assessment of public distribution networks[S].
[7]NIKKHAH M H,LOTFI H,SAMADI M,et al.Optimal allocation of transmission fixed costs to electric vehicle charging stations and wind farms using an analytical method and structural decomposition[J].Sustainable Energy,Grids and Networks,2023,34:101061.
[8]JO S T,KIM W H,LEE Y K,et al.Multi-objective optimal design of SPMSM for electric compressor using analytical method and NSGA-Ⅱ algorithm[J].Energies,2022,15(20):7510-7525.
[9]LIU X,CAO Z J,LI D Q,et al.Adaptive Monte Carlo simulation method and its applications to reliability analysis of series systems with a large number of components[J].Journal of Risk and Uncertainty in Engineering Systems,Part A:Civil Engineering,2022,8(1):1-17.
[10]胡晓静.含柔性直流的交直流混合电网运行风险评估方法研究[D].北京:中国电力科学研究院,2018.
HU Xiao-jing.Research on operation risk assessment method for hybrid AC/DC power system with the VSC station[D].Beijing:China Electric Power Research Institute,2018.
[11]SUN X,LIU Y L,DENG L C.Reliability assessment of cyber-physical distribution network based on the fault tree[J].Renewable Energy,2020,155:1411-1424.
[12]陈 铮,陈 武,马建军.适用于直流配电网的组合电容型直流负荷开关[J].电力工程技术,2022,41(5):124-130.
CHEN Zheng,CHEN Wu,MA Jian-jun.Assembly DC load switch based on pre-charged capacitors suitable for DC distribution network[J].Electric Power Engineering Technology,2022,41(5):124-130.
[13]QUILES-CUCARELLA E,MARQUINA-TAJUELO A,ROLDAN-BLAY C,et al.Particle swarm optimization method for stand-alone photovoltaic system reliability and cost evaluation based on Monte Carlo simulation[J].Applied Sciences,2023,13(21):11623.
[14]CARVALHO J H,SCHWARTZ U B,BORGES C L T.Copula based model for representation of hybrid power plants in non-sequential Monte Carlo reliability evaluation[J].Sustainable Energy,Grids and Networks,2023,35:101077.
[15]GUIMARÃES I O,LEITE DA S A M,NASCIMENTO L C,et al.Reliability assessment of distribution grids with DG via quasi-sequential Monte Carlo simulation[J].Electric Power Systems Research,2024,229:110-122.
[16]LIU W X,GUO D P,XU Y H,et al.Reliability assessment of power systems with photovoltaic power stations based on intelligent state space reduction and pseudo-sequential Monte Carlo simulation[J].Energies,2018,11(6):1419-1431.
[17]GUO J,LIU W X,SYED F R,et al.Reliability assessment of a cyber physical microgrid system in island mode[J].CSEE Journal of Power and Energy Systems,2019,5(1):46-55.
[18]GHOLAMI M,MUYEEN S M,MOUSAVI S A.Development of new reliability metrics for microgrids:Integrating renewable energy sources and battery energy storage system[J].Energy Reports,2023,10:2251-2259.
[19]SAI K R,SURESH R S.A mixed integer optimization model for reliability indices enhancement in micro-grid system with renewable generation and energy storage[J].Materials Today:Proceedings,2023,80:2937-2944.
[20]ALAVI O,KAAYA I,DE JONG R,et al.Assessing the impact of PV panel climate-based degradation rates on inverter reliability in grid-connected solar energy systems[J].Heliyon,2024,10(3):e25839.
[21]NGO D V,LIM J K,KIM D H.Reliability analysis and life prediction of aging LNG unloading arms based on non-destructive test data[J].Energies,2022,15(24):9408.
[22]CHEN J,YU Z H,CHEN G Y,et al.Calculation of carbon emission during expressway operation period based on energy consumption analysis[J].IOP Conference Series:Earth and Environmental Science,2021,647(1):012190.
[23]PELOSI D,LONGO M,BIDINI G,et al.A new concept of highways infrastructure integrating energy storage devices for e-mobility transition[J].Journal of Energy Storage,2023,65:107364.
[24]贾利民,师瑞峰,吉 莉,等.我国道路交通与能源融合发展战略研究[J].中国工程科学,2022,24(3):163-172.
JIA Li-min,SHI Rui-feng,JI Li,et al.Road transportation and energy integration strategy in China[J].Strategic Study of CAE,2022,24(3):163-172.
[25]SHIPP A J,JANSEN K J.Reinterpreting time in fit theory:Crafting and recrafting narratives of fit in medias res[J].Academy of Management Review,2011,36(1):76-101.
[26]HAN F C,LI X,SHI W,et al.Generic fully coupled framework for reliability assessment of offshore wind turbines under typical limit states[J].Engineering Structures,2024,304:117692.
[27]ABBES D,MARTINEZ A,CHAMPENOIS G.Life cycle cost,embodied energy and loss of power supply probability for the optimal design of hybrid power systems[J].Mathematics and Computers in Simulation,2014,98:46-62.
[28]ZHANG J M,LIU J,CHEN L,et al.Reliability evaluation of high permeability renewable energy distribution network considering energy storage charge and discharge strategy[J].Energy Reports,2023,9:361-368.
[29]LIU Q M,DONG M,PENG Y.A novel method for online health prognosis of equipment based on hidden semi-Markov model using sequential Monte Carlo methods[J].Mechanical Systems and Signal Processing,2012,32:331-348.
[30]RAHMAT M K,JOVANOVIC S,LO K L.Reliability and availability modelling of uninterruptible power supply systems using Monte-Carlo simulation[J].International Journal on Energy Conversion,2017,5(2):60.
[31]王海巍.考虑不确定性的配电网可靠性研究[D].北京:华北电力大学,2011.
WANG Hai-wei.Reliability evaluation of distribution systems considering uncertainty[D].Beijing:North China Electric Power University,2011.
[32]ODAT A S,ALZOUBI O,SHBOUL B,et al.Dynamic and adaptive maximum power point tracking using sequential Monte Carlo algorithm for photovoltaic system[J].Arabian Journal for Science and Engineering,2023,48(11):15063-15083.
[33]ZHANG S F,YU X L,MAO H J,et al.Evaluating expressway safety based on fuzzy comprehensive evaluation with AHP-entropy method:A case study of Jinliwen Expressway in Zhejiang Province,China[J].Systems,2023,11(10):496.
[34]MITROFANOV A N,GARANIN M A,OKLADOV S A.Construction of digital-twin models of electrical infrastructure of railways to assess the resource of load capacity[J].Russian Electrical Engineering,2023,94(10):699-703.
[35]孙光辉,沈国荣.加强三道防线建设确保电网的安全稳定运行(摘要)[J].电力安全技术,2004,6(7):9.
SUN Guang-hui,SHEN Guo-rong.Strengthening the construction of three defense lines to ensure the safe and stable operation of power grid(abstract)[J].Electric Safety Technology,2004,6(7):9.

Memo

Memo:
-
Last Update: 2024-10-20