|Table of Contents|

Planning of highway self-consistent energy system based on chance-constrained programming(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:
36-46
Research Field:
交通能源融合技术专题
Publishing date:

Info

Title:
Planning of highway self-consistent energy system based on chance-constrained programming
Author(s):
HUANG Xian;  JI Wen-tong;  YE Xiao-rong;  FENG Zhang-jie
(School of Control and Computer Engineering, North China Electric Power University, Beijing 102206, China)
Keywords:
traffic engineering;  highway self-consistent energy system;  chance-constrained programming;  multi-microgrid;  configuration planning
PACS:
U417.9
DOI:
10.19721/j.cnki.1671-8879.2024.05.004
Abstract:
To address the power supply issues of traffic infrastructure such as tunnels, toll stations, and service areas on highways, and in order to fully consider the impact of wind and solar uncertainty on the reliability of the power supply system, the Weibull and Beta probability density distribution parameters were fitted based on historical data of wind speed and solar radiation intensity. Monte Carlo simulation technique and backward reduction method were used to generate wind and solar scenario sets. An operation control strategy that integrates load shedding, energy storage charging and discharging, and operation control strategy for mutual support between multiple microgrids was proposed. These strategies were embedded in the subsequent optimization configuration model. Furthermore, an optimization configuration model based on scenario sets and stochastic chance constraints for the self-consistent energy system of multiple microgrids was established, with the minimization of the total life cycle cost as the optimization objective, and constraints including installed capacity, power balance between supply and demand, loss of load probability. A multi-population genetic algorithm was used to solve the optimization configuration model. Through case study simulations, the effects of random expected value planning, chance-constrained planning, and five confidence levels(60%, 70%, 80%, 90%, 100%)of chance constraints on the optimized configuration capacity, cost, and power supply reliability of wind-solar-storage were analyzed through case simulation. The results show that the application scenarios corresponding to the wind-solar resources and load intensity of the two typical sub-microgrids, chance-constrained planning required higher power supply reliability than expected value planning. The robustness requirement of the system could be changed by adjusting the confidence level β of chance constraints, which was more flexible and feasible. The higher the confidence level β was set, the higher the power supply reliability would be, but the total cost would also increase correspondingly, especially when β exceeded 90%, the cost growth rate significantly increased, showed a clear inflection point.4 tabs, 7 figs, 25 refs.

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Last Update: 2024-10-20