Optimal operation of hybrid energy system considering cold ironing based on model predictive control

被引：0

作者：

Wang W. ^{[1
]}

Zhang X. ^{[1
]}

Su S. ^{[1
]}

Li Z. ^{[1
]}

Wang Y. ^{[2
]}

Xia D. ^{[3
]}

Wang S. ^{[4
]}

机构：

[1] National Active Distribution Network Technology Research Center, Beijing Jiaotong University, Beijing

[2] State Grid Xinyuan Holdings Co., Ltd., Beijing

[3] Economic and Technological Research Institute of State Grid Tianjin Electric Power Company, Tianjin

[4] Haidian Electric Power Supply Company of State Grid Beijing Electric Power Company, Beijing

来源：

Dianli Zidonghua Shebei/Electric Power Automation Equipment | 2021年 / 41卷 / 11期

基金：

中国国家自然科学基金;

关键词：

Cold ironing; Hybrid energy system; Mixed-integer programming; Model predictive control; Rolling optimization;

D O I：

10.16081/j.epae.202107012

中图分类号：

学科分类号：

摘要：

An optimal operation approach is proposed for the hybrid energy system in the port. The system includes cold ironing, offshore wind turbine and energy storage. A hybrid energy system model is established, including load forecasting model, dynamic electricity price model, wind turbine model and energy storage model. Aiming at the problem of low accuracy of load prediction caused by the uncertainty in demands, a new approach is proposed to improve prediction accuracy, which uses wavelet packet decomposition for signal frequency division and selects different prediction approaches according to the characteristics of different frequency bands. In view of unclear electricity pricing mechanism for supply and sale, a model that sets the service fees increasing with the cold ironing power consumption and dynamically adjusting the electricity price according to demand level is proposed. This model balances the interests of the port, ship-owner and power grid. In view of the mixed-integer nonlinear programming problem caused by the introduction of integer variables, the MPC(Model Predictive Control) approach is used for rolling optimization, and CPLEX+YALMIP is employed to solve the problem, which reduces the error of the open-loop optimal control approach, and the optimization results that minimize the total operating cost of system are obtained. © 2021, Electric Power Automation Equipment Press. All right reserved.

引用

页码：17 / 24

页数：7

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