A Dual-Layer MPC of Coordinated Control of Battery Load Demand and Grid-Side Supply Matching at Electric Vehicle Swapping Stations

The uncontrolled charging of electric vehicles may cause damage to the electrical system as the number of electric vehicles continues to rise. This paper aims to construct a new model of the power system and investigates the rational regulation and efficient control of electric vehicle battery charg...

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Main Authors: Minan Tang, Chenchen Zhang, Yaqi Zhang, Yaguang Yan, Wenjuan Wang, Bo An
Format: Article
Language:English
Published: MDPI AG 2024-02-01
Series:Energies
Subjects:
Online Access:https://www.mdpi.com/1996-1073/17/4/879
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author Minan Tang
Chenchen Zhang
Yaqi Zhang
Yaguang Yan
Wenjuan Wang
Bo An
author_facet Minan Tang
Chenchen Zhang
Yaqi Zhang
Yaguang Yan
Wenjuan Wang
Bo An
author_sort Minan Tang
collection DOAJ
description The uncontrolled charging of electric vehicles may cause damage to the electrical system as the number of electric vehicles continues to rise. This paper aims to construct a new model of the power system and investigates the rational regulation and efficient control of electric vehicle battery charging at electric vehicle exchange battery stations in response to the real-time grid-side supply situation. Firstly, a multi-objective optimization strategy is established to meet the day-ahead forecasted swap demand and grid-side supply with the maximization of day-ahead electric vehicle battery swapping station (BSS) revenue in the core. Secondly, considering the variable tariff strategy, a two-layer Model Predictive Control (MPC) coordinated control system under real-time conditions is constructed with the objective function of maximizing the revenue of BSS and smoothing the load fluctuation of the power system. Then, the day-ahead optimization results are adopted as the reference value for in-day rolling optimization, and the reference value for in-day optimization is dynamically adjusted according to the real-time number of electric car changes and power system demand. Finally, verified by experimental simulation, the results show that the day-ahead-intraday optimization model can increase the economic benefits of BSS and reduce the pressure on the grid to a certain extent, and it can ensure the fast, accurate, and reasonable allocation of batteries in BSS, and realize the flexible, efficient, and reasonable distribution of batteries in BSS.
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spelling doaj.art-551890f1dedc489296c64560ab9eb9302024-02-23T15:15:20ZengMDPI AGEnergies1996-10732024-02-0117487910.3390/en17040879A Dual-Layer MPC of Coordinated Control of Battery Load Demand and Grid-Side Supply Matching at Electric Vehicle Swapping StationsMinan Tang0Chenchen Zhang1Yaqi Zhang2Yaguang Yan3Wenjuan Wang4Bo An5College of New Energy and Power Engineering, Lanzhou Jiaotong University, Lanzhou 730070, ChinaCollege of New Energy and Power Engineering, Lanzhou Jiaotong University, Lanzhou 730070, ChinaCollege of Electrical and Mechanical Engineering, Lanzhou Jiaotong University, Lanzhou 730070, ChinaCollege of Electrical and Mechanical Engineering, Lanzhou Jiaotong University, Lanzhou 730070, ChinaCollege of New Energy and Power Engineering, Lanzhou Jiaotong University, Lanzhou 730070, ChinaCollege of Electrical and Mechanical Engineering, Lanzhou Jiaotong University, Lanzhou 730070, ChinaThe uncontrolled charging of electric vehicles may cause damage to the electrical system as the number of electric vehicles continues to rise. This paper aims to construct a new model of the power system and investigates the rational regulation and efficient control of electric vehicle battery charging at electric vehicle exchange battery stations in response to the real-time grid-side supply situation. Firstly, a multi-objective optimization strategy is established to meet the day-ahead forecasted swap demand and grid-side supply with the maximization of day-ahead electric vehicle battery swapping station (BSS) revenue in the core. Secondly, considering the variable tariff strategy, a two-layer Model Predictive Control (MPC) coordinated control system under real-time conditions is constructed with the objective function of maximizing the revenue of BSS and smoothing the load fluctuation of the power system. Then, the day-ahead optimization results are adopted as the reference value for in-day rolling optimization, and the reference value for in-day optimization is dynamically adjusted according to the real-time number of electric car changes and power system demand. Finally, verified by experimental simulation, the results show that the day-ahead-intraday optimization model can increase the economic benefits of BSS and reduce the pressure on the grid to a certain extent, and it can ensure the fast, accurate, and reasonable allocation of batteries in BSS, and realize the flexible, efficient, and reasonable distribution of batteries in BSS.https://www.mdpi.com/1996-1073/17/4/879electric vehiclesbattery swapping stationmodel predictive controlmulti-stage optimizationpeak shaving
spellingShingle Minan Tang
Chenchen Zhang
Yaqi Zhang
Yaguang Yan
Wenjuan Wang
Bo An
A Dual-Layer MPC of Coordinated Control of Battery Load Demand and Grid-Side Supply Matching at Electric Vehicle Swapping Stations
Energies
electric vehicles
battery swapping station
model predictive control
multi-stage optimization
peak shaving
title A Dual-Layer MPC of Coordinated Control of Battery Load Demand and Grid-Side Supply Matching at Electric Vehicle Swapping Stations
title_full A Dual-Layer MPC of Coordinated Control of Battery Load Demand and Grid-Side Supply Matching at Electric Vehicle Swapping Stations
title_fullStr A Dual-Layer MPC of Coordinated Control of Battery Load Demand and Grid-Side Supply Matching at Electric Vehicle Swapping Stations
title_full_unstemmed A Dual-Layer MPC of Coordinated Control of Battery Load Demand and Grid-Side Supply Matching at Electric Vehicle Swapping Stations
title_short A Dual-Layer MPC of Coordinated Control of Battery Load Demand and Grid-Side Supply Matching at Electric Vehicle Swapping Stations
title_sort dual layer mpc of coordinated control of battery load demand and grid side supply matching at electric vehicle swapping stations
topic electric vehicles
battery swapping station
model predictive control
multi-stage optimization
peak shaving
url https://www.mdpi.com/1996-1073/17/4/879
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