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Energy management of a battery energy storage system for renewable energy DC micro-grid
Author(s)
Bipongo, Christian Ndeke
Date Issued
2021
Type
Thesis
Publisher
Cape Peninsula University of Technology
Abstract
This research presents a regime for energy management of a battery energy storage system
in a renewable DC micro-grid. The increase in world electricity demand is one of the principal
drives to the exhaustion of fossil fuels and expanded greenhouse gas emissions. To solve
these problems, several countries have adopted actions for large deployment renewable
energy sources, which includes wind energy, solar power, biomass power, tidal and
hydropower. These sources are considered as significant in delivering clean energy and
reducing greenhouse gas emissions for sustainable improvement. These renewable energy
sources are often connected to the conventional power system through the distribution
network near consumer loads, thus no extensive transmission system is needed. In such a
case, these are referred to as distributed generation systems.
Distributed generation can impact negatively the performance of the distribution network as
the distribution network will no longer operate with a unidirectional power flow pattern. Some
of the known issues are known to affect voltage quality, protection equipment settings,
desensitised relays, augmented fault currents, increased maintenance of equipment used,
and even a landing portions of the distribution network. To address these issues, micro-grids
are used as a platform to integrate distributed generation systems, as they provide significant
benefits to end-users and to the distribution network. The utilization of energy storage systems
is necessary in renewable micro-grids as they can ensure the reliability of the supplied power.
Battery energy storage systems are the types of energy storage widely utilized in renewable
micro-grids. Comparatively to Li-ion battery, most of the technologies present some issues
(the relation between the charge / discharge rate on their operating conditions, unbalance
SoC conditions), which can impact on the battery lifetime as well as the average of energy
stored in the battery. In case of battery bank, the deep discharge or the premature charge of
battery can lead to a reduced lifetime of the storage system.
The problem of this research was the lack of a proper battery management system in a
renewable DC micro-grid. The DC micro-grid and energy management system algorithm was
implemented and developed using MATLAB/Simulink software, which used a physical
modelling approach. The aim of this research was to develop a battery management system
algorithm to control the charging / discharging of a battery bank and to keep its state of charge
(SoC) in the admissible limits to avoid the deep charging / discharging of the battery within a
DC micro-grid. Moreover, in a micro-grid, given that several power sources are connected, an
energy management system needs to be implemented to ensure their proper operation. The
objectives of this research were to develop DC micro-grid component models to be used in the simulation model; to design and develop function block logic to be used for the simulation
using State-Flow logical programming environment in MATLAB/Simulink software; to develop
a control system schemes for the DC micro-grid; to develop an energy management system
(EMS) algorithm for the DC micro-grid and to develop a battery management system (BMS)
algorithm and to design and develop a simulation of a DC micro-grid with battery energy
storage using MATLAB/Simulink software.
The results of the scenarios of the developed energy management system (EMS) algorithm
have successfully shown that this developed algorithm will be able to ensure the reliability,
the resiliency, the robustness and the proper operation of the battery systems in micro-grids.
The principal advantage of this developed algorithm will be that it will ensure the proper
relation between the charge / discharge rate of battery energy storage systems on their
operating conditions and will allow to keep its SoC in the admissible limits according to the input
power conditions from the EMS flow chart, to avoid the deep charge / discharge of the battery
bank, which in return will significantly impact on their lifespan and on the reliability in a DC
micro-grid. The results demonstrated that the battery bank was able to handle the load
demands for different scenarios studied. Moreover, the developed software model presents
another advantage, which enables the users to access and to change any control parameter
within the DC micro-grid.
In addition, this developed algorithm will provide a low overall cost and degradation impact on
the battery. The SoC of the battery operation will directly affect its achievable lifetime positively
and the battery degradation costs will significantly decrease. This algorithm offered a proper
operation of the entire developed DC micro-grid system, which could result in reduced battery
degradation and improve battery life as well as the energy stored in the battery. The results
have shown that the initial investment cost will comparatively be lower and will decrease the
economic analyse in terms of LCOE.
in a renewable DC micro-grid. The increase in world electricity demand is one of the principal
drives to the exhaustion of fossil fuels and expanded greenhouse gas emissions. To solve
these problems, several countries have adopted actions for large deployment renewable
energy sources, which includes wind energy, solar power, biomass power, tidal and
hydropower. These sources are considered as significant in delivering clean energy and
reducing greenhouse gas emissions for sustainable improvement. These renewable energy
sources are often connected to the conventional power system through the distribution
network near consumer loads, thus no extensive transmission system is needed. In such a
case, these are referred to as distributed generation systems.
Distributed generation can impact negatively the performance of the distribution network as
the distribution network will no longer operate with a unidirectional power flow pattern. Some
of the known issues are known to affect voltage quality, protection equipment settings,
desensitised relays, augmented fault currents, increased maintenance of equipment used,
and even a landing portions of the distribution network. To address these issues, micro-grids
are used as a platform to integrate distributed generation systems, as they provide significant
benefits to end-users and to the distribution network. The utilization of energy storage systems
is necessary in renewable micro-grids as they can ensure the reliability of the supplied power.
Battery energy storage systems are the types of energy storage widely utilized in renewable
micro-grids. Comparatively to Li-ion battery, most of the technologies present some issues
(the relation between the charge / discharge rate on their operating conditions, unbalance
SoC conditions), which can impact on the battery lifetime as well as the average of energy
stored in the battery. In case of battery bank, the deep discharge or the premature charge of
battery can lead to a reduced lifetime of the storage system.
The problem of this research was the lack of a proper battery management system in a
renewable DC micro-grid. The DC micro-grid and energy management system algorithm was
implemented and developed using MATLAB/Simulink software, which used a physical
modelling approach. The aim of this research was to develop a battery management system
algorithm to control the charging / discharging of a battery bank and to keep its state of charge
(SoC) in the admissible limits to avoid the deep charging / discharging of the battery within a
DC micro-grid. Moreover, in a micro-grid, given that several power sources are connected, an
energy management system needs to be implemented to ensure their proper operation. The
objectives of this research were to develop DC micro-grid component models to be used in the simulation model; to design and develop function block logic to be used for the simulation
using State-Flow logical programming environment in MATLAB/Simulink software; to develop
a control system schemes for the DC micro-grid; to develop an energy management system
(EMS) algorithm for the DC micro-grid and to develop a battery management system (BMS)
algorithm and to design and develop a simulation of a DC micro-grid with battery energy
storage using MATLAB/Simulink software.
The results of the scenarios of the developed energy management system (EMS) algorithm
have successfully shown that this developed algorithm will be able to ensure the reliability,
the resiliency, the robustness and the proper operation of the battery systems in micro-grids.
The principal advantage of this developed algorithm will be that it will ensure the proper
relation between the charge / discharge rate of battery energy storage systems on their
operating conditions and will allow to keep its SoC in the admissible limits according to the input
power conditions from the EMS flow chart, to avoid the deep charge / discharge of the battery
bank, which in return will significantly impact on their lifespan and on the reliability in a DC
micro-grid. The results demonstrated that the battery bank was able to handle the load
demands for different scenarios studied. Moreover, the developed software model presents
another advantage, which enables the users to access and to change any control parameter
within the DC micro-grid.
In addition, this developed algorithm will provide a low overall cost and degradation impact on
the battery. The SoC of the battery operation will directly affect its achievable lifetime positively
and the battery degradation costs will significantly decrease. This algorithm offered a proper
operation of the entire developed DC micro-grid system, which could result in reduced battery
degradation and improve battery life as well as the energy stored in the battery. The results
have shown that the initial investment cost will comparatively be lower and will decrease the
economic analyse in terms of LCOE.
Additional information
Thesis (MEng (Energy))--Cape Peninsula University of Technology, 2021
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