Javascript must be enabled to continue!
Battery Energy Storage System (BESS) Modeling for Microgrid
View through CrossRef
In the age of technology, microgrids have become well known because of their capability to back up the grid when an unpleasant event is about to occur or during power disruptions, at any time. However, the microgrid will not function well during power disruptions if the controller does not respond fast enough and the BESS will be affected. Many types of controllers can be used for microgrid systems. The controllers may take the form of Maximum Power Point Tracking (MPPT) Controller, Proportional Integral Derivative (PID) Controller, and Model Predictive Controller (MPC). Each of the controllers stated has its functions for the microgrid. However, two controllers that must be considered are PID and MPC. Both controllers will be compared based on their efficiency results which can be obtained through simulations by observing both graphs in charging and discharging states. Most researchers implied that MPC is better than PID because of several factors such as MPC is more robust and stable because of its complexity. Other than that, MPC can handle more inputs and outputs than PID which can cater to one input and output only. Although MPC has many benefits over the PID, still it is not ideal due to its complex algorithm. This work proposed an algorithm of simulations for the MPC to operate to get the best output for microgrid and BESS and compare the performance of MPC with PID. Using Simulink and MATLAB as the main simulation software is a very ideal way to simulate the dynamic performance of MPC. Furthermore, with Simulink, unpredictable variables such as Renewable Energy (RE) sources input and loads demands that are related to MPC can be measured easily. The algorithm of MPC is a cost function. Then the performance of the MPC is calculated using Fast-Fourier Transform (FFT) and Total Harmonic Distortion (THD). Lower THD means a higher power factor, this results in higher efficiency. This paper recorded THD of 9.57% and 12.77% in charging states and 16.51% and 18.15% in discharging states of MPC. Besides, PID recorded THD of 22.10% and 29.73% in charging states and 84.29% and 85.58% in discharging states. All of the recorded THD is below 25% in MPC and it shows a good efficiency while PID’s THD is above 25% shows its inefficiency.
ABSTRAK: Pada zaman teknologi, mikrogrid menjadi terkenal kerana keupayaannya untuk menjana kuasa grid apabila kejadian yang tidak menyenangkan bakal berlaku atau ketika terjadinya gangguan kuasa, pada bila-bila masa. Walau bagaimanapun, mikrogrid tidak dapat berfungsi dengan baik semasa gangguan kuasa jika alat kawalan tidak bertindak balas dengan cukup pantas dan BESS akan terjejas. Banyak alat kawalan (pengawal) boleh digunakan bagi keseluruhan sistem mikrogrid. Setiap pengawal adalah berbeza seperti Pengawal Penjejakan Titik Kuasa Maksimum (MPPT), Pengawal Berkadar Terbitan Kamilan (PID) dan Pengawal Model Ramalan (MPC). Setiap pengawal yang dinyatakan mempunyai fungsinya yang tersendiri bagi mikrogrid. Walau bagaimanapun, dua pengawal yang perlu dipertimbangkan adalah PID dan MPC. Kedua-dua pengawal ini akan dibandingkan berdasarkan keputusan kecekapan yang boleh didapati melalui simulasi dengan memerhati kedua-dua graf pada keadaan pengecasan dan nyahcas. Ramai penyelidik menganggap bahawa MPC adalah lebih baik berbanding PID kerana beberapa faktor seperti MPC lebih teguh dan stabil kerana kerumitannya. Selain itu, MPC dapat mengendalikan lebih banyak input dan output berbanding PID yang hanya dapat menyediakan satu input dan output sahaja. Walaupun MPC mempunyai banyak faedah berbanding PID, ianya masih tidak sesuai kerana algoritma yang kompleks. Kajian ini mencadangkan algoritma simulasi bagi MPC beroperasi mendapatkan output terbaik untuk mikrogrid dan BESS dan membandingkan prestasi MPC dengan PID. Perisian simulasi utama yang sangat ideal bagi mensimulasi prestasi dinamik MPC adalah dengan menggunakan Simulink dan MATLAB. Tambahan, dengan Simulink, pembolehubah yang tidak terjangka seperti sumber Tenaga Boleh Diperbaharui (RE) dan permintaan beban yang berkaitan MPC boleh diukur dengan mudah. Algoritma MPC adalah satu fungsi kos. Kemudian prestasi MPC dikira menggunakan Penjelmaan Fourier Pantas (FFT) dan Total Pengherotan Harmonik (THD). THD yang lebih rendah bermakna faktor kuasa meningkat, ini menghasilkan kecekapan yang lebih tinggi. Kajian ini mencatatkan THD sebanyak 9.57% dan 12.77% dalam keadaan mengecas dan 16.51% dan 18.15% dalam keadaan nyahcas oleh MPC. Selain itu, PID mencatatkan THD sebanyak 22.10% dan 29.73% dalam keadaan mengecas dan 84.29% dan 85.58% dalam keadaan nyahcas. Semua THD yang direkodkan adalah di bawah 25% bagi MPC dan ia menunjukkan kecekapan yang baik manakala THD bagi PID adalah melebihi 25% menunjukkan ketidakcekapan.
Title: Battery Energy Storage System (BESS) Modeling for Microgrid
Description:
In the age of technology, microgrids have become well known because of their capability to back up the grid when an unpleasant event is about to occur or during power disruptions, at any time.
However, the microgrid will not function well during power disruptions if the controller does not respond fast enough and the BESS will be affected.
Many types of controllers can be used for microgrid systems.
The controllers may take the form of Maximum Power Point Tracking (MPPT) Controller, Proportional Integral Derivative (PID) Controller, and Model Predictive Controller (MPC).
Each of the controllers stated has its functions for the microgrid.
However, two controllers that must be considered are PID and MPC.
Both controllers will be compared based on their efficiency results which can be obtained through simulations by observing both graphs in charging and discharging states.
Most researchers implied that MPC is better than PID because of several factors such as MPC is more robust and stable because of its complexity.
Other than that, MPC can handle more inputs and outputs than PID which can cater to one input and output only.
Although MPC has many benefits over the PID, still it is not ideal due to its complex algorithm.
This work proposed an algorithm of simulations for the MPC to operate to get the best output for microgrid and BESS and compare the performance of MPC with PID.
Using Simulink and MATLAB as the main simulation software is a very ideal way to simulate the dynamic performance of MPC.
Furthermore, with Simulink, unpredictable variables such as Renewable Energy (RE) sources input and loads demands that are related to MPC can be measured easily.
The algorithm of MPC is a cost function.
Then the performance of the MPC is calculated using Fast-Fourier Transform (FFT) and Total Harmonic Distortion (THD).
Lower THD means a higher power factor, this results in higher efficiency.
This paper recorded THD of 9.
57% and 12.
77% in charging states and 16.
51% and 18.
15% in discharging states of MPC.
Besides, PID recorded THD of 22.
10% and 29.
73% in charging states and 84.
29% and 85.
58% in discharging states.
All of the recorded THD is below 25% in MPC and it shows a good efficiency while PID’s THD is above 25% shows its inefficiency.
ABSTRAK: Pada zaman teknologi, mikrogrid menjadi terkenal kerana keupayaannya untuk menjana kuasa grid apabila kejadian yang tidak menyenangkan bakal berlaku atau ketika terjadinya gangguan kuasa, pada bila-bila masa.
Walau bagaimanapun, mikrogrid tidak dapat berfungsi dengan baik semasa gangguan kuasa jika alat kawalan tidak bertindak balas dengan cukup pantas dan BESS akan terjejas.
Banyak alat kawalan (pengawal) boleh digunakan bagi keseluruhan sistem mikrogrid.
Setiap pengawal adalah berbeza seperti Pengawal Penjejakan Titik Kuasa Maksimum (MPPT), Pengawal Berkadar Terbitan Kamilan (PID) dan Pengawal Model Ramalan (MPC).
Setiap pengawal yang dinyatakan mempunyai fungsinya yang tersendiri bagi mikrogrid.
Walau bagaimanapun, dua pengawal yang perlu dipertimbangkan adalah PID dan MPC.
Kedua-dua pengawal ini akan dibandingkan berdasarkan keputusan kecekapan yang boleh didapati melalui simulasi dengan memerhati kedua-dua graf pada keadaan pengecasan dan nyahcas.
Ramai penyelidik menganggap bahawa MPC adalah lebih baik berbanding PID kerana beberapa faktor seperti MPC lebih teguh dan stabil kerana kerumitannya.
Selain itu, MPC dapat mengendalikan lebih banyak input dan output berbanding PID yang hanya dapat menyediakan satu input dan output sahaja.
Walaupun MPC mempunyai banyak faedah berbanding PID, ianya masih tidak sesuai kerana algoritma yang kompleks.
Kajian ini mencadangkan algoritma simulasi bagi MPC beroperasi mendapatkan output terbaik untuk mikrogrid dan BESS dan membandingkan prestasi MPC dengan PID.
Perisian simulasi utama yang sangat ideal bagi mensimulasi prestasi dinamik MPC adalah dengan menggunakan Simulink dan MATLAB.
Tambahan, dengan Simulink, pembolehubah yang tidak terjangka seperti sumber Tenaga Boleh Diperbaharui (RE) dan permintaan beban yang berkaitan MPC boleh diukur dengan mudah.
Algoritma MPC adalah satu fungsi kos.
Kemudian prestasi MPC dikira menggunakan Penjelmaan Fourier Pantas (FFT) dan Total Pengherotan Harmonik (THD).
THD yang lebih rendah bermakna faktor kuasa meningkat, ini menghasilkan kecekapan yang lebih tinggi.
Kajian ini mencatatkan THD sebanyak 9.
57% dan 12.
77% dalam keadaan mengecas dan 16.
51% dan 18.
15% dalam keadaan nyahcas oleh MPC.
Selain itu, PID mencatatkan THD sebanyak 22.
10% dan 29.
73% dalam keadaan mengecas dan 84.
29% dan 85.
58% dalam keadaan nyahcas.
Semua THD yang direkodkan adalah di bawah 25% bagi MPC dan ia menunjukkan kecekapan yang baik manakala THD bagi PID adalah melebihi 25% menunjukkan ketidakcekapan.
Related Results
Research on fault current control method of DC microgrid battery energy storage system
Research on fault current control method of DC microgrid battery energy storage system
Abstract
Battery energy storage system has become an important link to maintain the stable operation of DC microgrid because of its flexible control and fast response speed...
Application of wind photovoltaic microgrid with hydrogen energy storage system in industrial aquaculture enterprises
Application of wind photovoltaic microgrid with hydrogen energy storage system in industrial aquaculture enterprises
Abstract
The high electricity consumption problem of industrial aquaculture has been the bottleneck limiting the large-scale promotion of this new aquaculture technology. A...
APPLICATION OF SOLAR ENERGY TO MEASURE PHOTOVOLTAIC CAPACITY AND BATTERY OPTIMIZATION
APPLICATION OF SOLAR ENERGY TO MEASURE PHOTOVOLTAIC CAPACITY AND BATTERY OPTIMIZATION
This study uses the Markov Decision Model (MDP) to implement battery degradation and optimize battery use in Photovoltaic and the battery system model created. The battery optimiza...
Two-Stage Model Predictive Control for Battery Electric Vehicle-Centric Mobile Energy Storage in Microgrids
Two-Stage Model Predictive Control for Battery Electric Vehicle-Centric Mobile Energy Storage in Microgrids
With the accelerated global energy transition, the integration of plug-in electric vehicles (BEVs) into microgrid systems has emerged as a promising approach to enhance operational...
Data-Driven Decision Making in Battery Technology – How to Compete in Global Battery Industry?
Data-Driven Decision Making in Battery Technology – How to Compete in Global Battery Industry?
Battery technology is regarded as a crucial key technology for the energy transition and thus a sustainable future, as batteries can store and distribute renewable energy to cover ...
Realization of Fuzzy Logic Controller in Microgrid for Mongolian case
Realization of Fuzzy Logic Controller in Microgrid for Mongolian case
This paper presents the development and simulation of photovoltaic (PV), wind turbine and battery energy storage system (BESS) based microgrid in a Mongolian c...
Pursuit of “Absolute Battery Safety, Fear-Free Energy and Mobility” - A Technology Roadmap Toward a Fail-Never Battery Future
Pursuit of “Absolute Battery Safety, Fear-Free Energy and Mobility” - A Technology Roadmap Toward a Fail-Never Battery Future
The Pursuit of “Absolute Battery Safety, Fear-Free Energy, and Mobility”—A ”Technology Roadmap Toward a Fail-Never Battery Future
As the electrification of transportation and energ...
Switching control strategy for an energy storage system based on multi-level logic judgment
Switching control strategy for an energy storage system based on multi-level logic judgment
Energy storage is a new, flexibly adjusting resource with prospects for broad application in power systems with high proportions of renewable energy integration. However, energy st...

