Optimization of Renewable Energy Based Smart Grid

1. Chittagong University of Engineering & Technology
Maitry Dey
Shafiul Hasan Rafi
Ph.D. Student
Department of Electrical and Electronic Engineering (EEE)
Chittagong University of Engineering and Technology (CUET)
Optimization of Renewable Energy-Based Smart
Micro-Grid System
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Presented By

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o Background and Research Motivation
o Research Objectives
o Tentative Model
o Conclusions
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o World wide power usage in 2015 was around 18 TW [1].]
o In 2050 it would be 35 TW [2].
o Annual Report of 2019-20 (BPDB) - 5% of total population has no access
to electricity [3].
Table 1: Present electricity generation in Bangladesh 2019-2020 [3]
Source Percentage
Natural Gas 71.82%
Furnace Oil 13.25%
Diesel 0.20%
Hydro 1.16%
Renewable Energy 0.07%
Power Import 9.34%
Coal 4.16%

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o Demand of Energy on next decade -61 GW [5].
Fig. 1: World energy consumption (1950 to 2050) [4]

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o Renewable energy environmentally and reliable approach in
Bangladesh.
Table 2: Electricity production from renewable energy sources in
Bangladesh [6]
o Renewable energy capacity by 2021: Solar – 416 MW [7]
Wind- 359.9 MW [8]
Serial No. Technology Present
Renewable Energy
in Bangladesh
(MW in 2021)
Future
Renewable Energy
in Bangladesh
(MW within 2030)
1 Solar 120 165
2 Wind 80 170

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o Present system loss of electricity is 11.11% [9].
o High transmission losses [10].
o Greenhouse effect and environment pollution [11].
o Electricity generate by conventional method from renewable
sources.
o Improper use of renewable energy.

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o Utilizing the Renewable Energy Sources
o Extracting maximum power from renewable sources.
o Smart energy management strategy which minimize power loss.

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o To design and develop a hybrid renewable energy system using
ANFIS based MPPT controller.
o To reduce the loss of energy and emission of carbon.
o Cost optimization and development of effective control mechanism
for the system.

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 Microgrid:
o PV Array, Wind, Battery, Fuel Cell, Dc /Dc Boost converter,
Diode, Mosfet
 ANFIS: Adaptive neural fuzzy interface system.
o Used to improve the performance under unstable weather
conditions.

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• Maximum allowable shortage/year
• Minimum renewable fraction
• Wind and solar percentage of renewable fraction (wind-solar)
• Annual real interest rate
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• The power output of the solar farmis considered as Psolar (t ).
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The equation for the charging dynamics of the SS is given by
The equation for the discharging dynamics of the SS is given by
Detailed dynamics of the SS and it’s power delivery can be considered in a
local-level controller

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• Disel Genrator commanded power output.
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Fig : Consumer Load Power
the Power reference to be tracked using the given eqn, where the power from the
solar farm subtracted from the consumer load to provide the full reference power
that the electric grid will need to deliver.

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It depicts the control hierarchy of the hybrid system, where the supervisory controller
provides control commands to the various components on the electric grid. The main
objective is to make maximum use of the renewable power source, i.e. the solar farm,
while using the least amount of power from the diesel generator.
 The controller uses a High Fidelity
Simulator.
 The controller then send the power
commands U to the respective systems
on the power grid.

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Assumptions
• Generator, SS charge/discharge efficiencies assumed to be constant
• Power Transmission Line loss assumed as part of reference load
profile
System Dynamics
Let x represent the state variables and u the control inputs
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The hybrid system is modeled as a continuous linear time-invariant system with
three states variables and two control inputs as follows:

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• The inputs are related to the states through the B matrix, which
remains the same regardless of the mode operation
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• where wx are tracking weights
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• both the initial state, initial time and final time are fixed, while
the final state is free. So that:
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• The control outputs from the MPC depend on the current mode of
operation of the system, v. These outputs are determine by using
two different approaches using the embedded value of v provided
by the optimization algorithm
• Logic projection
• The hybrid mode v is computed as a continuous state ranging
from[0,1]. Once a value has been assigned, this is projected to
either mode 0 or mode 1 satisfying the following logic:
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• Projection based on Uss
In this case, the sign of the control inputUss determines whether the system
goes to charging or discharging mode. i.e.,

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 power reference profiles were tracked by using the parameters listed
below

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Figures 7 and 8 show the 3 set of inputs commands obtained from tracking a 50kW
power reference load, and the trajectory followed by the state variables
respectively. The simulation was run for a total time of 24 seconds

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[1] “Global Energy Consumption: The Numbers for Now and in the Future,” DTU Library, 2016.
Available at: https://Global_Energy_Comsumption_The_Number_for_Now_and_in_the_Future.pdf
(Accessed on December 26, 2021).
[2] Daniel G. Nocera, Daedalus,“ On the Future of Global Energy,” vol. 135, no.4, pp.112-115, 2006.
[3] Annual report, Bangladesh Power Development Board, 2019-2020.
Available at: https://www.bpdb.gov.bd/bpdb_new/resourcefile/annualreports/annualreport_
1604389759_Annual_Report_2019-20.pdf (Accessed on September 26, 2021).
[4] “World Energy 2018-2050: World Energy Annual Report (Part 1)”, Department of Economics, University of
Utah, June, 2018.
Available at: http://peakoilbarrel.com/world-energy-2018-2050-world-energy-annual-report-part-1/
(Accessed on December 26, 2021).
[5] N. K. Das et al., “Present energy scenario and future energy mix of Bangladesh,” Energy Strategy Reviews,
vol. 32, November 2020.
[6] Sazzad Hossain, Mohammad Maksudur Rahman, “Solar Energy Prospects in Bangladesh: Target and Current
Status ,” Energy and Power Engineering, vol. 13, No.8, August 2021.
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[7] “Solar and Wind Power Potential in Bangladesh,” Energy Tracker ASIA.
Available at: https://energytracker.asia/solar-and-wind-power-potential-in-bangladesh/
(Accessed on December 26, 2021).
[8] “SREDA-National Database of Renewable Energy.
Available at: https://ndre.sreda.gov.bd/index.php?id=1&i=11.
(Accessed on December 26, 2021).
[9] Power Cell (www.powercell.gov.bd).
Available at: http://www.powercell.gov.bd/site/page/d25a46c5-6c0f-47d7-94f2-
9ac4351f4404/System-Loss.(Accessed on December 26, 2021).
[10] Zhichuan Huang et al., “Minimizing Transmission Loss in Smart Microgrid by Sharing renewable Energy,”
ACM Transections on Cyber-Physical System, vol. 1, No. 2, pp. 1-22, December 2016.
[11] Vahid Sohrabi Tabar et al., “Sustainable planning of hybrid microgrid towards minimizing environmental
pollution, operational cost and frequency fluctuations,” Journal of Cleaner Production, pp. 1-14, September
2018.
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