OPTIMIZATION OF DC MICROGRID-DESIGN AND
SMART OPERATION
ABSTRACT
The need for electricity is one of the main world problems for the next centuries. With the
increase of the world thirsty for energy and shortage of energy reserves from traditional
fossil fuels, the world energy future seems to be unclear. One of the promised energy
sources are renewable energy resources like wind solar and marine energy. This work’s
aim is to study a DC-micro grid. The researcher is going to get an existing DC-micro grid
data. This data will be used to study and analysis optimum location and size of renewable
resources and also for the storage batteries. With the aid of suitable software and optimum
communications (IoT) and control systems, the operation of DC-micro grid will be smarter.
This smart DC-micro grid will demand a simple and high tolerance of perfect operation.
This would give local schools sufficient power to use computers, have lights on during the
night for those in boarding school and for those who have homework to do at night; and
residents can power their appliances. The benefits are significant. This will help to reduce
‘energy poverty’ and to promote social and economic development.
I. BACKGROUND
I.1 World and Energy
According to International Energy Agency [1], more than 1.3 billion people across the
globe are without access to electricity, and 85% of these live in rural/off-grid areas. The
term ‘energy poverty’ has been used to describe this situation where a certain population
or area lacks access to modern energy services including electricity and clean cooking
facilities. Approximately 2.7 billion people still rely on traditional energy such as bio-mass
and fossil fuels for cooking and light sources. By continuing use of the traditional fossil fuel
sources will greatly affect the environment in terms of deforestation and pollution residual
emissions created by burning these fuels [2]. Lack of access to modern energy services can
also have a detrimental effect on social and economic development.
According to the World Bank and International Monetary Fund, Asia and South America
present higher population growth rates than the rest of the world. This means that the
demand for electricity will increase. It is well known that for the past few years, energy has
been one of the main aspects of the fight for economic development; mainly due to rapid
population growth, which has outpaced slightly increasing electrification rates [3].
I.2 DC-Micro grid
DC off-grid systems/decentralised power play a major part in providing energy to rural
areas, and this can have positive economic and social consequences. DC off-grid systems
are mainly based on renewable sources, which is an advantage because most developing
countries are rich in natural and renewable energy sources.
Latin and Central America has achieved a lot of successive projects of DC off grid [1].
Their strong commitment to and investment in off-grid electrification has led to 11 million
people gaining access to electricity in the past years at a global 92.7% electrification rate
and 98.7% urban rate. This has led to 9% of the continent’s rural areas gaining electricity.
A micro-grid is defined [5], as a collection of controllable and physically proximate
distributed generator and load resources, where there are multiple sources of AC power, at
least one of which is based on a renewable energy technology. Traditionally, an offgrid/decentralised system (mainly in rural areas) is characterised by [5]:
 A remote community, supplied by a small number of relatively large generators,
with a centralised control system that has no load control incorporated in the
system.
 A single house or building connected to a local renewable energy system; for
example solar or wind energy. The system may or may not be connected to the main
utility grid. The system usually operates using a DC bus and single inverter.
 A single house or building with a local backup power supply. The backup battery
supply is usually a single generator or battery.
I.3 Smart System
A smart system works on the principle of real-time parameter measurements unlike most
current grid systems where demand figures are made on estimates based on experience and
monthly manual readings from analogue meters. Smart grid systems also operate on a twoway communication between the consumer and supplier, unlike traditional systems, which
are Omni-directional. It can be defined as an advanced digital two-way power system that
is capable of self-healing, adaptive, resilient and sustainable, with foresight for prediction
under different uncertainties. With all these characteristics, the system is able to achieve
[5];


Energy efficiency. Using real-time data and information related to the consumer’s
daily power usage, the system can adjust the amount of power delivered and when it
should be delivered. This means that less energy is wasted.
Operational efficiency. Traditionally, suppliers build power systems or plants 10-



20% larger than the anticipated demand to make sure they can accommodate
unexpected growth and meet everybody’s energy needs, especially at peak times.
Fault detection and repair is another expensive expenditure for utility companies.
And because energy cannot be stored, electricity production has to match consumer
demand in an instant. This means there is significant power loss. But with a smart
system, everything is automated and remotely controlled. This improves
performance, reduces losses and reduces operational costs. Energy storage and
demand-response saves costs and reduces energy loss.
Affordable. Using real-time data means that instead of a per-month rate, customers
are charged by the hour in real time, so they are able to save money.
Demand management. The smart grid allows the electricity system to reduce loads
readily when necessary, diverting electricity from non-critical to more critical and
essential loads automatically.
The smart system promotes clean energy and technologies.
The above text concludes that the majority of off-grid power generation systems used in
developing countries are not micro-grids but are mainly isolated power sources providing
power to required loads. This is due to a lack of intelligence in these systems.
A smart micro-grid will add the following features [5]:

Intelligence. Making it capable of sensing system conditions, reconfiguring device
operation and system topology given goals such as reliability of supply, cost of
operation and emissions minimisation.
 Efficiency based primarily on clean renewable generation sources and intelligent
energy-efficient loads.
 Resilient. The ability to configure and withstand device failure and avoid total
system collapse. The ability to maintain the quality of supply despite issues on the
wider electricity grid. The system is said to be self-healing.
 Dynamic. Constantly changing in order to meet the intelligent and resilient goals.
 Load integrated. The ability to intelligently integrate local loads with generation,
matching supply and demand and maximising infrastructure utilisation.
 Flexible. Facilitating the easy introduction of new loads and generators and the
adoption of new communications technologies without requiring significant
infrastructure change.
The system can either be isolated to or connected to the main utility grid via a two-way
point of common coupling.
II.
AIMS AND OBJECTIVES
The main aim of this project is to improve the operation and design of a micro grid, by
developing an intelligent micro-grid system that is tailored to the needs of developing
countries; especially in remote, off-grid and underdeveloped areas. The end result is to
provide a highly efficient and affordable smart grid system that is capable of providing
efficient power to communities and to reduce dependency on traditional energy sources
such as fossil fuels.
Because the aim is to make energy affordable, most of the design and development of this
system will be made from open source hard /software and cheap design parts for the
hardware, with minimal use of materials. The system should also be very easy to
understand so that people can be taught how to use and maintain it.
The keyword in this system is “SMART”. This means that the system should have the
ability to learn, adapt and perform without much supervision i.e. to be an automated
system. Such systems belong to a branch of engineering called ‘computational intelligence’.
Ref 6 defines computational intelligence as a term used to describe the advanced analytical
tools needed to optimise the bulk power network. It includes heuristic, evolution
programming, decision support tools and adaptive optimisation techniques. Computational
intelligence will be used in this research to develop an optimised adaptive system.
There are vast numbers of computational intelligence optimisation techniques that can be
used. These include: classical, heuristic, evolutionary and adaptive dynamic programming,
and the Pareto method of optimisation techniques [6].
Ref 6 explains performance analysis tool ‘Stochastic Dynamic Optimal Power Flow’
(DSOPF)’ for a smart grid system that uses computational intelligence algorithms to study
load flows plus other general purpose tools such as controllability, interoperability,
reliability, adaptability, sustainability and anticipatory behaviour.
Communication, measurement and monitoring are other important aspect of a smart
system.
The characteristics of smart grid technology include high bandwidth, IP-enabled digital
communication, encryption, cyber security, support and quality of service, and voice over
internet protocol. The technology to achieve this is readily available: multiprotocol label
switching (MPLS), worldwide interoperability for microwave access (WiMax), broadband
over power lines and wireless local area networks (Wi-Fi). The network topologies to apply
these communication systems include Local Area Network, Home Area Network and
Neighbourhood Area Network.
The metering and measurement technologies use digital electronic equipment. The
communication between these pieces of equipment is two-way, with various inputs and
outputs including tariff prices and real-time consumption data. The metering and
measurement technologies are partnered with an advanced utility monitoring system. The
main two types of monitoring systems as described in ref 6 include Wide Monitoring
System and Phase Measurement Units, which are mostly used in current smart grid
systems.
III.
METHODOLOGY
The DC micro grid will be modelled based on an actual data of an existing project. A power
flow program will be used to model elements of DC-Micro grid to study and optimize the
operation and different components renewable resources wind, solar and hydro. With the
aid of load analysis, the locations and size of batteries will be decided [12-13].
A small-scale PV monitoring system software design [9] that is designed and developed
using a microcontroller for analogue to digital conversion, data storage and transmission
while LabVIEW is used to develop the monitoring software. The system monitors
photovoltaic array voltage and array current, ambient temperature and solar irradiance
data.
Ref 10 describes the design of a monitoring system for wind power generation based on the
wireless sensor network. The hardware part of the monitoring system is made up of a
MSP430F169, 16-bit, ultra-low power Microcontroller unit, a CC2520 ZigBee RF
transceiver for a 2.4 GHz unlicensed ISM band and a CC2591 2.4GHz RF front end. The
software implementation is done using TinyOS-embedded operating system programming.
In this instance, the wide monitoring system is used.
Open Energy Monitor [7] is an open source hardware/software energy monitoring system.
Its applications include a wireless, web-connected home energy monitor and wireless webconnected solar PV monitor system/grid import/export monitoring system. The hardware
and software are ARDUINO based. Because this system is open source, the initial start
design of the smart monitor system will be based on this. The OpenEnergyMonitor is just a
monitoring system and has no smart characteristics, so further research developments will
focus on adding smart features such as a two-way communication system, automated
control and real-time data acquisition.
The monitoring and control system should be able to integrate with most forms of
renewable energies. Renewable energy sources are seen as volatile sources of power with
fluctuations because they are highly dependent on environmental conditions, it is necessary
to add environmental sensors and algorithms within the smart monitoring system to
increase system performance. Ref 8 developed a low-cost, autonomous remote weather data
acquisition system to collect and transfer local data to any PC with an internet connection.
This system is composed of sensors, a server/computer, precision electrical circuits and use
of LabVIEW software to develop the monitor interface.
A low-cost concept for data acquisition system, shown in ref 11 for decentralised renewable
energy, which uses a USB interface, is another interesting resource that will be used in this
research. This low-cost USB interface presents a new dual clock, dual operation philosophy
where the data acquisition system contains two clock sources for parallel information
processing. The system monitors real-time energy conversion efficiency and sends failure
information. The proposed data acquisition firmware and software for USB
microcontroller programming is free and open source software.
All the above background concepts are based on low-cost designs and will be used in the
research and development of this research project, which is to develop a low-cost smart
monitoring and control grid system for off-grid areas. A PC, electrical/electronic circuit
components, networking equipment, access to renewable energy sources and data, Matlab,
LabVIEW, TinyOS, GIS, Google mapping tools and Visual Studio are some of the software
and hardware resources required for this project. This will alter with time.
IV. RESEARCH PLAN
To achieve goals of this proposal the following steps will be done:
- A literature review for the progress in DC micro grid and smart systems such as
components and stages of development of a smart grid monitoring and control
system.
- Collecting system parameters and data such as: (weather conditions, load analysis
and characteristics, renewable energy resources PV/wind/hydro,
- Modelling the dc-micro grid, pv/wind turbine/hydro, loads, and controls systems.
- Study the effected of power generation from renewable resources and loads.
- Study integrating of weather monitoring in operation of power system.
- Study the optimization of renewable energy resources distributions.
- Study the optimization of batteries sizes and distributions.
- Design smart system for the studied micro grid. This stage will involve the initial
system hardware design. The hardware systems will include the sensors,
communication and network hardware, switching, control, monitoring and display
hardware, among others.
-
Programming the hardware components using specific software packages. Data
capturing, monitoring, display and user interface software application
developments. The hardware and software development will be performed in
parallel.
-
The hardware and software developments will be made. The different system
modules will be combined to create a complete system. This is where the
computational intelligence algorithms will be most important for smart automated
control of all the system modules.
-
A lot of field tests, error correction and system optimisation will be done at this
stage.
-
Final thesis writing and final system tests will be done at this stage.
V.
FEASIBILITY ANALYSIS
The researcher who will work in this proposal is from Uganda he will concern related
project in Uganda. In Uganda 99.3% of the electricity is produced by a centralized hydro–
electric power station [4]. Uganda has a population of 35 million people, of which only 5%
is connected to the grid amid widespread poverty. That 5% experiences load shedding due
to insufficient and inefficient supply generation, which doesn’t match demand. This means
that for developing countries that are projected to experience a significant population
increase, social and economic developments should improve and increase at a similar rate.
For this to occur, an efficient and reliable power source must be made available. Most
current off-grid locations are powered by either a renewable energy source or a backup
battery. These systems are usually left to operate without a well-developed energy
management structure. This comes with a number of disadvantages, for example high
power losses, poor equipment maintenance, equipment breakdown and power shortages,
which can lead to long delays in repairs; in other words the system in efficient. Most of the
smart grid resources that are currently on the market such as smart plugs and sensors are
very expensive, making it impossible to use these on a small scale basis.
The purpose of this research is to bridge this gap by developing a low-cost, off-grid smart
energy monitor and control system. Unlike other systems, it will mainly be designed for offgrid/rural areas, renewable energy sources and DC powered systems.
The research will require collaboration with other university departments, especially the
computer science department. Their research and experience in computational intelligence
algorithms and programming will be very vital in the development of the smart system.
This research will also be looking to collaborate with the Centre for Research in Energy
and Energy Conservation (CREEC) in Uganda .CREEC is a non-profit organization that
works with the College of Engineering, Design, Art and Technology of Makerere University
in Uganda. CREEC aims to apply and adapt renewable energy technologies that are
specific to the Ugandan local environment through access to modern research, training and
international consultancy. Recent meetings with CREEC have shown that they are looking
into application of affordable smart off-grid systems in rural areas. They have pilot
schemes ready to start in their project time-line. Collaboration with CREEC will be a very
important source of data and information.
VI.
EXPECTED OUTCOMES
It is expected to have several publications at conferences and journal level for the following
points
 Optimization of measurement and control elements and locations in dc micro smart
grid
 Improving data communications by applying Two-way communication, Real-time
data acquisition
 Optimization of renewable energy resources in DC-micro grid
 Optimization of batteries locations and sizes in DC-micro grid.
 Integrating weather prediction patterns in improving design and operation of DCmicro grid.
 Integrating power energy analysis with the design of DC-Micro grid
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Biogas/photovoltaic hybrid power system for decentralized energy supply of rural areas,
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