Analysis, modelling and control of a DC microgrid: AC grid ...

Treball de Fi de Màster

Màster en Enginyeria de l’Energia

Analysis, modelling and control of a DC

microgrid: AC grid connection and renewable energy integration

MEMÒRIA

Autor: Albert Andreu Solà Director: Oriol Gomis Bellmunt Convocatòria: Juny 2021

Escola Tècnica Superior d’Enginyeria Industrial de Barcelona

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Analysis, modelling and control of a DC microgrid: AC grid connection and renewable energy integration Pàg. 3

Summary

In this project the concept of smart grids and specially microgrids is studied and analysed in

order to propose a system that can generate the power necessary for a certain grid in a DC

based microgrid. The microgrid modelled in this system is composed by a photovoltaic plant

and a wind farm that generate the energy necessary for a certain proposed grid from the

CIGRE benchmark.

The interesting point of this project, apart from the modelling of the generation plants and

their converters, is the interconnection between both systems. The original grid is an

alternating current grid based on a small town in southern Germany and the proposed

microgrid is a direct current grid modelled by the author of this project, so, the

interconnection of both will be done with a voltage source converter. The control of this

device is what will help the system overgoing different problems that may occur. Together

with the modelling of this system, different tests are done to the different parts that compose

it in order to assure a perfect operation of the system.

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Index

INDEX _______________________________________________________ 4

1. PREFACE ________________________________________________ 8

1.1. Project’s origin................................................................................................ 8

1.2. Motivation ....................................................................................................... 8

2. INTRODUCTION ___________________________________________ 9

2.1. Objectives ...................................................................................................... 9

2.2. Range .......................................................................................................... 10

3. STATE OF ART __________________________________________ 11

3.1. Smart grids ................................................................................................... 11

3.1.1. Smart grid characteristics ................................................................................. 12

3.1.2. Smart grid challenges ...................................................................................... 14

3.1.3. Smart grid security ........................................................................................... 14

3.1.3.1. Adaptive protection ............................................................................... 15

3.2. Microgrids .................................................................................................... 15

3.2.1. Microgrid structure ........................................................................................... 16

3.2.2. Challenges in microgrid protection ................................................................... 17

3.2.2.1. Changes in fault currents ..................................................................... 17

3.2.2.2. Blinding of protection ............................................................................ 17

3.2.2.3. False tripping ........................................................................................ 18

3.2.2.4. Unsynchronized and automatic reclosing ............................................. 18

3.3. CIGRE Benchmark ...................................................................................... 18

3.4. Voltage source converter ............................................................................. 20

3.4.1. Clarke transformation ....................................................................................... 21

3.4.2. Park transformation .......................................................................................... 22

3.4.3. Instantaneous power theory ............................................................................. 23

3.4.4. General control scheme ................................................................................... 26

3.4.5. Current loop control.......................................................................................... 27

3.4.6. Phase locked loop ............................................................................................ 29

3.4.7. DC voltage regulator ........................................................................................ 29

4. CASE STUDY: DC MICROGRID IMPLEMENTATION ____________ 31

4.1. Grid’s data .................................................................................................... 31

4.2. Grid model ................................................................................................... 34


4.3. Wind farm model .......................................................................................... 35

4.3.1. First wind farm proposal .................................................................................. 35

4.3.2. Second wind farm proposal ............................................................................. 36

4.3.3. Third wind farm proposal ................................................................................. 37

4.3.4. Wind farm simulation ....................................................................................... 42

4.4. PV plant model ............................................................................................. 47

4.4.1. PV plant simulations ........................................................................................ 50

4.4.1.1. First simulation ..................................................................................... 50

4.4.1.2. Second simulation ................................................................................ 53

4.4.1.3. Third simulation .................................................................................... 54

4.5. VSC control model ....................................................................................... 57

4.5.1. VSC simulation ............................................................................................... 61

4.6. Microgrid model ............................................................................................ 64

4.7. System simulation ........................................................................................ 65

CONCLUSIONS ______________________________________________ 69

ACKNOWLEDGEMENTS _______________________________________ 71

BIBLIOGRAPHY ______________________________________________ 72


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1. Preface

In this section the project’s origin and the motivation will be explained.

1.1. Project’s origin

The project origin is from the necessity of our actual World to change its electrical system

from the conventional one with big centralized generation to a new scheme more

decentralized where the generation and the consumption are nearer. This is also why I

started studying this master, in the next few years a change on the electrical paradigm is

required and I want to be involved in order to help save our planet.

1.2. Motivation

As mentioned in the previous section the main motivation of this project is the necessity of

making this type of projects in order to show the World that we are capable of having our

own energy and also that we can generate that power from renewable sources, in order to

make it easier for the future generations to survive.

The fact of working with a smart grid comes from the motivation I had on working with this

type of devices as I see them as the best option in terms of electrical development for the

future.


2. Introduction

The introduction of renewables in the electric systems all over the World is becoming more

and more common nowadays due to the transition to a more distributed electric system and

the necessity of reducing the greenhouse gases emissions. Renewable plants like wind

farms or solar fields are wide spread all over the Earth, configurating a robust system

together with the conventional plants and helping to reduce the environmental impact of the

electricity generation, but the society’s development will need a more distributed system,

where the places of generation and consumption of electricity are as near as possible,

reducing the losses and therefore boosting the efficiency.

One of the main challenges that engineers have to face when designing a distributed system

with renewables is the conversion from AC signal to DC signal and vice versa that has to be

implemented due to the fact that most of the renewable energies produce in direct current.

This forces engineers to set converters and inverters to interconnect the generation with the

distribution and transmission, which sometimes can be very expensive and represent a big

part of the inversion.

In order to reduce the implementation of these electronic devices we can congregate all the

renewable generation in a DC smart grid and then connect it to the distribution grid, reducing

the number of inverters and converters to the ones that connect both systems. This would

affect to the decentralization of the electric system because we reduce it but it would also

help with its robustness as we concentrate all the DC generation at one point, making it

easier to control.

So, in this project, a DC smart grid with solar and wind generation will be modelled and

simulated in different scenarios with the objective of evaluating how it works and if it would be

possible and beneficial to operate. This will also include any type of energy storage

necessary and will not take into account any conventional generation plant. The model will

be simulated in Simulink and using the CIGRE benchmark models.

2.1. Objectives

The objectives of this project are:

- Make a research on Smart grids and microgrids, focusing on the challenges

present on their security and reliability.

- Implement two medium voltage grids from CIGRE benchmark on Simulink

and simulate them connected to the grid, in order to demonstrate the

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problems that can happen in this type of system.

- Implement a microgrid on the previous system which generates all the

necessary power to the system.

- Implement a control management device that regulates the connection

between both grids and solves all the problems present in a typical grid.

- Propose different devices in order to counter all the previous problematic

situations.

2.2. Range

From the previous objectives some of them were accomplished and the others will be left as

ways of continuing the work done in this project.

- A research on microgrids, smart grids and voltage source converters was done in

other to show the reader the different options present on this field.

- The CIGRE grid was modelled and simulated in Simulink thanks to the Simscape

library.

- The microgrid has been implemented generating power to the system but not all the

necessary, this is one of the lacking points of the system.

- The control management implemented is a voltage source converter that has

successfully connected both systems in order to operate together

- The devices that can be used in order to counter the problems that may appear have

not been mentioned, this is one of the lacking points of the system.


3. State of art

In this project different theorical aspects will be treated but basically we can distribute them in

the following topics: smart grids, distributed generation in microgrids and the CIGRE

benchmark. All these topics are important in order to understand the way the system

proposed works and is necessary to know what other researchers have found about them

and try to continue or adapt their work while using the data they have obtained through the

research.

3.1. Smart grids

The existing world power system was built following the principles of the beginning of the last

century, with large central generators that supply electric energy through a high voltage grid

that interconnects the consumers with the producers at long distances using a series of step-

down transformers. The main characteristics of these grids are:

- Centralized generation

- One-way communication

- Unidirectional flow of energy between producers and consumers

- Manual testing, control and reset

- Electromechanical hierarchy structure

As the population grows and the civilized areas increase, it also repercussions in the

electricity demand which increases exponentially and the recent years has had an increase

of about a 5% per year. This, added to the fact that a significant part of the transmission and

distribution grid equipment has more lifetime than the one expected when it was designed,

requiring both replacement and modernization, changing like-for-like but also using new

elements in order to minimize the power losses.[1]

When talking about modernization and optimization of the actual network, the concept of

smart grid appears as an opportunity. Since 2005 the smart grid development has suffered

and increasing interest because of the implementation of information and communication

technologies. This aspect of the smart grid allows us to automatically control it helping with

the decarbonization of our World as it allows to connect different renewable generation

points together with storage helping with the monitorization of this type of energy.[2]

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3.1.1. Smart grid characteristics

In order to define a smart grid, we can not find an exact definition because there is a vast

array of them and no one is universally accepted. We could say as a general definition that a

smart grid is an intelligent electrical network that employs information, two-way cyber-secure

communication technologies and computational intelligence in an integrated way across the

whole range of the energy system from the generation to the end points of electricity

consumption. It involves the use of up-to-date digital technologies, multi-tariff meters and

power distribution devices that ensure the reliability and transparency of the processes of

energy production, transmission, distribution and consumption. In the following picture from

IEA done in 2011 the change from old to new electricity network model is shown. [1]

The International Energy Agency presented eight different features that describe a general

smart grid:[3]

1. Wide area monitoring and control: Intended for monitoring, control and optimization of

the power system over large geographic area, avoiding power supply disruptions and

outages and facilitating the integration of renewable energy sources.

2. ICT integration: Aimed to achieve real-time, two-way communication for more

effective energy management.

3. Integration of renewable energy resources and distributed generation: Extension of

the generation capacity of the power system through additional photovoltaic arrays,

wind farms, geothermal and biomass energy sources, etc.

4. Transmission enhancement applications: Application of advanced technologies to

enhance the transfer of power, reduce transmission losses, minimize chances of

Fig. 3.1. The process of smart grid’s evolution. Source: IEA 2011.


overloading, improve controllability of transmission networks.

5. Distribution grid management: Combines sensing and automation technologies to

continuously maintain voltage levels, detect and locate faults, control DERs, and

reconfigure grid’s topology to ensure optimal operation of equipment and to avoid

outages.

6. Advanced metering infrastructure: Installation of smart meters and network

infrastructure to transmit data from consumers to the utility, software to proceed the

received data.

7. EV charging infrastructure: Connection of EVs to the grid for battery recharging and

electric energy exchange with the system during peak hours, handling of billing

functions.

8. Customer-side systems: Integration of automation systems to control a customer side

e.g. installation of the network sensors to monitor the power consumption from

heating, air conditioning, lightning and other household appliances, using of demand-

response hardware.

The span of these different features varies depending on the type, embracing the entire grid,

from generation, through transmission and distribution, to various types of consumers. These

different spans are shown in the following picture:[3]

Fig. 3.2. The span of smart grid technology facilities through the grid.

Source: Markovic.

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3.1.2. Smart grid challenges

There are a big number of challenges involved in the implementation of smart grids around

the world. A large number of countries do not have the resources and the previously well-

placed infrastructure to accommodate the needs of the distributed generation plants, also, it

would be an enormous investment for those countries. Some researches have been done in

countries like Brazil or India discussing this challenge.

Apart from this, another big challenge for the Smart Grids is the interoperability, that is what

defines and sets the interconnections, interfaces, requirements and technical standards for

the deployment of smart grid technology. So, in order to ensure a good quality in the

communication and operation of all power system devices, a good level of interoperability

has to be achieved. This is a problem when talking about smart grids because different

complications can arise because of the different distributed energy resources having

completely different operating characteristics or some renewable resources like wind or solar

that depend on the weather.[4]

As it has been introduced in the previous paragraph, renewable resources represent another

challenge for the smart grid system. Sources like wind and solar depend exclusively on

weather conditions, so, an efficient energy storage is required. Using renewable energy

based distributed generation the protection of our smart grid may be affected; it is a

challenge to operate the smart grid and monitor its protection under dynamic network

condition. [5]

3.1.3. Smart grid security

A smart grid has to have a very strong communication infrastructure in order to operate and

control properly the system, this fact makes security one of the main technical challenges.

Internet of Things has emerged as one of the enabling technologies for a smart grid, causing

problem because of the interconnectivity of so many devices. This makes improving the

cyber security a never-ending challenge with three main objectives: Confidentiality, integrity

and availability. Until now most of the research done to increment the efficiency and reliability

of smart grids involve using machine learning and datamining techniques together with

protection devices, Wide Area Monitoring Protection and Control used for protection, IEC

61850 based protection systems and mainly adaptative protection techniques, built upon

traditional methods. [6]

The classical protection techniques can be divided into three categories: Overcurrent

protection, distance protection and differential protection. The overcurrent relay is the most

commonly used equipment in power systems in order to protect the grid. It basically opens

the grid circuit when an overcurrent happens, sending a signal to the circuit breaker to open.


They usually happen because of a short circuit in the line resulting in currents larger than the

load current, generating this fault on the system. A differential relay detects a fault when the

phasor difference and magnitude of the current flowing in and out an element of the system

is inequal. Finally, distance protection is the most commonly used protection relay in

transmission lines, where the relay operates with respect to fault impedance of the

transmission line.[4]

3.1.3.1. Adaptive protection

Adaptive protection is a protection philosophy which permits and seeks to make adjustments

to various protection functions, in order to make the more adequate for power system

conditions. This is not a new philosophy as Horowitz et al [7] presented more than three

decades ago results of a research into the possibilities of using digital techniques to change

the transmission system accordingly to the power system changes.

3.2. Microgrids

The system of this project will be energetically supplied by a microgrid connected through

transformers and converters to the other two grids. The trend of using microgrids as entities

that coordinate the distributed energy resources in a more decentralized way has been

motivated in the recent years by the need to improve resilience and reliability of power

systems, reduce greenhouse gases emissions and mitigate climate change.

A microgrid basically consists of distributed generation, energy storage systems and different

loads at the same voltage level. The main benefit from a network point of view is that

microgrids can be treated as controlled entities and may be considered also aggregated

loads. Moreover, the use of microgrids reduce the line losses and interruption costs and are

beneficial from a customers’ point of view since they can improve reliability and efficiency

while reducing blackouts.[8]

There are some microgrids that have been successfully implemented in the USA, Japan,

Korea, Spain, Finland and Germany but their widespread implementation is still limited

because of technical challenges. The most important one is the protection and security of the

system to all the disturbances present in a normal grid, basically overvoltages due to different

phenomena. Then the real challenge for the protection devices is to isolate as quick as

possible any element of the system when it is subjected to any of these problems that can

cause damage to the grid.

When integrating all the elements into a microgrid, traditional schemes may not operate

properly due to different issues like the topological changes in the power grid due to the

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nature of the distributed generation resources, bidirectional power flows, changes in fault

currents and basically the different types of distributed generation and their dynamic

behaviour.[5]

3.2.1. Microgrid structure

A microgrid can be considered a local system of power and energy delivery to individual

consumers that typically consists of a set of elements such as distributed generators, energy

storage systems, a communication infrastructure, loads and a central controller. This last one

is responsible for the central control and management of the microgrid and has several

functions while heading the hierarchical control system, whose second hierarchical control

level is composed of unit controllers located at loads and sources. The following picture

shows a traditional scheme for a microgrid.

The power generation in microgrids may be either a direct current or alternating current

supply, depending on the type of energy sources used. If the generation is in AC, then the

generated power is rectified to DC and integrated to the grid through a Voltage Source

Inverter controlled by Pulse Width Modulation technique. This results in a microgrid being a

perfect solution to manage local generations and loads as microgrids can potentially increase

the system power quality, efficiency and security for critical loads.

Fig. 3.3. Example of a microgrid structure. Source: Barra et al.


A microgrid can be a single or three-phase system, connected to the medium or low voltage

and can operate in two different operational modes: connected or islanded. During grid

connected mode, the microgrid receives power from both the utility and from the generation

sources connected to the system. Under grid connected mode, major portion of the real

power required for the load is met by the distributed connected to the system and the

remaining portion and variation in the real power demand are met by the grid. During

islanded mode, load and generation experiment a shedding in order to maintain the power

balance and the critical loads are made to undergo load shedding.[4]

3.2.2. Challenges in microgrid protection

There are many reasons that make microgrids unstable like their dynamic characteristics,

their intermittent nature or the changes in fault current. Additionally, the topology of a

microgrid can be mixed, looped or meshed and they have bidirectional flows. The challenges

in microgrid protection that should be highlighted and will be discussed are:

- Changes in fault currents

- False tripping

- Blinding of protection

- Unsynchronized and automatic reclosing

3.2.2.1. Changes in fault currents

The changes in fault currents have a strong dependence on existing short-circuit sources in

the system. This short-circuit level is higher in transmission and distribution systems than in

the small distributed generation sources that may be connected to the microgrid. This means

that when the microgrid is working in islanded mode the fault current seen by protective

devices will be much smaller than the fault current seen when the microgrid is operating in

grid-connected mode. Apart from the operation mode the fault current level depends on the

type, control, placement, power rating and quantity of distributed generation units in the

microgrid. [4]

3.2.2.2. Blinding of protection

This phenomenon occurs when the fault current is detected by the security relay and

changes due to the connection of a distributed generation unit that can imply the

misoperation of protective devices upstream or downstream the affected relay. In order to

understand better the blinding of protection it can be considered the grid presented in Fig 4.4.

In this grid, for a fault current F1 the current detected by the overcurrent relay R3 trips the

relay and it can also trip erroneously the overcurrent relay R2 as its current is also increased

because of the presence of a distributed generation unit. In this case it’s commonly said that

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the relay R2 is blinded to the fault.[4]

3.2.2.3. False tripping

False tripping is another typical situation in microgrids that happen when a protective device

connected to a feeder responds to a fault current occurring in an adjacent feeder because of

the connection of distributed generation units. Referring again to the Fig. 4.4, when the fault

current F2 happens, the presence of the distributed generation unit can overcome the pickup

current of the overcurrent relay R1 leading to a false trip depending on the settings of both R1

and R4.[4]

3.2.2.4. Unsynchronized and automatic reclosing

When a distributed generation system is connected to the grid by a recloser, the

synchronism between the unit and the grid needs to be considered. If this connection occurs

not taking into account the synchronism between both systems, overvoltages, overcurrents

and large mechanical torques may occur. [4]

3.3. CIGRE Benchmark

In 1991, Szechtman and Wess elaborated a first approach of the CIGRE HVDC benchmark

model presented as a common reference for HVDC control studies. This benchmark allows

the user to find the best layout that fits all needs, because in order to cover all the spectrum

of studies pertinent to the integration of DER and renewable energy resources, a

Fig. 3.4. Hypothetical grid with two different branches and two current faults.

Source: Barra et al.


comprehensive set of benchmarks was developed. The main aim of this benchmark is to

divide the electric power system until all levels of detail that are of interest for the evaluation

of the integration of renewable and distributed energy resources are reached.

Generally, an electric power system is described by its underlying network structure and the

resources connected to its nodes. In order to study the integration of renewable sources as

distributed generation in electric systems, the resource-side benchmark may be used as

many of the techniques for the implementation of this technology rely on resource-side

control and power electronic conversion.[9]

The medium voltage distribution network used in this project is extracted from this CIGRE

benchmark on its European configuration which is summarized in these points:[9]

• Structure: European MV distribution feeders are three-phase and either of meshed or

radial structure, with the latter dominating rural installations. The benchmark allows

flexibility to model both meshed and radial structures. Each feeder includes

numerous laterals at which MV/LV transformers would be connected. The nominal

voltage is 20 kV. The system frequency is 50 Hz.

• Symmetry: Efforts are typically made to balance the various low voltage laterals

along the MV lines, but some unbalances are still typically experienced in practice.

Unbalance is not explicitly included in the European benchmark, but it can be

Fig. 3.5. Hierarchy for identifying benchmarks.

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introduced if desired. Section 6.3 on flexibility provides further information.

• Line types: Overhead lines are used with bare conductors made of aluminium with or

without steel reinforcement, i.e. A1 or A1/S1A. Underground cables are XLPE with

round, stranded aluminium conductors and copper tape shields.

• Grounding: The grounding of the MV network largely depends on regional

preferences. European networks are typically ungrounded or impedance-grounded.

3.4. Voltage source converter

One of the most important parts of this project is the device that will connect the two

differentiated parts of the system, the inverter. Normally inverters are classified regarding the

kind of semiconductor used:

• Inverters based on Insulated-Gate Bipolar Transistors or similar technologies that can

provide fast switching and modulate any desired voltage. The resulting converters

are the so-called Voltage Sourced Converters which can control independently active

and reactive power, can provide black start capability and inject reduced harmonic

currents allowing to use lighter filters. The high switching frequency at which they are

operated implies higher losses, which is the main drawback of this technology.

• Inverters based on thyristor or similar technologies that require the grid to be

operated. The resulting converters are the so-called Line Commutated Converters

which can control active power while consuming noncontrollable reactive power,

require the grid to be operated and require large filters for the important harmonic

currents they generate. The main advantage is that they are available for higher

voltage and power and that they produce less losses since they commutate at low

frequency.

The most important part of power converters is the control as it assures a correct output of

the system. The main used control techniques for converters are feedbacks controllers

because they present several advantages compared to open loop-controlled converters. The

better security against disturbances on the grid and to different operation points and the fast

response and higher stability have proven necessary in most applications and have made

feedback control almost unavoidable.

In this project the control technique used is a linear control technique that is based on the

averaged model of the converter, which considers the control action to be able to change

continuously despite the discrete number of possible switching states of the converter. This

type of control uses a pulse width modulation technique, such as the sinusoidal PWM or the

space vector PWM, to transform the voltage output reference from the current controller into

the switching signals sent to the actual converter switching devices. The data received from


the controller output is usually treated with a transformation matrix like the so known Park

reference transformation matrix. Thanks to this transformation, both voltage and current

magnitudes become constant in steady state under grid balance conditions, making it

possible to use the classical proportional integrator regulators on the control part of the

system. For unbalanced conditions, some authors suggest to use an enhanced double

synchronous reference frame, using the Clarke transformation instead, changing the system

to a stationary reference frame which requires proportional resonant regulators but enables

proper operation of the system under such condition. In the following points the operation

mode of a voltage source converter will be explained.[10]

3.4.1. Clarke transformation

In order to apply the instantaneous power theory, the electrical quantities expressed in the

abc reference frame have to be expressed in the αβ0 orthogonal reference frame, using the

Clarke transformation that can be defined as:

[𝑥𝛼𝛽0] = [𝑇𝛼𝛽0][𝑥𝑎𝑏𝑐]

[

𝑥𝛼

𝑥𝛽

𝑥0

] =2

3

[ 1 −

1

2−

1

2

0 −√3

2−

√3

21

2

1

2

1

2 ]

[

𝑥𝑎

𝑥𝑏

𝑥𝑐

]

Once the control theory is applied, the electrical quantities are required to be again in the abc

reference frame, so the inverse matrix multiplication is done:

[𝑥𝑎𝑏𝑐] = [𝑇𝛼𝛽0]−1[𝑥𝛼𝛽0]

[

𝑥𝑎

𝑥𝑏

𝑥𝑐

] =

[

1 0 1

−1

2−

√3

21

−1

2

√3

21]

[

𝑥𝛼

𝑥𝛽

𝑥0

]

This transformation is graphically expressed at the Fig 4.6 where the voltage in the abc

reference frame is changed to the αβ0 orthogonal reference frame.

(1)

(2)

(3)

(4)

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3.4.2. Park transformation

Despite having the electrical variables in the αβ0 reference frame, in order to design the

control part of the system the electrical quantities have to be constant and not oscillating as

the αβ0 frame that has the same nature than the abc frame. Here appears a third reference

frame on which the quantities are constant achieved thanks to the Park transformation and

the synchronous reference frame. The Park transformation can be written as:

[𝑥𝑞𝑑0] = [𝑇𝑞𝑑0][𝑥𝑎𝑏𝑐]

Where the transformation matrix is:

𝑇(𝜃) =2

3

[ 𝑐𝑜𝑠(𝜃) 𝑐𝑜𝑠 (𝜃 −

2𝜋

3) 𝑐𝑜𝑠 (𝜃 +

2𝜋

3)

𝑠𝑖𝑛(𝜃) 𝑠𝑖𝑛 (𝜃 −2𝜋

3) 𝑠𝑖𝑛 (𝜃 +

2𝜋

3)

1

2

1

2

1

2 ]

Fig. 3.6. Clarke transformation graphically expressed.

Source: Renato Carlson

(5)

(6)


The inverse of this matrix is:

𝑇−1(𝜃) =

[

cos(𝜃) sin(𝜃) 1

𝑐𝑜𝑠 (𝜃 −2𝜋

3) 𝑠𝑖𝑛 (𝜃 −

2𝜋

3) 1

𝑐𝑜𝑠 (𝜃 +2𝜋

3) 𝑠𝑖𝑛 (𝜃 +

2𝜋

3) 1]

As before, this transformation is better understood with the geometrical representation:

3.4.3. Instantaneous power theory

This theory is applicable to balanced voltage systems, in the abc frame the instantaneous

voltages and currents of a balanced three-phase system can be expressed as:

𝑥𝑎(𝑡) = √2 𝑋 𝑐𝑜𝑠(𝜔𝑡 + 𝜙)

𝑥𝑏(𝑡) = √2 𝑋 𝑐𝑜𝑠 (𝜔𝑡 + 𝜙 −2𝜋

3)

Fig. 3.7. Park transformation graphically expressed.

Source: Mathworks

(7)

(8)

(9)

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𝑥𝑐(𝑡) = √2 𝑋 𝑐𝑜𝑠 (𝜔𝑡 + 𝜙 +2𝜋

3)

Then, using the Clarke transformation these quantities can be expressed in the αβ0

reference frame:

𝑥𝛼 = √2𝑋 cos(𝜔𝑡 + 𝜙)

𝑥𝛽 = −√2𝑋 sin(𝜔𝑡 + 𝜙)

𝑥0 = 0

Where x0=0 because the system is balanced. Expressing the voltage and current as phasors

the power expression can be deduced from the three-phase expression:

√2𝑉𝛼𝛽 = 𝑣𝛼 − 𝑗𝑣𝛽

√2𝐼𝛼𝛽 = 𝑖𝛼 − 𝑗𝑖𝛽

𝑆 = 𝑃 + 𝑗𝑄 = 3𝑉𝛼𝛽𝐼𝛼𝛽∗ = 3(𝑣𝛼 − 𝑗𝑣𝛽

√2) (

𝑖𝛼 + 𝑗𝑖𝛽

√2)

From this expression we can deduce the active and reactive power as functions of voltages

and currents in the αβ0 frame.

𝑃 =3

2(𝑣𝛼𝑖𝛼 + 𝑣𝛽𝑖𝛽)

𝑄 =3

2(𝑣𝛼𝑖𝛽 + 𝑣𝛽𝑖𝛼)

The difference between both reference frames can be seen in the following graphs:

(10)

(11)

(12)

(13)

(14)

(15)

(16)

(17)

(18)


In the synchronous reference frame, the angle ϴ is used in the Park transformation in order

to obtain constant steady state quantities that can be expressed replacing the electrical

voltage angle ϴ=ωt+ϕ0 and transforming abc voltages and currents to the qd0 frame,

obtaining:

𝑉𝑞𝑑 =𝑣𝑞 − 𝑗𝑣𝑑

√2

𝐼𝑞𝑑 =𝑖𝑞 − 𝑗𝑖𝑑

√2

In this case, the power of a three phase system yields:

𝑆 = 𝑃 + 𝑗𝑄 = 3𝑉𝑞𝑑𝐼𝑞𝑑∗ = 3(𝑣𝑞 − 𝑗𝑣𝑑

√2) (

𝑖𝑞 + 𝑗𝑖𝑑

√2)

And reordering this expression, active and reactive power can be expressed as functions of

voltages and currents in the qd0 frame:

Fig. 3.8. Example of three-phase voltages in the abc and αβ0 frames.

Source: Egea-Alvarez et al.

(19)

(20)

(21)

Pàg. 26 Memory

𝑃 =3

2(𝑣𝑞𝑖𝑞 + 𝑣𝑑𝑖𝑑)

𝑄 =3

2(𝑣𝑞𝑖𝑑 − 𝑣𝑑𝑖𝑞)

In this case the voltages can be represented as:

3.4.4. General control scheme

A voltage source converter allows us to control the active and reactive power of two different

electrical variables. The reactive power reference is usually obtained from the grid operator

so it will be set to a value of 0 in this project. In renewable energy systems like the microgrid

of this work, the active power reference depends on the nature of the source connected in

the DC side. In our case, for a renewable energy system, it is adjusted to regulate the DC

bus voltage and to ensure the power balance. In this case the general control scheme is:

Fig. 3.9. Example of three-phase voltages in the abc and qd0 frames.

Source: Egea-Alvarez et al.

(22)

(23)


3.4.5. Current loop control

The current loop is the essential structure for a voltage source converter control as it permits

the regulation of the current flowing through the converter towards the grid.

There are two different control approaches in order to control the q and d components of the

current:

• Multivariable control, using a single two-dimension controller to manage both of them.

• Decoupling and independently controlling q and d components in the synchronous

reference frame.

In this project, the second approach will be used, so a decoupling of the voltages is required:

[𝑣𝑙𝑞

𝑣𝑙𝑑] = [

−𝑣𝑙𝑞 + 𝑣𝑧𝑞 − 𝑙𝑙𝜔𝑒𝑖𝑙𝑑−𝑣𝑙𝑑 + 𝑙𝑙𝜔𝑒𝑖𝑙𝑞

]

where 𝑣𝑙𝑞 and 𝑣𝑙𝑑 are the outputs of the current controllers and 𝑣𝑙𝑞 and 𝑣𝑙𝑑 are the voltages

to be applied by the converter. Substituting in the voltage equations:

Fig. 3.9. Grid converter control general scheme for renewable energy

generation systems. Source: Egea-Alvarez et al.

(24)

Pàg. 28 Memory

[𝑣𝑙𝑞

𝑣𝑙𝑑] = [

𝑟𝑙 00 𝑟𝑙

] [𝑖𝑞𝑖𝑑

] + [𝑙𝑙 00 𝑙𝑙

]𝑑

𝑑𝑡[𝑖𝑞𝑖𝑑

]

Applying the Laplace transformation, the transfer function between the controller voltages

and converter currents can be derived as:

𝑖𝑞(𝑠)

𝑣𝑙𝑞(𝑠)=

1

𝑙𝑙𝑠 + 𝑟𝑙

𝑖𝑑(𝑠)

𝑣𝑙𝑑(𝑠)=

1

𝑙𝑙𝑠 + 𝑟𝑙

The constants for the proportional integrator can be calculated as:

𝐾𝑝 =𝑙𝑙𝜏

𝐾𝑖 =𝑟𝑙𝜏

Where the 𝜏 is the closed loop time constant of the electrical system that must be chosen

considering the converter physical restrictions. The implementation of the overall current

controller is:

Fig. 3.10. Current controller. Source: Egea-Alvarez et al.

(25)

(26)

(27)

(28)

(29)


3.4.6. Phase locked loop

A phase locked loop or PLL is used to determine the angle and the angular velocity of the

electrical network. A three-phase PLL consists in a feedback of the d-axis voltage component

filtered by a PI controller. The output of the controller corresponds to the angular velocity of

the electrical grid and the integration of this signal corresponds the grid angle. A typical PLL

scheme is following:

The function Kf(s) of the PLL can be defined as:

𝐾𝑓(𝑠) = 𝐾𝑝 (

1𝜏𝑃𝐿𝐿

+ 𝑠

𝑠 )

Where 𝜏𝑃𝐿𝐿 is the PLL constant.

3.4.7. DC voltage regulator

In this system, the DC voltage regulator is required in order to control the voltage of the DC

bus ensuring power balance between the two sides of the converter, one in AC and the

other in DC. The proposed control scheme is sketched as:

Fig. 3.11. Phase locked loop scheme. Source: Egea-Alvarez et al.

Fig. 3.12. DC voltage regulator scheme. Source: Egea-Alvarez et al.

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Pàg. 30 Memory

The proposed control scheme is sketched in Figure 13, where it can be seen that the

controlled quantity is E2 and a feed-forward scheme is used to improve the system response.

This is a common practice, since E2 is proportional to the energy stored in the capacitor, and

the output of the controller is the active power injected to the capacitor P*C. Therefore, the

power reference for the power converter will be P* = P*C +PDC, where PDC is the measured

power before the capacitor.

The P controller will be modelled following the equation:

𝐾𝑝𝐷𝐶 =𝐶

2𝜏𝐸

(31)


4. Case study: DC microgrid implementation

In the case study of this project a microgrid will be designed in order to supply the energy

required by two medium voltage AC grids interconnected. First of all, the two grids will be

defined together with their lines, loads and transformers parameters and then the microgrid

will be implemented concentrating all the generation and connected to the previous two

through a controller. After that, different tests will be done to the system in order to assure a

normal operation. All these simulations are done with Simulink, especially with the

Simscape’s electrical library.

4.1. Grid’s data

In this section the different parameters of the multiple parts of the system will be shown, all

this data is extracted from the “Benchmark systems for network integration of renewable and

distributed energy resources” file from CIGRE. The topology of the European version of the

MV distribution network benchmark is shown in the following scheme:

Fig. 4.1. Original grid layout. Source: CIGRE benchmark

Pàg. 32 Memory

In a first approximation of the model, the switches S1, S2 and S3 are considered lines and

this grid is supposed to be connected to a high voltage grid, so there’s no generation

included in both medium voltage grids as it is supposed to be in a DC microgrid connected in

S1.

Overhead lines are mounted on towers without neutral wires, and underground cables are

tape-shielded and buried in back-filled trenches with a protective plate. The network topology

and line lengths of the network are described in the following table:

In order to implement the line into Simulink three parameters are required in their positive

and zero sequence: resistance and reactance, given by the CIGRE benchmark, and

capacitance. Taking into account the previous data the capacitance of each line is given as:

𝐶 =𝐵′

𝜔

The value of the positive and zero sequence for the capacitance of the first 12 lines is

9,52·10-9 F/km, the value of the positive sequence for the last three lines will be 1,01·10-8

F/km and the zero sequence 4,07·10-9 F/km.

Once the data of all the lines is defined the loads have to be implemented. Each bus will

have a load with the following data:

Line segment

Node from

Node to

R’ph

(Ω/km) X’ph

(Ω/km) B’ph

(µS/km) R’0

(Ω/km) X’0

(Ω/km) B’0

(µS/km) L

(km)

1 1 2 0,501 0,716 47,493 0,817 1,598 47,493 2,82

2 2 3 0,501 0,716 47,493 0,817 1,598 47,493 4,42

3 3 4 0,501 0,716 47,493 0,817 1,598 47,493 0,61

4 4 5 0,501 0,716 47,493 0,817 1,598 47,493 0,56

5 5 6 0,501 0,716 47,493 0,817 1,598 47,493 1,54

6 6 7 0,501 0,716 47,493 0,817 1,598 47,493 0,24

7 7 8 0,501 0,716 47,493 0,817 1,598 47,493 1,67

8 8 9 0,501 0,716 47,493 0,817 1,598 47,493 0,32

9 9 10 0,501 0,716 47,493 0,817 1,598 47,493 0,77

10 10 11 0,501 0,716 47,493 0,817 1,598 47,493 0,33

11 11 4 0,501 0,716 47,493 0,817 1,598 47,493 0,49

12 3 8 0,501 0,716 47,493 0,817 1,598 47,493 1,3

13 12 13 0,510 0,366 3,172 0,658 1,611 1,280 4,89

14 13 14 0,510 0,366 3,172 0,658 1,611 1,280 2,99

15 14 8 0,510 0,366 3,172 0,658 1,611 1,280 2,00

Fig. 4.2. Lines parameters. Source: CIGRE benchmark

(31)


Finally, the transformers data will be:

Node from Node to Connection V1 [kV] V2 [kV] Z [Ω] S [MVA]

0 1 3-ph Dyn1 110 20 0.016+j1.92 25

0 12 3-ph Dyn1 110 20 0.016+j1.92 25

Fig. 4.3. Loads data. Source: CIGRE benchmark

Fig. 4.3. Transformers data. Source: CIGRE benchmark

Apparent power [kVA] Power factor Residential Commercial/

industrial Final data

No

de

Res

iden

tial

Co

mm

erci

al/

Ind

ust

rial

Res

iden

tial

Co

mm

erci

al/

Ind

ust

rial

Act

ive

po

we

r

[kW

]

Rea

ctiv

e

po

we

r [k

Var

]

Act

ive

po

we

r [k

W]

Rea

ctiv

e

po

we

r [k

Var

]

Act

ive

po

we

r [k

W]

Rea

ctiv

e

po

we

r [k

Var

]

1 15300 5100 0,98 0,95 12706,6 8522,4 4148,4 2966,6 16855,0 11489,0

2 0 0 0 0 0,0 0,0 0,0 0,0 0,0 0,0

3 285 265 0,97 0,85 235,1 161,1 199,1 174,9 434,2 336,0

4 445 0 0,97 0 367,1 251,6 0,0 0,0 367,1 251,6

5 750 0 0,97 0 618,7 424,0 0,0 0,0 618,7 424,0

6 565 0 0,97 0 466,1 319,4 0,0 0,0 466,1 319,4

7 0 90 0 0,85 0,0 0,0 67,6 59,4 67,6 59,4

8 605 0 0,97 0 499,1 342,0 0,0 0,0 499,1 342,0

9 0 675 0 0,85 0,0 0,0 507,1 445,5 507,1 445,5

10 490 80 0,97 0,85 404,2 277,0 60,1 52,8 464,3 329,8

11 340 0 0,97 0 280,5 192,2 0,0 0,0 280,5 192,2

12 15300 5280 0,98 0,95 12706,6 8522,4 4294,8 3071,3 17001,4 11593,7

13 0 40 0 0,85 0,0 0,0 30,1 26,4 30,1 26,4

14 215 390 0,97 0,85 177,4 121,5 293,0 257,4 470,3 378,9

Pàg. 34 Memory

4.2. Grid model

Once the data is defined the system can be implemented in Simulink, using different blocks

for each type of element. In a first model with only the two grids defined by the CIGRE the

layout is the following:

Fig. 4.5. Grid layout in Simulink. Source: Simulink database


In this model there’s a sensor of voltage and current connected between the 8th and 14th bus

that will be the emplacement of the microgrid. At this point the voltage and current of the

microgrid have values of 2379 V and 14,1 A.

4.3. Wind farm model

Once the both grids are implemented, the following step is the implementation of the different

elements of the microgrid, where basically the power will be generated. In order to create the

wind farm different options where proposed.

4.3.1. First wind farm proposal

The first proposal of wind farm consists in a permanent magnet synchronous machine that

has an input for the mechanic torque that can be generated by a special block of Simscape

named “Wind turbine”, the value is given in pu, so is previously multiplied by the nominal

power of the wind turbine, set in 8,5 kW. The wind farm is composed by default

aerogenerators with the following power characteristics:

Finally, a pitch angle generator is required in order to get the pitch angle of the machine from

its speed, in order to do this the following block is defined:

Fig. 4.6. Turbine power characteristics. Source: Simulink database

Pàg. 36 Memory

The rotor speed is obtained from the permanent magnet synchronous machine as a

parameter in rad/s and then converted in pu. The wind speed is a variable that will be used in

order to simulate different scenarios with different wind rate speed.

The problem of this program was that once the user executes it, the program runs very

slowly probably due to the pitch angle generator that creates algebraic looping.

4.3.2. Second wind farm proposal

The second option proposed involved the Simscape block Wind Turbine Induction Generator

(Phasor type). The wind turbine and the induction generator (WTIG) are shown below. The

stator winding is connected directly to the grid and the rotor is driven by the wind turbine. The

power captured by the wind turbine is converted into electrical power by the induction

generator and is transmitted to the grid by the stator winding. The pitch angle is controlled in

order to limit the generator output power to its nominal value for high wind speeds. In order to

generate power, the induction generator speed must be slightly above the synchronous

speed. But the speed variation is typically so small that the WTIG is considered to be a fixed-

speed wind generator. The reactive power absorbed by the induction generator is provided

by the grid or by some devices like capacitor banks, SVC, STATCOM, or synchronous

Fig. 4.7. Pitch angle controller.

Fig. 4.8. First wind turbine proposal.


condenser.

The advantage of this block is that contains its own pitch controller and the only required

thing is a wind value and a protection system that controls the tripping of the wind turbine.

Once again, this program cannot be used because the analysis of this block has to be done

in phasor type and the rest of the system is in discrete type of analysis. One solution could

be a concurrent execution doing a partition of the model but apart of the complexity of this

procedure it may lead to different problems during the execution of it.

4.3.3. Third wind farm proposal

After trying to do a concurrent execution with the model proposed in the previous section with

no success the decision made is to use a special block designed by Richard Gagnon at

Hydro-Quebec that simulates a doubly-fed induction generator driven by a wind turbine. In

this section this block will be explained together with the description of the layout.

Fig. 4.9. Wind turbine induction generator block and scheme.

Fig. 4.10. Wind turbine induction generator block and scheme.

Source: Hydro-Quebec.

Pàg. 38 Memory

This block contains a subsystem that represents the internal scheme for a wind turbine. The

first important part is the drive train, where the previous mentioned block in first proposal

“Wind Turbine” is used to generate the torque of the wind turbine that is later on treated to

get the torque of the shaft which multiplied by the power base of the generator gives the

mechanical torque.

Where the drive train:

Once the mechanical torque is obtained, the electrical circuit for the representation of the

generator is done as previously, with a wound-rotor induction generator in this case and a

AC-DC-AC converter that regulates the output of the wind turbine:

Fig. 4.11. Turbine and Drive train layout in Simulink. Source: Hydro-Quebec.

Fig. 4.12. Drive train internal scheme. Source: Hydro-Quebec.


Finally, the control part is done all together in another subsystem that will not be explained

because it has several control methods that would occupy lots of pages to explain. The

control contains a grid-side converter control system and a rotor side converter control

system that generate the pulses for the AC-DC-AC converter and a speed regulator and

pitch control for calculating the pitch angle. All these values are previously filtered and

transformed depending on the necessity of every control part. The parameters that define

this wind turbine were selected by looking at the average parameters of a 1,5 MW wind

turbine.

Generator data

Nominal power 1,5/0,9 MW

Line to line voltage 575 V

Frequency 50 Hz

Rs (pu) 0,023

Lls (pu) 0,18

Rr’ (pu) 0,016

Llr’ (pu) 0,16

Lm (pu) 2,9

Inertia constant 0,685 s

Friction factor (pu) 0,01

Pairs of poles 3

Fig. 4.13. Wind turbine internal layout. Source: Hydro-Quebec.

Fig. 4.14. Generator data for the wind turbine model.

Pàg. 40 Memory

Drive train data

Wind turbine inertia constant 0,4 s

Shaft spring constant (pu) 1,11

Shaft mutual damping (pu) 1,5

Turbine initial speed (pu) 1,2

Initial output torque (pu) 0,83

Control data

DC bus voltage Kp 8

Dc bus voltage Ki 400

Grid-side converter current Kp 0,83

Grid-side converter current Ki 5

Speed regulator Kp 3

Speed regulator Ki 0,6

Rotor-side converter current Kp 0,6

Rotor-side converter current Ki 8

Q and V regulator Kp 0,05

Q and V regulator Ki 20

Pitch controller Kp 150

Pitch compensation Kp 3

Pitch compensation Ki 30

Converter data

Maximum current (pu) 0,8

Grid-side coupling inductor: L (pu) 0,3

Grid-side coupling inductor: R (pu) 0,003

Nominal DC bus voltage 1150 V

DC bus capacitor 10000 µF

Line filter capacitor 120 kvar

Wind turbine data

Mechanical power 1,5 MW

Wind speed at nominal speed 11 m/s

Initial wind speed 11 m/s

Fig. 4.15. Converter data for the wind turbine model.

Fig. 4.16. Wind turbine data for the wind turbine model.

Fig. 4.17. Drive train data for the wind turbine model.


Frequency of the grid-side PWM carrier 2700 Hz

Frequency of the rotor-side PWM carrier 1620 Hz

Maximum pitch angle 27°

Maximum rate of change of pitch angle 10°/s

Once the data is all defined, the layout presented in this project consists of 18 turbines,

distributed in groups of 6 turbines each, that will receive different speeds of wind. All this

groups of turbines are connected in parallel to a rectifier that has the following layout:

Finally, the overall wind farm layout is:

Fig. 4.18. Control data for the wind turbine model.

Fig. 4.19. 2-level rectifier layout where 1 and 5 are the DC ports and 2, 3 and 4 the AC ports.

Fig. 4.20. Wind farm of the project layout.

Pàg. 42 Memory

Where the voltmeter and scope connected at the DC side of the rectifier would represent the

connection to the microgrid.

4.3.4. Wind farm simulation

The wind farm simulations started wrong, as the output of the system was purely a voltage

source and the voltage at the wind turbines dropped to 0 once the desired voltage was

reached at the output. Adjusting the values of the rectifier to R=0,5Ω, L=5mH and C=2500µF

and setting a capacitors bank at the input of the wind turbines in the rectifier solved this

problem obtaining the following voltage and current at the wind turbine rotor expressed in pu:

Until T=2s the system is

transitioning to the steady state

and irregular values appear,

when the stability of the system

is reached, it is also reached the

constant voltage output of the

system, that is stepped until it

reaches the value of 16500 V

approximately.

Fig. 4.21. Voltage and current wind turbine output.

Fig. 4.22. Voltage wind farm output.


This is not a desirable output, as the voltage is stepped and irregular at the beginning, also

the voltage at the wind turbines is too much bigger and it could lead to future problems at the

system. In this case the simulation was done with a time step of 0,0001 seconds and a

speed of wind of 10 m/s.

Increasing the speed to the nominal value of 11 m/s leads to a similar form of the voltage of

the turbine, with disturbances for the first two seconds and a half but then reaches a

stabilized mode where the voltage is more correct than it was before as it has a lower value

while the output of the system is almost the same.

Fig. 4.23. Voltage and current wind turbine output with 11 m/s of wind speed.

Fig. 4.24. Wind farm voltage output with 11 m/s of wind speed.

Pàg. 44 Memory

Finally, if the wind speed is lower than 10 m/s, for example 9 m/s, the output of the system is

even better, with no disturbances at the beginning of the simulation in the case of the voltage

and current in the rotor, expressed in pu:

The stabilized mode is reached faster than before and this is also reflected at the voltage

output of the whole system, despite the fact that in this case the voltage doesn’t even reach

the 14000 V value:

Fig. 4.25. Voltage and current wind turbine output with 9 m/s of wind speed.

Fig. 4.26. Wind farm voltage output with 9 m/s of wind speed.


Wind is a meteorological phenomenon that is never constant, having differences on the wind

speed in a small amount of time, so in the following graphs the effect of increasing and

decreasing wind from 6 m/s to 11 m/s will be studied. In the first test, the wind has this form:

With the voltage and currents as expected, first decreasing when the wind speed starts

increasing and then increasing until the stabilized mode.

Fig. 4.27. Wind value increasing from 6 to 11 m/s.

Fig. 4.28. Voltage and current values with an increasing wind speed.

Pàg. 46 Memory

Finally, the output has no abrupt changes, meaning that the system is prepared for changes

in the wind speed:

So, the voltage output doesn’t change until a value near to 11 m/s is reached in the wind

speed, if this wind speed was maintained constant there will be a point where the system

reached the previous output with the 11 m/s wind speed. When the wind speed decreases

instead of increasing, the voltage and current at the wind turbine:

Fig. 4.29. Wind farm voltage output with an increasing wind speed.

Fig. 4.30. Wind turbine voltage and current with a decreasing wind speed.


So, it’s clearly demonstrated that the wind farm operates better with low wind speeds,

offering a good output besides not being operating at nominal speed, thanks to the rectifier

PWM control. When working on these last simulations the capacitors values were changed,

in order to adapt to the differences that could provoke the wind speed changes, the parallel

capacitor at the DC side of the rectifier was changed to C=2200µF and the capacitor bank at

the AC side of the rectifier was changed to a 500 kvar value.

4.4. PV plant model

The implementation of the photovoltaic plant is easier as it exists a specific block that

simulates the operation of a group of photovoltaic panels taking into account two different

variables: irradiance and temperature, but in our case the temperature will not be taken into

account as we consider this block to be a robust discrete model and the temperature has

been internally set to the value of 25°C. Simulink also offers the possibility of choosing a

model of panel that exists in the real market, in the case of this project the model selected is

the SolarWorld Industries GmbH Sunmodule Protect SW 285 mono. Another important data

that has to be introduced is the number of solar panels that exist in the installation that will be

changed for different scenarios in order to change the output voltage and current of the plant.

The layout of the PV plant and the module V-I and P-V characteristics are the following:

Fig. 4.31. PV plant layout.

Fig. 4.32. PV array V-I and P-V characteristics.

Pàg. 48 Memory

The output of this PV plant will be regulated by a maximum power point tracker system or

MPPT, which will provide us the maximum power that the system can achieve by regulating

the voltage and current output of the PV panels. In order to implement this system in

Simulink a MATLAB code is written, with a perturb and observe technique program that will

change constantly the values of the voltage finding the optimal duty cycle. The input

parameters of this program will be provided in the Simulink interface and will be the initial,

maximum and minimum value of the duty cycle and the increment value used to increase or

decrease the duty cycle. Apart from these inputs, the voltage and current will be provided

directly by the system as an input of the function block and another input that will decide if

the MPPT is enabled or not. The voltage, power and duty cycle variables are declared as

persistent variables, which are local to the function in which they are declared, yet their

values are retained in memory between calls to the function. In the first run of the program, if

the voltage variable is empty, the voltage, power and duty cycle are defined in the first

iteration of the program as a value of 0 and the duty cycle as the decided parameter for initial

value. Once these variables are declared the program starts by calculating the difference

between the actual values and the values previously defined. If power and voltage are

decreasing, the duty cycle also decreases, if the power decreases but voltage increases, the

duty cycle is increased. When the power increases and the voltage also increase, the duty

cycle decreases and if the power increases but the voltage decreases the duty cycle is

increased. If the difference of the power is 0 or the duty cycle overpasses the limits set by the

maximum and minimum parameters, the duty cycle is set to be the previous one. The

program code is:

function D = MPPT(Param, Enabled, V, I)

Dinit = Param(1);

Dmax = Param(2);

Dmin = Param(3);

deltaD = Param(4);

persistent Vold Pold Dold;

dataType = 'double';

if isempty(Vold)

Vold=0;

Pold=0;

Dold=Dinit;

end

P= V*I;

dV= V - Vold;

dP= P - Pold;

if dP ~= 0 & Enabled ~=0

if dP < 0

if dV < 0

D = Dold - deltaD;

else


D = Dold + deltaD;

end

else

if dV < 0

D = Dold + deltaD;

else

D = Dold - deltaD;

end

end

else D=Dold;

end

if D >= Dmax | D<= Dmin

D=Dold;

end

Dold=D;

Vold=V;

Pold=P;

A DC-DC boost converter is required in order to control the output of the PV plant, in this

case the PWM control is done directly at the converter and with the duty cycle obtained with

the MPPT program, that enters the block at the input number 1. Inductances and reactances

are added in order to filter the input data and a condenser of 2200 µF and a diode are set at

the output in order to obtain a correct direct current output.

Fig. 4.33. DC-DC boost converter layout.

Pàg. 50 Memory

The overall layout for the PV plant is:

Where “Param” is a block that contains all the parameters listed above and mentioned

previously:

4.4.1. PV plant simulations

In order to assure a correct operation of the PV plant, different simulations where done, with

different scenarios in order to check what are the possible layouts for this system.

4.4.1.1. First simulation

In a first simulation we will vary the number of parallel strings and the number of series-

connected modules per string and see how this affects to the system.

- First scenario: 40 parallel strings and 5 series-connected modules per string

In this scenario, the irradiance is set 1000 W/m2. The voltage and current of the PV modules

are:

Parameter Value

Initial duty cycle (Dinit) 0,485

Maximum duty cycle (Dmax) 0,6

Minimum duty cycle (Dmin) 0,4

Duty cycle step (deltaD) 20·10-6

Fig. 4.34. PV plant and control layout.

Fig. 4.35. Control parameters.


There’s a ripple between 200 and 205 volts and between 15 and almost 0 amperes that is

originated due to the MPPT system. When the MPPT point is found, there’s also an

overvoltage that can be seen better in the output of the PV plant, once the signal has been

treated by the DC-DC boost converter.

As expected, in this scenario the current is lower because there’s a small number of panels

in series in each string. In order to tackle the negative values that may appear in the current

of the photovoltaic power, which could produce damages to the system, another capacitor

with the same value is set in the input of the DC-DC boost converter. Apart from this, to

tackle the overvoltage originated when reaching the point of operation, the values of the

Fig. 4.36. PV plant voltage and current with 40 parallel strings and

5 series-connected modules per string.

Fig. 4.37. PV plant output voltage.

Pàg. 52 Memory

resistor and inductor are defined as R=0,5Ω and H=0,1mH taking into account that the

number of PV panels has to be increased in order to reach a suitable power and voltages

output.

- Second scenario: 100 parallel strings of 60 modules per string.

In the previous scenario only a few kilowatts of power were reached and for our installation

there are required a power of around 1’5 MW, this is the reason why the parallel strings are

increased to 100 and the modules per string to 60. With this layout and the settings changed

at the end of the previous scenario, the voltage and current at the PV plant is:

As the current signal has a very high ripple, the settings of the RL branch and capacitor have

to be changed. Now, the capacitor will be of a value of C=9100µF and the inductance

L=0.07mH. With these parameters the value of power is 1638 kW and the voltage and

current outputs are:

Fig. 4.38. PV plant voltage and current with 100 parallel strings

and 60 series-connected modules per string.

Fig. 4.39. PV plant voltage and current with 100 parallel strings and 60

series-connected modules per string and arranged RLC values.


In this case we have an optimal output with a ripple in the current with values between 800

and 840 A and a voltage with a very low ripple. By the way, all these ripples are mitigated

through the DC-DC boost converter, which output is:

Finally, the voltage output value is 6000 V and this will have to be later adapted to the

voltage of the microgrid which has not already been decided.

4.4.1.2. Second simulation

In the second round of simulations, the duty cycle ranges will be analysed in order to know if

the actual ranges are correct. In the previous simulations, the duty cycle that helps to reach

the steady state is 0,5. In this

simulation the initial state for the duty

cycle will be set to 0,5 directly and the

difference between the voltages of

different cycles (DeltaDC) will be

changed to 50·10-6.With these

changes, the output signal of the

voltage of the system is smoother than

previously as the duty cycle is already

defined correctly at the beginning of the

simulation.

Fig. 4.40. PV plant final output of the first round of simulations.

Fig. 4.41. PV plant final output of the

second round of simulations.

Pàg. 54 Memory

4.4.1.3. Third simulation

In this last round of simulations, the solar data will be changed in order to not make it

constant and at 1000 W/m2 as it was before, testing more reasonable scenarios and looking

how the changes affect to the system.

- First scenario: Irradiance decreasing from 1000 to 500 W/m2.

In this case, in a simulation of 10 seconds, the decrease is done between t=2 s and t=7 s.

What this decrease on the irradiance causes to the voltage and current of the PV plant is

also a decrease on their values, decreasing the average power of the simulation from the

previous 1638 kW to 779,3 kW.

Fig. 4.42. Sun irradiance for this simulation.

Fig. 4.43. PV plant current and voltage output with a decrease on the irradiance.


When the irradiance is lower, the system offers an output with less ripple than previously due

to the lower levels of voltage in respect to the parameters of the capacitors and RL branch of

the DC-DC boost converter. Finally, the output voltage of the system will be:

- Second scenario: Irradiance increasing from 500 to 1100 W/m2.

In this case two things were important to test, how the system responds when starts working

with less irradiance and how responds when this irradiance is higher than the nominal value

of 1100 W/m2. The irradiance in this case is:

The PV plant has a perfect adaptation to the 500 W/m2 irradiance, offering an output with no

ripples. When the irradiance increases, the ripple increases with it, but the average power of

Fig. 4.44. PV plant output voltage with a decrease on the irradiance.

Fig. 4.45. Sun irradiance for this simulation, with an increasing value.

Pàg. 56 Memory

the PV plant in this case is 1714 kW, so, the increase of the irradiance above the nominal

one, generates more power at the expense of having a greater ripple at the PV plant voltage

output:

Also, there’s an abrupt change on the voltage and current values at t=3 s, just right before

the ripple starts, so this is the point where the RL branch and capacitors values are

undersized in order to not decrease the output, despite having ripple. At the current graph it

can also be appreciated how the ripple has a higher value when the irradiance is over 1000

W/m2.

In a last round of simulations, the Sun irradiance was increased to unreachable levels like

Fig. 4.46. PV plant voltage and current output with an increasing irradiance.

Fig. 4.47. PV plant output with an increasing irradiance.


1500 W/m2 and the ripple of the voltage plant and system output is constant but the ripple of

the current increases with the irradiance, so this fact is demonstrated. Finally, it was also

checked that for low power values the duty cycle was 0,4 and for big power values the duty

cycle was 0,5. The ranges of the duty cycle could be stretched but in order to overcome

possible overvoltages due to hot spots or operation problems the levels are maintained as

before.

4.5. VSC control model

At this point of the project, the original CIGRE grid and the project’s microgrid have been

defined and now is time to connect both of them. In order to do this operation, a voltage

source converter has to be implemented. The principal theorical aspects of this device have

been explained in the State of the Art of this work, so at this point the programming of this

part in Simulink will be explained. The general scheme of the voltage source converter is:

The Vzabc and Iabc values will be extracted through a block called Three-Phase V-I

Measurement from the grid part of the system, at the point of connection with the microgrid.

The voltage is then treated with Clarke and Park transformations in order to obtain the values

Fig. 4.48. Grid converter control general scheme for renewable energy

generation systems. Source: Egea-Alvarez et al.

Pàg. 58 Memory

in the qd0 plane:

In this block, called “Clarke + Rotation”, the value of the Vzabc vector is multiplied by the

Clarke matrix, defined in the theorical part of the project and previously multiplied by the

theta matrix or rotation matrix doing the Park transformation and obtaining the voltage in the

qd0 plane. This theta is obtained thanks to a phase locked loop or PLL with the following

scheme:

The Vzd value is obtained from the previous block, closing in this way the loop between them.

The reference value or Vzd_ref is 0. The values for the PI controller will be calculated lately.

Fig. 4.49. Clarke and Park transformations modelled in Simulink.

Fig. 4.50. PLL block that helps obtaining the theta value.


With the same theta we obtained previously we can obtain the values of the Izabc parameter in

the qd0 plane and then implement a current loop control with the iq, id and Vzq values.

Finally, the final Vzabc of reference is obtained through the multiplication of the vector Vlqd0 by

the Theta inverse matrix that is programmed in a similar way than the original theta matrix:

Fig. 4.51. Current loop control layout.

Fig. 4.52. Theta inverse matrix Simulink implementation.

Pàg. 60 Memory

The general layout of the voltage source converter control part is:

This would be a typical voltage source converter modelled taking as reference the grid side

values but in the system of this project there’s presence of renewable energies and the

microgrid working in direct current mode, so it’s necessary to also know the values of the

microgrid side. In order to do this a DC voltage regulator as the one explained in the theorical

part of the project needs to be implemented and it will help to obtain the iq* parameter. At the

current loop, the iqref that was previously set as 200 A value, will be changed by an inport in

order to receive the output of the DC regulator. This DC regulator is modelled as:

Fig. 4.53. General layout of the voltage source converter control part.

Fig. 4.54. DC regulator layout in Simulink.


Finally, the voltage source converter layout with the DC voltage regulator is:

4.5.1. VSC simulation

Once the voltage source converter is modelled, in order to simulate this part of the system a

three-phase source will be implemented simulating the grid and current source together with

a capacitor of value C=4700µF that will simulate the microgrid. The layout of this simulation

is:

Simulating this layout brought problems because of the controlled current source, that was

changed by an alternating current source that connected in parallel with the capacitor will

give us an output similar to the one of the microgrid. So, the voltage at the microgrid side is:

Fig. 4.55. Voltage source converter control part with DC voltage regulator.

Fig. 4.56. Layout for the simulation of the voltage source converter.

Pàg. 62 Memory

And the voltage at the grid side, generated by the three-phase source block is:

It is clear that the disturbance at the beginning of the simulation in the microgrid side, that

also happens in the simulation of the PV plant and wind farm, leads to a disturbance at the

beginning of the simulation at the grid side, which means that the system works correctly, as

a disturbance on one side affects to the other side. The tests that have to be done in this

case are related with overvoltages and phase short-circuits, so, in a first test, the microgrid

Fig. 4.57. Microgrid side voltage output.

Fig. 4.58. Grid side voltage output.


will be modelled to have different overvoltages at some point of the simulation.

- First test, disconnection of the microgrid for 0,1 seconds at time 3 seconds.

In this case the microgrid is disconnected for 0,1 seconds and the response during this time

at the grid side is:

There is a slight increase on the voltage but only of one of the phases, while the other

phases remain equal and not affected, it is clear now that the system operates correctly.

- Second test, disconnection of the grid for 0,1 seconds at time 3 seconds.

This disconnection does not affect to the microgrid side as it is a independent current source

connected to a capacitor so it continues working. At the grid side, the recovery of the system

when the fault has passed is:

Fig. 4.59. Grid side voltage in case of disconnection of the microgrid.

Fig. 4.60. Grid side voltage in case of disconnection of the grid.

Pàg. 64 Memory

The voltage drops to 0 but it instantly recovers once it has passed the fault, originating only a

small overvoltage. This decrease on the voltage is reflected in the current, which increases a

lot during the 0,1 seconds of fault, resulting in a dangerous overcurrent that may lead to

problems in the devices connected to the grid if they are not prepared for this type of error.

During the rest of the simulation the currents at both sides are very small, a desirable fact

when a system of this magnitude is modelled. More tests can be implemented at the voltage

source converter, but it will be done with the all system already connected.

4.6. Microgrid model

The general layout of the microgrid, where the outports 1 and 2 indicate the connection with

the voltage source converter is:

Fig. 4.61. Grid side current in case of disconnection of the grid.

Fig. 4.62. Project’s microgrid layout.


4.7. System simulation

The whole system implemented is the following:

On a first simulation, assuming a constant wind of 9 m/s and a constant irradiance of 1000

W/m2 the voltage and current at the interconnection point of the grid with the microgrid is:

It can be observed that as it happened before, the system has a small overvoltage and its

correspondent undercurrent in the beginning of the system, probably due to the start of

operation of the PV plant. The system works correctly in steady state and now different tests

will be done in order to know if the voltage source converter operates correctly. In a first

simulation, it is supposed that the feeder number 2 is disconnected for a few milliseconds

and then reconnected. The voltage at this point:

Fig. 4.63. Project’s system layout.

Fig. 4.64. Voltage and current at the interconnection point.

Pàg. 66 Memory

It is now clear that the voltage source converter works really well, offering a very short

transitionary state when disconnecting the feeder and low levels of overvoltages when it is

reconnected. The only problem at this point is the high levels of current that the system will

have and that could be dangerous for the system if it is not protected.

When the feeder 1 is disconnected, the same effect is produced but in different levels

because of the difference of load between both feeders.

Fig. 4.65. Voltage at the interconnection point when the feeder number 2 is disconnected.

Fig. 4.66. Current at the interconnection point when the feeder number 2 is disconnected.


When the microgrid is disconnected, the system receives less power but it continues

operating with less voltage but more current in order to maintain the same power as

previously. For example, the voltage and current on the second feeder:

In this case the disturbances or overvoltages are not very important because the grid helps

recovering from the fault.

Finally, another typical problem that may occur is the disconnection of one of the phases

probably produced by the impact of a lightning for example. In this case, considering the

same time of disconnection as before but only for the phase A, the voltage and current at the

Fig. 4.67. Voltage at the feeder number 2 when the microgrid is disconnected.

Fig. 4.68. Current at the feeder number 2 when the microgrid is disconnected.

Pàg. 68 Memory

second feeder is:

Once again, the system works adequately to what is required as it overcomes the reduction

of voltage of the first phase and also it overcomes the diphase produced in the current,

obtaining again a perfect output once the fault has passed.

Fig. 4.69. Voltage at the feeder number 2 when there is a fault on the phase A.

Fig. 4.70. Current at the feeder number 2 when there is a fault on the phase A


Conclusions

To conclude with the work done in this project, there are different points that can be

commented that have been worked in this paper. First of all, on the theorical part of the

project different techniques and devices related with protection of smart grids and microgrids

have been presented, together with a clear definition of Smart Grid and their importance in

the future. Also in this part, the CIGRE benchmark has been presented which is a great help

when doing this type of researches. Finally, to close the theorical part, the voltage source

converter theory has been explained which may seem difficult but once implemented in

Simulink becomes more friendly to the user.

In the practical part the CIGRE medium voltage grid has been implemented in Simulink, by

using the Simscape library and a further work in this way could be doing the same but with

high voltage or low voltage grids. Next to this, the microgrid was implemented, which is the

part that has brought more difficulties to the system, especially the wind farm, as there was

not a specific block for simulating a wind turbine in discrete mode and finally it has been

necessary to use the block that created Richard Gagnon from Hydro-Quebec. Despite this

fact, all the wind farm operated correctly and in the separated simulations it can be seen how

thanks to the rectifier the system is able to adapt to the changes on wind.

The solar plant has been easier to implement as there is a specific block that simulates a

photovoltaic plant with the desired dimensions. Different tests have been done to this part of

the system showing a great performance even with irradiances over and under the nominal

one. It is also remarkable in this part the maximum power point tracker system that controls

the DC-DC boost converter and makes possible obtaining always the maximum power from

the solar plant.Finally, the voltage source converter part was one of the most difficult parts to

model because of the complexity of all the operations and the desire of the author of not

using the Simscape blocks that exist for this part. In the simulation done to the voltage

source converter independently and together with the rest of the system it has been show

how this device works perfectly, having a very small time of response when finding any

problem in the system.

In order to follow the work done in this project, an energy storage management could be

implemented. It was intended to do with blocks that are present in Simulink as the other

types of devices but it was impossible in this case, not obtaining any correct value in the

simulations. Another way of continuing this project could be working on the islanded mode

from the grid of the medium voltage grid and the microgrid, where all the power should be

supplied by the microgrid. These two options were tried in this project with no success and

this is why they do not appear.


Acknowledgements

This project would not have been possible without the help of Oriol Gomis Bellmunt, who

gave me all the data referent to the CIGRE benchmark and the voltage source converter,

one of the main parts of the project. Apart from this he also helped me solving any doubt I

had.

Thanks also to my family and friends that have supported me since the first day I entered in

the UPC 6 years ago until this last project that marks the end of a beautiful stage of my life

and the beginning of a prosperous one.

Pàg. 72 Memòria

Bibliography

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[6] D. Fan, Y. Ren, Q. Feng, Y. Liu, Z. Wang, and J. Lin, “Restoration of smart grids: Current status, challenges, and opportunities,” Renew. Sustain. Energy Rev., vol. 143, no. March, p. 110909, 2021.

[7] S. H. Horowitz, A. G. Phadke, and J. S. Thorpe, “Adaptive transmission system relaying,” IEEE Trans. Power Deliv., vol. 3, no. 4, pp. 1436–1445, 1988.

[8] X. Zhou, T. Guo, and Y. Ma, “An overview on microgrid technology,” 2015 IEEE Int. Conf. Mechatronics Autom. ICMA 2015, pp. 76–81, 2015.

[9] K. Strunz, C. Abbey, C. Andrieu, R. C. Campbell, and R. Fletcher, Benchmark Systems for Network Integration of Renewable and Distributed Energy Resources, no. July. 2009.

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