Master of Science Thesis
KTH School of Industrial Engineering and Management Energy Technology EGI-2014-045MSC-EKV1019
Division of Heat & Power
Meeting the Challenges for Increasing the Share of Variable Renewable Energy in the Generation Mix of Mauritius
Rakesh Kumar DHUNUNJOY
EKV1019
Meeting the Challenges for Increasing the Share of Variable Renewable Energy
in the Generation Mix of Mauritius
Rakesh Kumar DHUNUNJOY
Approved
2014-08-19
Examiner
Miroslav Petrov - KTH/ITM/EGI
Supervisors at KTH
Miroslav Petrov
Commissioner or Partner
University of Mauritius
Local Supervisor
Dr. Dinesh Surroop
Abstract
As a Small Island Developing State (SIDS), Mauritius is exceptionally vulnerable. It faces similar threats to its survival as other SIDS, which include, inter alia, a strong reliance on a depleting natural resource base, loss of biodiversity and degradation of essential components of the ecosystem, and a heavy dependency on fossil fuels and other imported commodities that support society. Climate change, long distances that separating Mauritius from Africa and Asia, coupled with rising fuel costs exacerbates the situation considerably. Unless substantial and effective interventions are put in place soonest, the current and future generations may not be able to meet their needs.
Being aware of the susceptibility of the island towards energy security, the Government of Mauritius is focused on diversifying the country’s energy supply, improving energy efficiency, addressing environmental and climate changes and modernizing our energy infrastructure in order to meet the challenges ahead. Besides security of supply and affordability the Government is attempting a rapid shift to a low carbon, efficient and environmentally benign energy system. This policy is integrated in a Long- Term Energy Strategy (LTES) that aims at reducing the dependency on fossil fuels and promoting energy generation from local renewable sources. However, increasing the current share of renewable energy from 20% to 35% by 2025 as provided in the LTES, implies major investment in both RE technologies and at the same time in research studies in view to mitigate the upcoming challenges with increasing renewable generations in particular caused by VRE sources such as wind and solar.
The aim of this thesis is therefore to identify the major problems and complexities arising with increasing share of VRE more specifically related to grid stability, security operation and power quality. The various problems related to unconscious continuous addition of VRE were identified and solutions were proposed on how to mitigate them in order to be able to reach the RE targets set out in the LTES.
ACKNOWLEDGMENTS
I wish to express my warmest gratitude to my local project supervising, Dr. Dinesh Surroop (Lecturer in the Faculty of Engineering at University of Mauritius) and Mr.
Miroslav Petrov (KTH University) for their keen guidance, fruitful discussions and valuable suggestions that have been an important ingredient for the successful completion of this thesis.
I am also greatly indebted to my parents, wife and friends who have constantly provided their support during the preparation of this thesis.
Last, but not least, I would like to convey my sincere thanks to all those people, including Mrs. Chamindie Senaratne, who have helped me in achieving this goal.
Chapter 1 Introduction
1.0 Introduction and Background 1
2.0 The Electricity Sector in Mauritius 2
2.1 Institutional Structure 2
2.2 Electricity Generation Mix 2
2.3 Long Term Energy Strategy 2009‐2025 3
2.3.1 Renewable Energy (RE) Targets 3
3.0 Potential Barriers to Achieve the RE Targets 4
4.0 Objectives of the Thesis 5
5.0 Outline of the Subsequent Chapters 6
Chapter 2 Negative Impact of Variable RE on Isolated Grid Systems
1.0 Rationale 72.0 Comparison between Steady and Variable Power Generation Technologies 7 3.0 Variable Renewable Energy Technologies 8
3.1 Wind Energy Technology 8
3.1.1 Source of Wind 8
3.2 Wind Power Generation 9
3.2.1 Power Curve of Wind Turbine 10
3.2.2 Variable Nature of Wind Power Generation 11
3.3 Solar Energy Technology – Photovoltaic 12
3.3.1 Solar Irradiance & Insolation 13
3.3.2 Ideal Curve for PV Generation 13
3.3.3 Actual PV Output Profile 14
3.3.4 Daily Clearness and Variability Indices 14
3.4 CEB’s Power System 15
3.4.1 Generation Park 16
3.4.1.1 CEB Owned Plants 17
3.4.1.2 Independent Power Producers 18
3.4.2 Typical Daily Demand Profile 19
3.5 System Constraints with Variable Renewable Energy Integration 21
3.5.1 Frequency Aspects 21
3.5.1.1 Established Model for Frequency Control 22
3.5.1.2 Time Delays for Frequency Response 24
3.5.1.3 Grid Capacity Limitation for VRE Integration 25
3.5.2 Voltage Levels 27
3.5.3 Power Quality Issues 30
3.6 Actual Targets for VRE in 2025 32
3.6.1 Committed Addition for VRE on CEB’s Grid 33
3.6.2 Additional Requirement for VRE Installations 34
Chapter 3 Rodrigues Island Case Study –Analysis of Wind Farm Impact on System Frequency
1.0 Introduction 352.0 Electrical System Overview 36
2.1 Generation Park 37
2.2 System Frequency Regulation 38
2.3 Network Planning Criteria 38
3.0 System Modeling and Methodology 39
4.0 Impact of Wind Power Integration on System Frequency 41
4.1 Generation Dispatch 41
4.2 Maximum and Minimum Load Conditions 41
4.3 Wind Speed Variation and Frequency Disturbance 41
4.4 Study of Wind Farm Trip 42
4.5 Study of Wind Farm Output Power Variation 44
5.0 Recommendations 46
Chapter 4 Inexpensive Methods to Allow Larger VRE Integration
1.0 Introduction 482.0 Proposed Low Cost Solutions 48
Additional Base Generation
2.1.2 Curtailment of Wind Farms 52
2.1.3 Curtailment of Solar PV Output 53 2.2 Increasing Spinning Reserve on the Grid 53 2.2.1 Negative Impacts of Increasing Spinning Reserves 55 2.3 Keeping/Integrating High Inertia Generators on the Grid 56
2.3.1 H Constant 56
2.3.2 Recommendation 59
2.4 Decreasing Frequency Dead Band for Medium Speed Diesel Engines 59
2.4.1 System Frequency Response 60
2.4.2 Factors Affecting Steady‐State Frequency Error 61 2.4.3 Modes of Generation of Existing Generating Units 62 2.4.4 Recommendation for an Enhanced Sys Freq. Regulation 63 2.4.5 Simulation Results with Modified System 63
2.5 Geographical Dispersion of VREs 64
2.5.1 Aggregated Power Fluctuations 65 2.5.2 Analysis of Dispersed PV on Power Output Variability 66 2.5.3 Overview of Methodology to Det. Impact of Dispersed PV 67
2.5.4 Analysis Findings 67
2.5.5 Recommendation 69
Chapter 5 Energy Storage Systems for Mauritius
1.0 Introduction 70
1.1 Understanding Storage Performances 70
2.0 Proposal for Converting Champagne Hydro Plant into Pumped Storage Sys 71 2.1 Proposed Pumped Storage Solution at Champagne Power Station 72 2.2. Benefits with Proposed Pumped Storage System 73
2.3 Recommendation 73
3.0 Battery Technologies 74
3.1 Available Battery Technologies 74
3.2.2 Stabilizing Wind Power Generation 76
3.2.3 Stabilizing Solar PV Generation 78
3.2.4 Advantages of NAS Batteries 79
3.2.5 Sizing of NAS Batteries for Wind and Solar Energy Storage 80 3.2.6 Recommendation for Use of NAS Batteries 80
Chapter 6 Automatic Generation Control (AGC)
1.0 Introduction 822.0 AGC Tasks 83
3.0 AGC Strategies and Objectives 83
4.0 Area Control Error (ACE) 84
5.0 Philosophy of the AGC 85
6.0 AGC for CEB’s Grid 85
7.0 Findings from PB Power Consultant 87
8.0 Conceptual Framework for AGC System 88
Chapter 7 Conclusion & Recommendation
1.0 Introduction 912.0 Overall Assessment of Proposed Solutions 91
3.0 Financial Implications 92
4.0 Recommendations 96 5.0 Further Work
Figure 1.0 – Energy Mix of Mauritius (2010)
Figure 2.0 (a) ‐ Output profile from a Firm power plant Figure 2.0 (b) ‐ Output profile from a Non‐Firm power plant Figure 2.1 – Wind Turbine Operation
Figure 2.2 – Typical Wind Turbine Power Curve Figure 2.3 – Wind Turbine Output Profile
Figure 2.4 – Solar PV Electricity Generation Figure 2.5 – Ideal PV profile on a clear day
Figure 2.6 – Category of Daily Profile based Clearness and Variability Indices Figure 2.7 – Overview of CEB’s Power System
Figure 2.8 – Share of Electricity Generation
Figure 2.9 – Typical Summer and Winter Demand Profile Figure 2.10 – Dispatching Order of Power Plants
Figure 2.11 – System Frequency Balance Requirement with VRE Figure 2.12 – Model for frequency control loop
Figure 2.13 – Capacity Limit for VRE Integration
Figure 2.14 – Model for Distribution Feeder using Lumped Load Approach Figure 2.15 – Voltage Profile for Different Level of DG Integration
Figure 2.16 – VRE Interconnection Point Depending on Capacity Figure 2.17 – Brownout Condition
Figure 2.18 – Harmonic Distortion on Voltage Profile Figure 3.0 – Energy mix for Rodrigues Island (2011)
Figure 3.1 – Typical daily load profile for Rodrigues Island Figure 3.2 – Schematic diagram for the existing electrical system Figure 3.3 – Redundancy in Transmission Line
Figure 3.5 – Simulated response for a wind farm trip at 625 kW(max load condition) Figure 3.6 – Simulated response for a wind farm trip at 300 kW (min load condition) Figure 3.7 – Simulated response for a wind farm output power (1250kW) during the maximum load condition
Figure 3.8 – Simulated response for a wind farm output power (500kW) during the minimum load condition
Figure 3.9 – Wind power integration sustainable as a function of the system load demand
Figure 4.0 – Load Duration Curve 2012
Figure 4.1 – Load Curve with Spinning Reserves
Figure 4.2 – Specific Fuel Consumption and Engine Efficiency w.r.t. Engine Loading Figure 4.3 – Frequency Response with low and high System Inertia
Figure 4.4 – Governor Droop Characteristics of generating units
Figure 4.5 – System frequency responses following the loss of generation Figure 4.6 – Current Frequency Response for Medium Speed Diesel Engines Figure 4.7 – System Frequency Response
Figure 4.8 – SSDG Sites under Study
Figure 4.9 – Aggregated PV Power at six Dispersed Locations
Figure 4.10 – Aggregated PV Power Showing Max. Power Drop Rate Figure 5.0 – Proposed Pumped Storage at Champagne Power Station Figure 5.1 – Operating Principle of NAS batteries
Figure 5.2 – Wind Power Stabilization with NAS Batteries Figure 5.3 – NAS Battery Wind Power Stabilization
Figure 5.4 – Solar PV Stabilization with NAS Batteries Figure 6.0 – AGC System Overview
Figure 6.1 – Tripping of 25 MW wind Farm at Peak Load Conditions
Figure 6.3 – 50 MW wind Farm Trip with All Fort George Units on AGC (low load) Figure 6.4 – Conceptual Framework for AGC System
Table 1.0 – Targets for Renewable Energy Table 2.0 – CEB’s Owned Generation Park Table 2.1 – Capacity Info of IPPs
Table 2.2 – Inherent time delays for Response in Frequency Change Table 2.3 –Energy Consumption Forecast
Table 2.4 –Proposed Capacity VRE Installation Table 2.5 – Committed VRE Projects
Table 3.0 ‐ Installed Generation Capacity
Table 3.1 ‐ System frequency response for wind farm trip at maximum load demand Table 3.2 ‐ System frequency response for wind farm trip at minimum load demand Table 3.3‐ Frequency variation for wind farm output power at max load demand Table 3.4 ‐ Frequency variation for wind farm output power at min load demand Table 4.0 – Minimum load requirement from IPPs
Table 4.1 ‐ Analysis for the minimum load demand Table 4.2 – H constant values for Generating Units Table 4.3 – Current Mode of Operation of CEB Plants
Table 4.4: Illustration of the improvement of the system frequency response with additional generating units operating in droop‐control mode
Table 5.0 – NAS Battery Comparison
Table 7.0 – Proposed Solutions to Promote VRE Integration
Chapter 1
Introduction
1.0 Introduction and Background
Energy helps to drive the world economy and has a significant impact on the quality of life and health of the population. Reliable and affordable energy has in the wake of the recent surge in prices of petroleum products, never been as important as it is to‐day. It is now central to our economic development and will continue to be an essential vector on which the economic and environmental sustainability will depend [1].
As a Small Island Developing State (SIDS), Mauritius is exceptionally vulnerable. It faces similar threats to its survival as other SIDS, which include, inter alia, a strong reliance on a depleting natural resource base, loss of biodiversity and degradation of essential components of the ecosystem, and a heavy dependency on fossil fuels and other imported commodities that support society. Climate change, long distances that separating Mauritius from Africa and Asia, coupled with rising fuel costs exacerbates the situation considerably. Unless substantial and effective interventions are put in place soonest, the current and future generations may not be able to meet their needs.[1]
Being aware of the susceptibility of the island towards energy security, the Government of Mauritius is focused on diversifying the country’s energy supply, improving energy efficiency, addressing environmental and climate change and modernizing our energy infrastructure in order to meet the challenges ahead. Besides security of supply and affordability, the Government is further confronted with another challenge namely that of making a rapid shift to a low carbon, efficient and environmentally benign system of energy supply [1].
CEB Hydro 4%
CEB HFO 40%
CEB Kerosene
0.8%
IPP Coal 41%
IPP Bagasse 16%
2.0 The Electricity Sector in Mauritius
2.1 Institutional Structure
There are currently three main bodies related to energy sector in Mauritius namely:
1) The Ministry of Energy and Public Utilities (MEPU) – its main task is to prepare energy policies and its portfolio energy, water and wastewater; and
2) The Central Electricity Board (CEB) ‐ which was established in 1952, is empowered by the Central Electricity Board Act, 1964 to ʺprepare and carry out development schemes with the general object of promoting, coordinating and improving the generation, transmission, distribution and sale of electricityʺ in Mauritius. The Electricity Act of 1939 (amended 1991), Electricity Regulations of 1939 and Central Electricity Board Act provide the legislative framework for the electricity sector. The CEB produces around 45% of the countryʹs total power requirements from its 4 thermal power stations and 8 hydroelectric plants, the remaining 55% being purchased from Independent Power Producers (IPPs), mainly sugar industry owned, who produce electricity from bagasse or coal.
2.2 Electricity Generation Mix
The electricity generation mix in Mauritius is essentially based on fossil fuels (82%) such as coal, fuel oil and kerosene. The remaining share is met from renewable sources such as bagasse and hydro. The pie‐chart below illustrates the energy mix of Mauritius as of year 2010.
Figure 1.0 – Energy Mix of Mauritius (2010)
It can be observed from Figure 1.0 that bagasse and hydro (the data includes also landfill gas sources) are the three major renewable resources, cumulatively contributing around 18% fuel requirement for electricity generation in Mauritius. Other than bagasse and hydro, Mauritius has no known indigenous occurrence of natural resource of fuel such as oil, natural gas or coal reserves and therefore it is heavily dependent on imported energy sources. Fossil fuel accounts for approximately 82% of the total fuel consumed for electricity generation.
2.3 Long Term Energy Strategy 2009‐2025
In October 2009, the Government of Mauritius (Ministry of Energy and Public Utilities) issued a Long Term Energy Strategy (LTES) document which globally presents the vision of the energy sector on the island for the planning period until 2025. The LTES document lays particular stress on the development of renewable energy, reduction of dependence on imported fossil fuel and the promotion of energy efficiency together with the Government’s objective to promote sustainable development in line with the
“Maurice Ile Durable”1 vision [1].
2.3.1 Renewable Energy (RE) Targets
Among the critical recommendations of the LTES document are the milestone targets for renewable resources in the energy mix. The current share of RE for the base year (2010) was 20% (comprising 16% bagasse and 4% hydro generation) and the goal is to increase this share to 35% in 2025. The transition strategy for shifting towards this target is shown in Table 1.0 below.
1 It is the vision of the Government to make Mauritius a sustainable island. Energy is one of the five elements which are covered under it.
Table 1.0 – Targets for Renewable Energy in Mauritius (Source: Long Term Energy Strategy 2009‐2025)
3.0 Potential Barriers to Achieve the RE Targets
The energy policy of Mauritius has set targets on RE generation and at the same time curbing the dependency on fossil fuels. However, there are some major hurdles that lie ahead in order to meet those targets. These hurdles are identified below:
High Investment Cost
The costs for RE technologies are very high as compared to other conventional sources of power generation, and therefore act as major obstacle in moving towards these sources. Moreover, since Mauritius is prone to cyclones, the renewable sources of generation should be constructed more robustly in order to be able to withstand gusts of the order of 350 km/hr. The cyclonic resistant technologies further increase the initial investment cost.
Fuel Source
Percentage of Total Electricity Generation
2010 2015 2020 2025
Renewable
Bagasse 16% 13% 14% 17%
Hydro 4% 3% 3% 2%
Waste to energy 0 5% 4% 4%
Wind 0 2% 6% 8%
Solar PV 0 1% 1% 2%
Geothermal 0 0 0 2%
Sub‐total 20% 24% 28% 35%
Non‐
Renewable
Fuel Oil 37% 31% 28% 25%
Coal 43% 45% 44% 40%
Sub‐total 80% 76% 72% 65%
Total 100% 100% 100% 100%
Variable in Nature
Most renewable sources of power generation, such wind and solar are intermittent in nature, that is, they do not give a constant power output all the time. In this case, other power sources are needed as back‐up to compensate for the dips in output. Such problem is not encountered with conventional sources such as coal and diesel engines.
Site Specific
RE technologies are very site specific implying that they can only be optimized if they are installed at the appropriate sites. Otherwise, their energy output would be so low that the project would no longer be bankable – Financing bodies would be reluctant to provide loans for such projects.
Low Efficiencies
Renewable technologies have comparatively low efficiencies of power conversion and are often deemed not so economical for promoters to venture in these types of projects.
An example is the conversion of solar power by a polycrystalline PV panel, having typically an efficiency of only about 15 % as compared to a coal plant which is of the order of above 30% while that of a diesel engine plant is around 45%.
Technologies Still in Experimental Stage
Some RE technologies are still at experimental stage and there is long time for them to reach full commercial operation. For instance Mauritius is surrounded by sea but harnessing marine energy is still a far‐fetched concept. One example is the “Pelamis”2 which uses wave motion to generate electricity. However, same is still under trial stage.
4.0 Objectives of the Thesis
The Government policy aims at reducing the dependency on fossil fuels and promoting energy generation from local renewable sources on the island of Mauritius. However, increasing the current share of renewable energy from 20% to 35% by 2025 as stated in the LTES, implies major investments in RE development and at the same time in research studies in view to mitigate the upcoming challenges related to the increased Variable Renewable Energy (VRE) share in the island energy system.
2The Pelamis is an offshore wave energy converter that uses the motion of waves to generate electricity
The primary aim of this thesis work is therefore to identify the major problems and complexities arising from the increasing share of VRE, more specifically related to grid stability, security operation and power quality. If these problems are not resolved at the very beginning, unconscious continuous addition of VRE may result in frequent power outages, abnormal voltage levels and poor power quality to electricity consumers.
It is therefore imperative that a complete study be carried out identifying all hurdles with increasing VRE and providing the necessary solutions for each of them.
In light of the above, this thesis has been entitled as:
” Meeting the Challenges for Increasing the Share of Variable Renewable Energy in the Generation Mix in Mauritius”
5.0 Outline of the Subsequent Chapters
Chapter 2 ‐ Analysis of the complexities associated with increased penetration of variable renewable energy sources in an isolated grid, in particular wind and solar;
Chapter 3 – Description of a case study in Rodrigues Island on how fluctuations in wind power generation affect grid stability and security;
Chapter 4 – Details some of the inexpensive solutions available that can improve grid stability while at the same time increasing the share of variable renewable energy in the generation mix.
Chapter 5 – Discusses about the use of storage systems in particular pumped storage and battery systems such as Sodium Sulphide (NAS) batteries as ways to mitigate fluctuations in output power from wind/solar sources;
Chapter 6 – Considers the implementation of Automatic Governing Control (AGC) on the high response generators on the grid.
Chapter 7 – Assesses and summarizes the different options available, provides conclusions and recommendations.
Chapter 2
Negative Impact of Variable Renewable Energy on Isolated Grid Systems
1.0 Rationale
One of the ways to classify power generation technologies nowadays is whether the power output from the technology is steady or unsteady (time varying). Formerly, all conventional power generation technologies such as diesel engines, coal plants, nuclear, hydro and biomass provide constant power outputs, which can be varied by the grid operator depending on the electricity demand. However, after most industrial and developing countries have signed the Kyoto Protocol, there has been a paradigm shift towards decreasing usage of fossil fuels and harnessing more energy from renewables, whereas wind and solar technologies have quickly developed to widespread commercial applications. The advantages of renewable electricity are many, including reduced environmental impact, potential for lower costs and reduced dependence on imported fuels. However, some forms of renewable electricity — notably wind and solar — can aggravate the operational challenge of meeting electricity demand while maintaining the power quality. The output of wind and solar plants varies with the resource (the wind and the sun, respectively), and it is not possible to ramp these plants according to the actual demand. Instead, electricity system operators must simply take what they can get from these plants, and use “dispatchable” fossil‐fired power plants to fill in any gaps.
2.0 Comparison between Steady and Variable Renewable Power Generation Technologies
By definition, a firm power plant is one whose power is available at scheduled times and at controllable levels. In contrast, a non‐firm (or varying) power plant is defined as one whose capacity cannot be scheduled with certainty. The power supplied is very much dependent on the availability of the renewable energy resource [2].
Typical power output profiles for a firm (dispatchable) and a non‐firm (stochastically variable) power plants are illustrated in figures 2.0 (a) and 2.0 (b) respectively.
Figure 2.0 (a) Firm power plant Figure 2.0 (b) Non‐Firm power plant (Source: Integrated Electricity Plan 2013‐2022)
3.0 Variable Renewable Energy Technologies
Currently, among mature renewable energy technologies, wind and solar (photovoltaic) generations provide variable outputs as they depend on the natural availability of the resource to generate power. For the purpose of this thesis, the negative impacts of these two specific technologies will be considered and covered in the sections which follow.
3.1 Wind Energy Technology
3.1.1 Source of Wind
The true source of the energy found in the wind resource is the sun. Global winds are caused by pressure differences across the earth’s surface due to the uneven heating of the earth by solar radiation. For example, the amount of solar radiation absorbed at the earth’s surface is greater at the equator than at the poles. The variation in incoming energy sets up convective cells in the lower layers of the atmosphere, which are known as the troposphere [3].
In a simple flow model, air rises at the equator and sinks at the poles. The circulation of the atmosphere that results from uneven heating is greatly influenced by the effects of the rotation of the earth. In addition, seasonal variations in the distribution of solar
energy give rise to variations in the circulation. The spatial variations in heat transfer to the earth’s atmosphere create variations in the atmospheric pressure field that cause air to move from high to low pressure. There is a pressure gradient force in the vertical direction, but this is usually cancelled by the downward gravitational force. Thus, the winds blow predominately in the horizontal plane, responding to horizontal pressure gradients. [3]
3.2 Wind Power Generation
Energy can be harnessed from the wind through wind turbines. They convert the kinetic energy in wind into electricity. The figure illustrates a wind turbine extracting the energy from wind and converting it into electricity.
Figure 2.1 – Wind Turbine Operation (Source: [4])
The power from the wind that can be converted is given by the following formula:
P = ½ C
pρAV
3Where:
P – Power extracted from wind (W)
Cp – Power Coefficient of the energy conversion device (wind turbine rotor)
ρ
– Density of air (assumed to be 1.225 kg/m3 in standard conditions)A – Swept area of the rotor (m2)
V – Velocity of the undisturbed wind (m/s)
As it can be observed from the formula, the power is proportional to the cube of wind velocity. This implies that if wind speed is doubled, the extracted power from the wind turbine would increase eight times.
However, not all of the available wind power can be extracted by the turbine. The power coefficient gives therefore the ratio of the power extracted by the wind turbine to the power available in the undisturbed wind:
C
p= P
WT/ P
airIt can be shown that for any turbine device in a free‐flowing fluid stream, the theoretical maximum power that can be extracted is 59.3%. This is referred to as the Betz limit.
Modern wind turbines have power coefficients of the order of 35% to 45%.
3.2.1 Power Curve of Wind Turbine
The power output of a wind turbine varies with wind speed and every wind turbine has a characteristic power performance curve. The figure below presents an example of a power curve for a hypothetical wind turbine.
Figure 2.2 – Typical Wind Turbine Power Curve (Source: [4])
0 0.1 0.2 0.3 0.4 0.5 0.6
0 5 10 15 20
Active power output of a 1MW Wind Turbine Generator (MW)
Time of the day (Hours)
With such a curve it is possible to predict the energy production of a wind turbine without considering the technical details of its various components. It should be noted that the performance of a particular wind turbine generator can be associated to three fundamental points on the velocity scale and these are:
Cut‐in speed: the minimum wind speed that is needed for the machine to deliver useful power.
Rated wind speed: the wind speed required for the rated power to be reached.
Cut‐out speed: the maximum wind speed that is allowed for the turbine to deliver power without endangering its integrity.
3.2.2 Variable Nature of Wind Power Generation
As explained in the above section, the power output from a wind turbine is dependent on the characteristic of its power curve. Since the wind speed is always varying with time, the power output from a wind turbine is also fluctuating depending on the wind speed. Wind speeds vary with time of day, time of year, height above ground and location on earth surface. This makes wind generators in what might be called energy producers rather than power producers.
A wind turbine produces only when wind is available. At a good site, the power output would be zero (or very small) for around 10% of the time, rated for about another 10%
of the time and at some intermediate value for the remaining 80% of the time.
Figure 2.3 below shows the five minutes interval wind production from a typical 1 MW wind turbine over a 24 hour period.
Figure 2.3 – Wind Turbine Output Profile
3.3 Solar Energy Technology ‐ Photovoltaic
Among the different solar technologies available for generating electricity, we shall consider solar photovoltaics (PV) for the analysis in this thesis. Solar PV is a method of generating electrical power by converting solar radiation into direct current electricity using semiconductors that exhibit the photovoltaic effect. Photovoltaic power generation employs solar panels composed of a number of solar cells containing a photovoltaic material, based on different production technologies. Materials presently used for commercial PV include monocrystalline silicon, polycrystalline silicon, amorphous silicon, cadmium telluride, and copper indium gallium selenide/sulfide. [5]
Photovoltaics are best known as a method for generating electric power by using solar cells to convert energy from the sun directly into a flow of electrons. The photovoltaic effect refers to photons of light exciting electrons into a higher state of energy, allowing them to act as charge carriers for an electric current. Figure 2.4 below depicts the basic principle of PV electricity generation.
Figure 2.4 – Solar PV Electricity Generation (Source: [5])
3.3.1 Solar Irradiance & Insolation
The solar resource at a given time is dependent on the weather conditions and on the time period examined. Irradiance and insolation are the two common and well defined measures of solar resource.
Irradiance is a measure of solar power on a given plane (e.g. on a horizontal plane) and is usually expressed in W/m2. The power output from a PV plant is generally proportional to the irradiance across the PV plant’s footprint. Since plant output is proportional to irradiance, variability in irradiance is informative about the variability in plant power output. Irradiance can be measured by using pyranometers.
Insolation, on the other hand, is defined as the energy received over time i.e. the integration of irradiance. Typical daily values range from 2 to 7 kWh/m2 depending on location, array tilt, time of year and weather. In Mauritius, insolation level is higher in summer months than winter months.
3.3.2 Ideal Curve for PV Generation
An idealized PV output profile on a clear day is shown in Error! Reference source not found.2.5 below. Usually, the angle of the sun to the solar modules is very low in the morning, though the day is ‘bright’ to the eye, resulting in a low power output. As the sun moves more directly in front of the modules, the output rises to a peak value which occurs at noon when the sun is almost perpendicular to the PV modules. Then, as the sun begins to decline, the angle gets lower and a decrease in power output is noticed.
Figure 2.5 – Ideal PV profile on a clear day (Source: [6])
3.3.3 Actual PV Output Profile
Solar photovoltaic technology is an intermittent source of power generation as it depends on the amount of light energy in a given location. As expected, the resource generally rises as the sun rises and falls as it sets. Perhaps, not as expected, the resource can be highly variable within time frames of seconds to minutes, changing quickly with passing clouds. No two days are similar. Some days may be clear, others are partly cloudy while others are overcast.
3.3.4 Daily Clearness and Variability Indices
Looking day to day gives a perspective on the variation for a particular location and the time period. A method for classifying days as more or less variable is proposed. This method uses a combination of the classical daily clearness index and a new daily variability index defined by Sandia National Laboratories. Research is being conducted to determine if distinguishing variability in this manner can be used by utility generation planners and grid operators in making decisions. [7]
The daily clearness index (CI) is defined as the ratio of solar energy measured on a given surface to the theoretical maximum energy on the same surface during a day with clear skies:
Daily Clearness Index =
The calculated clear sky solar insolation can be calculated from a number of clear sky models. Typical values for the daily clearness index range from 0.0 to 1.1. Values greater than 1.0 can be obtained in practice because clear sky models may not be exact for every hour at any given location. [7]
The daily variability index is the variability in the measured irradiance, relative to the variability of the calculated clear sky irradiance, with each quantified by length of irradiance versus time plot of the day. Typical values for daily variability index range from 1 to 30 and are determined using the following equation:
Daily Variability Index =
Using combinations of the daily clearness index and the variability index, variability in irradiance can be qualitatively categorized as shown in Figure 2.6 below, using five categories of variability conditions; high variability, moderate variability, mild variability, clear and overcast days. Example of each type of day is shown with a corresponding value for variability index and clearness index [7].
Figure 2.6 – Category of Daily Profile Based Clearness and Variability Indices (Source: [7])
3.4 CEB’s Power System
The figure below gives a broad overview of the CEB’s generation, transmission and distribution systems on the island of Mauritius.
Figure 2.7 – Overview of CEB’s Power System (Source: [2])
In general, power is generated at 11 kV (in some cases at 6.6 kV) and is stepped up to high voltage (HV) at 66 kV via power transformers. It is then transmitted to different substations where the 66 kV is stepped down to 22 kV medium voltage (MV). The main reason for high voltage transmission is to minimize the effect of network losses. A distribution network at 22 kV covers the island through different feeders. At consumer end, the medium voltage is further stepped down to 415 V via distribution transformers and then supplied to consumers. In the urban areas, the 22 kV is first stepped down to 6.6 kV at substations and then transmitted to distribution transformers.
3.4.1 Generation Park
The total electricity generation of the country is met by both CEB’s owned power plants (mainly based on fuel oil and hydropower) and independent power producers IPPs which are mostly coal/bagasse fired power plant. The share of CEB to IPP generation for year 2012 is depicted in Fig. 2.8 below.
Figure 2.8 – Share of Electricity Generation 3.4.1.1 CEB Owned Plants
The CEB owns four thermal power plants, out of which three operate on heavy fuel oil while the last one operates on kerosene (Jet A1). The total effective capacity for the thermal units is approximately 386 MW. The CEB also has nine hydro generating units, making a total effective capacity of 55 MW, scattered over the island. The biggest hydro plant (2 x 14 MW) is generally dispatched as a peaking unit while the remaining ones are utilized as and when there is availability of water. The table below gives a more elaborated understanding of the CEB’s owned power plants.
Power Plants No. of Units Eff. Capacity (MW)
Technology Dispatching
Fort George 5 134 Slow Speed Diesel Base Load
Saint Louis 9 71 Medium Speed
Diesel
Semi Base Load
Fort Victoria 8 107 Medium Speed
Diesel
Semi Base Load
Nicolay 3 74 Open Cycle gas
Turbine
Peaking
Hydro Units 9 55 Hydro Turbines Base / Peaking
Table 2.0 – CEB’s Owned Generation Park
3.4.1.2 Independent Power Producers
CEB is presently managing Power Purchase Agreements (PPAs) with five IPPs, which operate on a steady output basis. The largest of the IPPs is the ‘Compagnie Thermique de Savannah’ (CTSav), which was commissioned in 2007. Its net total export capacity is 74 MW. All the IPPs, with the exception of ‘Compagnie Thermique Du Sud’ (CTDS), operate on bagasse in the crop season and on coal during inter‐crop season. In the
‘bagasse’ mode of operation, the IPPs export less power to the CEB’s grid, as some of the produced steam is sent to the nearby sugar factories for sugar‐cane production processes [2].
Among the IPPs, three, namely CTBV, FSPG and CEL, have ‘take‐or‐pay’ contracts with CEB. The ‘take‐or‐pay’ principle means that the CEB shall pay for the contractual energy amount even if the energy is not dispatched, while the power plant is available.
The PPAs of these IPPs include the purchase of energy on the single‐part tariff model.
For the other two IPPs (CTDS and CTSav), CEB negotiated the two‐part tariff model, which treats Capacity and Energy Charges as two different cost elements [2].
The table below provides the names of the IPPs and their corresponding power output in both coal and bagasse modes of operation.
IPPs Eff. Capacity (MW) ‐ Coal Eff. Capacity (MW) ‐ Bagasse
CTSav 74 65.5
CTBV 62 46
CTDS 30 N/A
FUEL 27 20
CEL 22 11
Total 215 172.5
Table 2.1 – Capacity Information of IPPs
3.4.2 Typical Daily Demand Profile
An examination of the day‐to‐day demand curves discloses that electricity demand is not same over time. It varies constantly irrespective of the day. In Mauritius, based on seasonality, two typical demand curves are found, as shown in Figure 2.9 below. The hourly values along the curves are expressed in per unit (as ratios of the highest peak).
Figure 2.9 ‐ Typical Summer and Winter Demand Profile (Source: [2]) It is projected that the system load factor is typically 83% in summer and 68% in winter months. This higher demand in summer is caused primarily by air conditioning loads and same accounts for 20‐30% increase on the winter demand profile.
3.4.3 Dispatching Order of Generating Units
The CEB generally adopts an economic approach in dispatching the available generating units. Usually, IPPs coal/bagasse plants and Fort George power station are operated as base load generators. The medium speed diesel units are dispatched as semi base load generators i.e. they are started early in the morning and cease operation after meeting the evening peak demand. Lastly, the hydro unit and Nicolay are dispatched as peak load generators as they can ramp up and synchronize very rapidly to the grid to meet the peak demand. Figure 2.10 below illustrates how generators are dispatched in order to meet a particular day demand.
Figure 2.10 – Dispatching Order of Power Plants
3.4.4 System Frequency
For the security and stability of the CEB’s power system, it is required to systematically match the total power generated with the prevailing load demand. The system frequency for CEB power system is 50 Hertz (Hz). When both are balanced, the system frequency is 50 Hz. However, if demand is higher than the generation, then the frequency goes lower than 50 Hz and vice versa. The following 3 scenarios are possible:
o Power generation = Load demand, Frequency held constant at 50 Hz o Power generation > Load demand, Frequency > 50 Hz
Base Load Generators F. George
& IPPs
Semi Base Load Generators St Louis &
F. Victoria Peaking Units Hydro and Nicolay
o Power generation < Load demand, Frequency < 50 Hz
Generally, a spinning reserve equivalent to 10% of the prevailing peak demand is kept synchronized to the grid. In the event a generator trips from the grid, the hot spinning reserve shall provide the necessary quick response to restore the system frequency to nominal 50 Hz.
3.5 System Constraints with Variable Renewable Energy Integration
While the integration of firm renewable energy sources, such as coal, hydro and biomass, does not pose technical challenges or constraints, the time‐varying nature of wind and solar power presents challenges with respect to system stability, security, operation and power quality. These challenges are of particular concern for a small‐
sized and insular power system, such as for the CEB, which is characterized by a small number of generating units, low spinning reserve and low system inertia3. [2]
There are three principal aspects that need to be considered prior to integrating variable renewable energy into the grid system in order not to jeopardize grid stability and security. These are:
1) Frequency Aspects 2) Voltage Levels 3) Power quality issues
3.5.1 Frequency Aspects
As per regulatory requirements, CEB has to maintain the supply frequency within ±0.75 Hz of the nominal value 50 Hz so as to ensure the safe and reliable operation of electrical equipment and appliances on the consumer end.
For planning purposes, CEB uses the limit of ±0.5 Hz for system frequency deviation to ensure system stability, security and the reliability of supply. The limit of ±0.5 Hz caters for the condition, whereby a generator trip coincides with the minimum system frequency, caused by a sudden drop in time‐varying renewable energy generation, to help in minimizing the extent of load shedding and the risk of total system breakdown.
3 System inertia is a measure of the total rotating mass in the power system
Under normal operating condition, by ensuring system frequency within the stated limits, power generation safely matches system demand. The frequency band of ±0.5 Hz around the nominal value of 50 Hz enables safe system control during any mismatch between instantaneous demand and supply. The mismatch is due to the inherent delays of the generating units to follow the varying load demand [2].
However, as a larger integration of variable renewable energy systems is contemplated, imbalances are caused between power generation and load demand thereby increasing the frequency deviation from the nominal value. Figure 2.11 below illustrates the balance that needs to be kept in terms of spinning reserve when variable RE is connected to the grid.
Figure 2.11 – System Frequency Balance Requirement with VRE (Source: [8])
3.5.1.1 Established Model for Frequency Control
In order to assess the stability of a network, dynamic models of the frequency and voltage control systems of generation units are required. CEB’s models have been developed in the DigSILENT Power factory Software4, using the IEEE standard models
4 DigSilent Power Factory is the software tool used for system planning studies
Non-firm RE generation
Spinning reserve Firm
generation
Rise in power output from non-Firm RE farms 50 Hz
> 50 Hz
< 50 Hz Drop in power output from non-firm RE farms
Load demand Power generation
Load demand
and have been validated through field tests and measurements. Figure 2.12 below depicts a block diagram in the S‐domain for the active power frequency control.
Figure 2.12 – Model for frequency control loop (Source: [2]) Where:
The governor continuously senses the grid frequency and compares it with the nominal frequency of 50 Hz (reference frequency). In the event there is a change in the grid
frequency, the deviation between the system frequency and the reference frequency causes an error in the governor. The latter then sends a signal to the fuel valve system and adjusts the fuel admission to the prime mover thereby regulating the power output to the grid. In so doing, the grid frequency is readjusted to 50 Hz.
The frequency response of the power system is different for the low‐demand conditions and high‐demand conditions, due to different amount of spinning reserve and system inertia. Higher load demand is associated with higher level of spinning reserve and higher system inertia, therefore, the impact of variable renewable energy on the system frequency is less.
For each of the low‐demand and the high‐demand conditions, the maximum level of variable renewable energy that can be integrated has been determined by increasing the level in step and determining the corresponding maximum system frequency deviation, which is caused by the variable power output from the renewable energy farms.
The maximum renewable energy integration is taken as that value which brings a maximum operational system frequency deviation of ±0.5 Hz.
3.5.1.2 Time Delays for Frequency Response
The above simplistic frequency loop model applies only in ideal cases. In reality, there are time delays between sensing the deviation in frequency and responding to corrective actions (i.e. adjusting the output power). Even firm generating units cannot instantly increase their power output to compensate for the change in power output from the variable renewable energy sources due to the inherent delay of governor, prime‐mover and generator to operate and change the unit active power output.
Time delays are very dependent on the available technology. Hydro turbines and diesel generators can be inherently fast in ramping up and down, while e.g. the response from a coal‐fired unit is comparatively slow as it is limited by the steam valve opening and closing rates together with the thermal inertia and the inherently slow ramping rate of the steam boiler.
Table 2.2 below gives an idea of the time delays on the different available technologies.
It is to be noted that the total delay of the generating system is the sum of the governor,
actuator and prime‐mover time delays. The steam valve opening and closing rates for coal‐fired generating units also determine the generating system response.
Generating unit Governor and actuator time delay (sec)
Prime‐mover time delay (sec)
Medium‐speed diesel (St Louis and Fort Victoria)
0.5601 sec 0.045 sec
Slow‐speed diesel (Fort George 1‐2)
0.5601 sec 0.217 sec
Slow‐speed diesel (Fort
George 3‐5)
0.5601 sec 0.210 sec
Coal‐bagasse (Spreader‐
stoker technology)
Actuator and servo delay =0.2 sec
Valve opening time, Uo=0.002 pu/sec
Valve opening time, Uc=‐0.008 pu/sec
0.500 sec
Pulverized coal technology
Governor servomotor delay=0.2 sec
Servomotor rate limit (closing)=0.3MW/sec
Servomotor rate limit (opening)=0.4MW/sec
Steam header and inlet piping time constant=0.1 sec
Table 2.2 – Inherent time delays for Response in Frequency Change (Source [9])
3.5.1.3 Grid Capacity Limitation for VRE Integration
With the current statutory limits for frequency, simulation studies have shown that there is a limit of integrating VRE in the actual grid system. The limit shall of course depend on the prevailing load demand. The diagram on figure 2.13 illustrates the capacity limits for accommodating VRE with respect to load demand while at the same time remaining within the allowable frequency tolerances.
Figure 2.13 – Capacity Limit for VRE Integration (Source: [2])
As can be observed in the figure above, X1 and X2 represent the maximum level of variable renewable energy (MW) that can be safely integrated in the Mauritius Power System during minimum and maximum load (demand) conditions respectively, while maintaining the system frequency within ±0.5 Hz of the nominal value of 50 Hz. X1 and X2 are determined by the level of demand and the amount and quality (response time of the generation system) of spinning reserve.
Generally, in our context, the minimum demand conditions occur between midnight and six o’clock in the morning, when solar energy source is not available. On the other hand, the maximum demand conditions occur during the daytime. Usually, during the daytime period both solar and wind power can be tapped off. Given these specific conditions, it is therefore possible to optimize the integration of time‐varying renewable energy through a mix of wind and solar power technologies.
3.5.2 Voltage Levels
As per regulatory requirements, CEB needs to maintain a single‐phase voltage of 230 V
± 6% at customers’ terminals. Renewable energy generators are operated in the power factor control mode (nearly unity power factor) and their interconnections to the low‐
voltage network or medium‐voltage network inevitably lead to rise in voltage.
A similar approach to that of frequency model has been adopted for voltage analysis in the DigSilent Software. In fact, steady‐state models of typical medium‐voltage distribution feeders and low‐voltage distributed feeders have been developed; where the electrical lines, transformers, loads and equivalent grid system have been accurately modeled. Figure 2.14 below illustrates the model of distribution feeder using a lumped load approach.
Figure 2.14 – Model for Distribution Feeder using Lumped Load Approach (Source: [2]) The maximum level of renewable energy that can be integrated on a low‐voltage feeder and a medium‐voltage feeder has been determined by increasing the level of renewable energy in step until the voltage reaches the upper limit of ±6% of the nominal value. The diagram below in Figure 2.15 shows that if high level of integration of distributed generation (DG), which can be either wind or solar, gets connected across one of the nodes, the voltage levels may rise outside permissible limits in the event demand is low and DG is at full capacity.
Figure 2.15 – Voltage Profile for Different Level of DG Integration (Source: [2])
In order to avoid situations as shown above, the following principle has been adopted at CEB:
1. Maximum RE farm capacity that can be interconnected to a low‐voltage feeder is 50 kW. This type of RE installation falls under the existing Small‐Scale Distributed Generation (SSDG) Scheme5.
2. Depending on the location and specific feeder’s absorption capacity, maximum RE farm capacity that can be interconnected to existing medium‐voltage (22 kV) feeders is 2 to 4 MW. Connection of such RE installation requires a prior detailed system study under the Medium‐Scale Distributed Generation (MSDG) Scheme.
3. Depending on the technology and the substation’s absorption capacity, RE farms of capacity above 4 MW up to 10 MW can be connected through dedicated 22 kV line to the CEB’s 22 kV busbar.
5 The SSDG scheme allows residential consumers to produce their own electricity (through either wind, solar PV or hydro) for their own consumption and sell the excess to the grid at a pre‐determined feed‐in tariff.
4. RE farms of capacity more than 10 MW have to be connected to the CEB’s 66 kV substation busbar system.
The diagram in Figure 2.16 below illustrates the point of interconnection for VRE of different capacities:
Figure 2.16 – VRE Interconnection Point Depending on Capacity (Source: [2]) In addition to the voltage rise, the variable power output from the RE farms leads to fluctuation in voltage along the low‐voltage and medium‐voltage feeders. As a mitigation measure, advanced automatic voltage control will be required for power transformers and capacitor banks in substations.
