i
Faculdade de Engenharia da Universidade do Porto
Multi-temporal Optimal Power Flow Including
Storage
Diogo Domingos Lopes de Freitas
Mestrado Integrado em Engenharia Eletrotécnica e de Computadores
Supervisor: Prof. Dr. José Nuno Moura Marques Fidalgo Co-Supervisor: Dr. Leonel de Magalhães Carvalho
ii
iii
A otimização da exploração dos Sistemas Elétricos de Energia exige o recurso a técnicas avançadas, capazes de lidar com problemas complexos, de natureza multi-temporal, não-linear e combinatória. O OPF (Optimal Power Flow) constitui um problema de otimização, que é resolvido para ajudar a encontrar uma solução ótima para os trânsitos de potência da rede
Neste trabalho, pretende-se desenvolver uma ferramenta para resolver o problema de OPF incluindo a otimização dos recursos de armazenamento de energia. Esta ferramenta foi implementada em MATLAB, aproveitando as funções disponíveis na biblioteca MATPOWER.
v
With the growth of renewable energy sources and other distributed generation sources, electricity grids are becoming more complex. Renewable production has many advantages but has the disadvantage of the inherent variability, which requires conventional production to back it up when the weather does not allow for renewable production.
One of the most promising technologies for electricity grids are energy storage systems. Storage systems are gaining more importance as renewable generation increases in the electric system, and it is seen as one of the tools to help smooth the variability of renewable energy sources, among other advantages.
In this study, the main objective was to develop a Multi-temporal Optimal Power Flow methodology, able to integrate storage and to deal with AC constraints. The multi-temporal problem formulation allows the optimization of the charging and discharging schedule, in order to evaluate the benefits of storage integration.
The proposed approach is based on a two-blocks system. The first block uses the MATPOWER Optimal Scheduling Tool (MOST), responsible for the initial DC OPF and optimization of the global dispatch for the time interval considered, while defining the storage unit charge and discharge periods that would minimize the overall production cost. The second block is an AC OPF, applied for each hour individually, that aims at computing losses and checking all system constraints, namely reactive power flows and limits. In the last step, the AC information (losses, constraint violation) are re-integrated in the MOST tool to produce the final production schedule.
The proposed methodology was validated through simulations studies on the IEEE 30 bus system
During this study, several case studies are put into test to analyse the influence of the storage unit on various aspects of the system, with the main objective being always to diminish the system’s production cost.
vii
MATPOWER, MOST, Otimização, Sistemas de Armazenamento de Energia, Transito de
Potências Ótimo, Unit Commitment
Keywords
Energy Storage System, MATPOWER, MOST, Optimal Power Flow, Optimization, Unit Commitment
ix
Firstly, I would like to deeply thank the supervisor of this dissertation, Professor Doctor José Nuno Moura Fidalgo for letting me develop this study with him, for all the support and attention he gave to me during the semester, and for the continuous help during the best and the worst moments of this study.
I would also like to thank the Co-Supervisor of this dissertation, Doctor Leonel de Magalhães Carvalho, for providing an incredible insight to the subject, and helping with the elaboration of the work itself. Without his knowledge, this work would not be so complete.
Special thanks to Doctor Carlos Murillo-Sánchez, one of the developers of MATPOWER and
MOST, for being able to debate ideas and help me implement the code to have the simulation
program up and running. He was a great help to this work and I am deeply thankful of all the support he and Doctor Ray Zimmerman provided me.
I also thank the institution that is the Faculdade de Engenharia da Universidade do Porto, for being the house that took me since 2011 and that helped making me what I am today.
Special thanks must be given to my family, my girlfriend, and my friends. To my family, especially my parents, that supported me through all my education, that were always there to motivate me even when they knew they could not help. And to my brother, that always tried to cheer me on, especially during the course of this study.
I also need to thank my girlfriend Sara, for helping me have the strength to face all adversity. She has put up with me through all the panic moments, all the scares, all the rough days, but as also been there for me for every victory, every smile, every moment of joy. Although she denies it, she is a major part of this work and a major part of what I achieved. Without her, I would probably not be writing these words. And for that I will be eternally grateful. She is the woman of my dreams and I hope I can make her proud with my doings.
Finally, I would like to thank my friends. That throughout the entire adventure that was university, were there to support me, to hear me complain, to see me cry in despair. I thank all of my friends for everything and for being always there for me, especially Filipe, that was the one who followed closer all the work of this Dissertation; Rodrigues, for always being there to help me with IT and programming, and Pedro, for being a partner in the tough years that were the early years of university.
xi
... 1
Introduction ... 1 1.1 - Context ... 1 1.2 - Objectives ... 2 1.3 - Dissertation Structure ... 2... 5
Energy Storage Systems – Technologies and applications ... 5
2.1. Introduction ... 5
2.2. Existing Types of Energy Storage Systems ... 6
2.2.1. Pumped Hydroelectric Storage (PHS) ... 6
2.2.2. Compressed Air Energy Storage (CAES) ... 7
2.2.3. Flywheel Energy Storage ... 8
2.2.4. Battery Energy Storage Systems (BESS) ... 9
2.2.4.1. Lead-Acid Battery ... 10
2.2.4.2. Lithium-Ion Battery ... 11
2.2.4.3. Sodium-Sulfur (NaOS) Battery ... 12
2.2.4.4. Nickel-cadmium (NiCd) Battery ... 13
2.2.5. Flow Battery Energy Storage (FBES) ... 14
2.2.6. Capacitors and Supercapacitors ... 15
2.2.7. Superconducting Magnetic Energy Storage ... 16
2.2.8. Hydrogen Storage and Fuel Cell ... 18
2.2.9. Thermal Energy Storage ... 19
2.2.10. Hybrid Electrical Energy Storage ... 20
2.3. Energy Storage Systems Applications ... 21
2.3.1. Load Leveling ... 21
2.3.2. Impact on long distance energy transport ... 23
2.3.3. Congestion Management in the Power Grid ... 24
2.3.4. Renewable Energy Sources Penetration Increase ... 24
2.3.5. Deployment of the Smart Grid Concept ... 27
2.3.6. Continuity and Flexibility of Supply ... 30
2.4. Chapter Summary ... 31
... 33
Problem Formulation... 33
3.1. Introduction and Context ... 33
3.2. General Optimal Power Flow Formulation ... 33
3.3. Expanding the OPF formulation ... 36
3.4. Methodology ... 39
3.5. Software Description ... 41
3.5.1. MATPOWER ... 41
3.5.2. Matpower Optimal Scheduling Tool (MOST) ... 41
... 43
Presentation of the Study Case ... 43
4.1. Introduction and Context ... 43
4.2. Network and Load Characteristics ... 44
4.2.1. Network Configuration, description and characteristics ... 44
xii
5.1. Introduction ... 53
5.2. Case 1 – Initial Case: Influence of Storage in multiperiod AC OPF ... 54
5.2.1. Results Without Storage ... 54
5.2.1.1. Results for MOST without considering the Storage unit ... 54
5.2.1.2. Results for the Multi-Period AC OPF without considering Storage ... 55
5.2.1.3. Results for MOST with losses compensation without Storage ... 60
5.2.1.4. Final observations ... 64
5.2.2. Results with the inclusion of the Storage unit ... 65
5.2.2.1. Results for MOST with a Storage unit and without loss compensation ... 66
5.2.2.2. Results of AC OPF With Storage... 69
5.2.2.3. Results for MOST with loss compensation and storage ... 75
5.2.2.4. Final Observations ... 78
5.2.3. Case 1 Conclusions ... 79
5.3. Case 2 – Avoiding generator start with the use of the Storage Unit ... 80
5.3.1. Storage Profile Definition... 81
5.3.2. Multiperiod AC OPF Analysis ... 82
5.3.2.1. Without Storage ... 82
5.3.2.2. With Storage ... 85
5.3.3. MOST with Lost compensation analysis ... 89
5.3.3.1. Without the Storage Unit ... 89
5.3.3.2. With the Storage Unit ... 91
5.3.4. Case 2 Conclusions ... 96
5.4. Case 3 – Analyzing the influence of the storage unit location on the system losses 97 5.4.1. First Iteration of MOST ... 97
5.4.2. Multiperiod AC OPF with the Storage unit on Bus 5 ... 99
5.4.3. MOST with loss compensation with the storage unit on Bus 5 ... 104
5.4.4. Case 3 Conclusions ... 107
... 109
Conclusions and Future Works ... 109
6.1. Conclusions ... 109
6.2. Future Works ... 111
References ... 113
Annex A ... 119
Per Bus Load for each hour of the system ... 119
Annex B ... 123
Case 1 - Generator Production for each hour in MOST without the storage unit ... 123
Annex C ... 125
Case 1- Generator Production for each hour of the system for the AC OPF ... 125
Annex D ... 127
xiii
List of Figures
Figure 2-1 - Simple layout of a pump hydroelectric storage plant [3] ... 6
Figure 2-2 - Schematic of a Compressed Air Energy Storage System operation [1] ... 7
Figure 2-3 - Flywheel Energy Storage system description [1] ... 8
Figure 2-4 - Simple diagram of how a battery energy storage system works [1] ... 10
Figure 2-5 - Example and scheme of a lead-acid battery [17] ... 11
Figure 2-6 - Simple scheme of the way of operation for a Li-ion battery. The movement of the Li+ ions from the anode to the cathode forces the electrons to circulate and create electric current [19] ... 12
Figure 2-7 - Simple schematic of the constitution of a Sodium-Sulfur battery [22] ... 13
Figure 2-8 - Scheme of how a Nickel-Cadmium battery is constituted [24] ... 13
Figure 2-9 - Simple diagram of the operation of a redox flow battery (Vanadium Redox Flow Battery) [1] ... 14
Figure 2-10 - Simple schematic of a Supercapacitor [3] ... 16
Figure 2-11 - Simple scheme of the composition and operation of a SMES system [3] ... 17
Figure 2-12 - Simple scheme of Hydrogen Storage and Fuel Cell system [3] ... 18
Figure 2-13 - Simple schematic of a Sensible Heat storage system, being integrated into a wind generation unit [3] ... 20
Figure 2-14 – Variation of electric energy costs for the Iberian Market, in 10-07-2010 [42] ... 21
Figure 2-15 - Simple scheme for a load leveling solution with an ESS [43] ... 22
Figure 2-16 - Basic representation of a conventional use of an ESS [44] ... 23
Figure 2-17 - – Evolution of RES in the European scenario [45] ... 25
Figure 2-18 - Evolution of the different types of energy generation installed capacities [46] ... 25
xiv
Figure 2-20 - Simple Scheme of a PV system with Energy Storage [50] ... 27
Figure 2-21 - A simple schematic of a Smart Grid, where all the active parts of the grid are connected [52] ... 28
Figure 3-1 - Methodology flow chart ... 39
Figure 4-1 - One-line scheme of the IEEE 30 Bus Network [63] ... 44
Figure 4-2 - Load chart of the total system load during the 24 hours ... 50
Figure 5-1 - Generator total production over 24 hours ... 55
Figure 5-2 - Generator total production over 24 hours ... 56
Figure 5-3 - Difference of production between MOST and the AC OPF for all system's running hours ... 57
Figure 5-4 - Comparison of the system total generation between MOST and the AC OPF ... 57
Figure 5-5 - System per hour dispatch ... 58
Figure 5-6 - System AC losses over time ... 58
Figure 5-7 - Comparison of system total generation with the system's losses ... 59
Figure 5-8 - System loss percentage in all periods ... 59
Figure 5-9 - System Production curves, for each generator, during the 24 hours ... 60
Figure 5-10 - Difference in Production in all generators in MOST without and with loss compensation ... 61
Figure 5-11 - System Total Production comparison ... 62
Figure 5-12 - Difference in production for all generators between MOST with loss compensation and AC OPF ... 63
Figure 5-13 - Total system production comparison between MOST with loss compensation and the AC OPF ... 63
Figure 5-14 - Graphical comparison of the economic dispatch obtained in the three steps of the simulation ... 65
Figure 5-15 - Comparison of dispatches for MOST with and without storage ... 66
Figure 5-16 - Generator and Storage unit production curve for MOST, for the 24 hours of the system ... 67
Figure 5-17 - Difference in production for each generator in MOST with and without storage ... 68
Figure 5-18 - Added Production comparison between MOST with and without Storage ... 68
xv
Figure 5-21 -Comparison of the dispatches per hour of the AC OPF with and without storage
... 70
Figure 5-22 – Production of all generators for the multi-period AC OPF with Storage ... 71
Figure 5-23 - Difference in production in the AC OPFs with and without storage ... 71
Figure 5-24 - Difference in production between the AC OPF and MOST with storage unit ... 72
Figure 5-25 - Total losses comparison between the AC OPF with and without the storage unit ... 73
Figure 5-26 -Comparison of system total production with the system total production ... 74
Figure 5-27 -System total loss percentage per hour ... 74
Figure 5-28 - Comparison of the economic dispatches of MOST with loss compensation, with and without the storage unit ... 75
Figure 5-29 - Generator Production for MOST with loss compensation and storage unit ... 76
Figure 5-30 - Average percentage difference between MOST with loss compensation and the AC OPF, both with storage ... 77
Figure 5-31 - Average Percentage Error of MOST compared to AC OPF ... 77
Figure 5-32 - Difference in generator production between MOST with loss compensation, with and without storage unit ... 78
Figure 5-33 - Comparison of the system's total dispatch for all the steps of the simulation for the multiperiod OPF with Storage ... 79
Figure 5-34 - Storage Unit Charge over time obtained from MOST ... 81
Figure 5-35 - Individual Generator production during the 24 hours of the multiperiod OPF ... 82
Figure 5-36 - System Total production in the 24 hours of the AC OPF ... 83
Figure 5-37 - System total losses over the 24 hours of the system ... 84
Figure 5-38 - Percentage of losses over generation for the multiperiod AC OPF ... 84
Figure 5-39 - Comparison of the economic dispatch for the AC OPF without storage /1) and with storage (2) ... 85
Figure 5-40 – Evolution of the production for each generator and the storage unit in the AC OPF considering Storage ... 86
Figure 5-41 - Comparison of the individual Generator production in the multiperiod AC OPF, with and without the storage unit ... 86
Figure 5-42 – Comparison of the production from Generator 5 in the AC OPF with and without Storage ... 87
Figure 5-43 - Comparison of System's total production between Case 1 and Case 2’s multiperiod AC OPF with Storage ... 87
xvi
Figure 5-45 - Difference in total production between AC OPF with and without storage ... 88 Figure 5-46 - Comparison of the system's losses for the AC OPF with and without storage ... 89 Figure 5-47 - Evolution of generator production for MOST with the AC losses consideration .. 90 Figure 5-48 - System total production for MOST when considering the AC Losses ... 90 Figure 5-49 - Comparison of the system's economic dispatch for MOST, with and without the
storage unit ... 91 Figure 5-50 - Generation comparison between MOST with the storage unit considered, and
MOST without considering the storage ... 92 Figure 5-51 - Individual generator production for MOST with the storage unit ... 92 Figure 5-52 - Generator 5 production in MOST with and without the storage unit in the
system ... 93 Figure 5-53 - Difference in individual generator production between the multiperiod AC OPF
and MOST with loss compensation ... 93 Figure 5-54 - Average difference (in percentage) between the multiperiod AC OPF and MOST
for all the generators of the system ... 94 Figure 5-55 - Total System production comparison between the multiperiod AC OPF and
MOST ... 95 Figure 5-56 - Comparison of the economic dispatch between the multiperiod AC OPF (1) and
MOST (2) ... 95 Figure 5-57 - Individual Generator and Storage Production ... 98 Figure 5-58 - Storage Unit power input/output profile ... 98 Figure 5-59 - Storage Unit Charge levels at the end of each hour after the first iteration of
MOST ... 99 Figure 5-60 - Comparison of Economic dispatch between Case 2 and Case 3 multiperiod AC
OPF ... 100 Figure 5-61 - Individual Generator Production over the 24 hours for the multiperiod AC OPF
with the storage unit on Bus 5 ... 100 Figure 5-62 - Difference in total production between Case 3 and Case 2 multiperiod AC OPF
... 101 Figure 5-63 - Difference between the active losses obtained in Case 3 and Case 2 ... 102 Figure 5-64 - Comparison of system losses between the AC OPF with the storage on Bus 5
and without storage ... 102 Figure 5-65 - Comparison of the loss percentage for the AC OPF without storage and with
storage in bus 1 and 5 ... 103 Figure 5-66 - Graphical Representation of the economic dispatches presented in Table 5-16
xvii
Figure 5-68 - Difference in generator production between MOST in Case 3 and in Case 2 ... 105 Figure 5-69 - Comparison of individual generator production between MOST and the AC OPF,
both with the storage on Bus 5 ... 106 Figure 5-70 - Total system production comparison between MOST and the AC OPF ... 107
xix
List of Tables
Table 4-1 - Generator characteristics ... 45
Table 4-2 - Characteristics of Voltage and Bus Bar classification ... 45
Table 4-3 - System Line Parameters ... 47
Table 4-4 – Transformer data for the system in study ... 48
Table 4-5 - Capacitor banks information ... 48
Table 4-6 – Load per hour to be applied to the network ... 49
Table 4-7 – Original Per Bus of the IEEE 30 Bus Case ... 51
Table 5-1 - Value of the system total dispatch when running MOST ... 54
Table 5-2 - System dispatch for the 24 hours AC OPF ... 56
Table 5-3 - Economic dispatch for MOST with loss consideration ... 60
Table 5-4 - Comparison between the economic dispatches of the various steps of the simulation ... 64
Table 5-5 - Economic dispatch for MOST with storage ... 66
Table 5-6 - Economic dispatch for the AC OPF with Storage Unit ... 70
Table 5-7 - Economic dispatch of the system with MOST considering losses and storage ... 75
Table 5-8 – Table summary of all the economic dispatches of the simulation steps with Storage ... 79
Table 5-9 - Case B generation cost function ... 81
Table 5-10 - Economic dispatch for the multiperiod AC OPF without Storage ... 82
Table 5-11 - Economic dispatch for the multiperiod AC OPF with storage ... 85
xx
Table 5-14 - Economic Dispatch for the multiperiod AC OPF with the storage unit on Bus 5 .. 99
Table 5-15 - Total Active losses for the 24 hours of the system for each of the study cases . 103 Table 5-16 - Values for the economic dispatch of MOST with loss compensation (Case 3 and Case 2) and multiperiod AC OPF for Case 3 ... 104
Table A-1 - System MW Load, per bus, for each hour of the system ... 120
Table A-2 - System MVar load, per bus, for each hour of the system ... 121
Table B-1 - Generator production, per hour, for MOST without the storage unit ... 123
Table C-1 - Individual Generator Production, per hour, for the multiperiod AC OPF without storage ... 125
xxi List of Abbreviations
AC Alternate Current
AFC Alkaline Fuel Cell
BESS Battery Energy Storage Systems
BSS Battery Storage Systems
CAES Compressed Air Energy Storage
DC Direct Current
DG Distributed Generation
DMFC Direct Methanol Fuel Cell
DP Disperse Production
EES Electric Energy Storage
ESS Energy Storage Systems
EV Electric Vehicle
FBES Flow Battery Energy Storage
FES Flywheel Energy Storage
HV High Voltage
MCFC Molten Carbonate Fuel Cell
MOST Matpower Optimal Scheduling Tool NaOS Sodium Sulfur
NiCd Nickel-Cadmium
PAFC Phosphoric Acid Fuel Cell
PEMFC Proton Exchange Membrane Fuel Cell
PHS Pumped Hydroelectric Storage
PSB Polysulfide Bromine
PV Photovoltaic
RES Renewable Energy Sources
SMES Superconducting Magnetic Energy
SOFC Solid Oxide Fuel Cell
TES Thermal Energy Storage
VRB Vanadium Redox Flow
1
Introduction
1.1 - Context
Electrical energy systems are changing. The growth of the electricity grid and the constant growing demand by the consumers changes the system every day, with networks becoming more complex and harder to operate.
At the same time, environmental issues are becoming more serious. Energy production is swiftly moving from the conventional production using big thermal powerplants to a more distributed generation panorama, with renewable energy sources gaining a bigger role on the energy production scenario. With renewable generation, the environmental issues caused by thermal powerplants can be avoided. Production sources like solar and wind power generation do not release pollutant gases to the atmosphere, nor generate toxic waste like the one that is obtained from nuclear reactors. Renewable energy sources provide clean energy, that goes well with the current global panorama of searching for a more sustainable and environmentally friendly way of living.
Renewable energy sources also provide cheaper power to the network, with the overall production costs being diminished when renewable sources start to replace thermal plants. Since the fuel used by these plants is considered free, the overall cost of their energy is lower when it is available for market than the prices offered by thermal powerplants.
However, the growth of renewable energy sources has its limitations. Renewable production is very weather dependent, and can have a variable behavior, ending up being impossible to rely solely on renewable sources to supply an entire energy network. When the weather conditions are not the most appropriate and there are no more generation units available, there might be blackouts since renewable generation will not be enough to supply all the loads.
2
Energy storage might be a key part of that scenario. With the addition of storage units to the network, the variable effect of renewable generation can be mitigated, with energy storage units being able to help to store electricity in periods with surplus of renewable energy and supply the loads when there is generation deficit or high price.
Electric energy storage can be a big part of today’s energy systems even without considering renewable generation. Storage units can contribute to energy production costs reduction by diminishing the amount of energy that is produced by the conventional plants during peak hours where, normally, the electricity cost is more expensive.
1.2 - Objectives
The main objective of this dissertation is to study the influence that the addition of a storage unit can have in an electric energy system, specially the influence that the storage unit can have on the multi-temporal scheduling of generating units during a period of 24 hours.
To perform this study, a simulation tool was needed that could perform a multi-temporal Optimal Power Flow (OPF) with storage and determine the optimal operation cost for the 24 hours of the simulation. Since there was no direct tool capable of giving the desired results, the first objective was to develop an algorithm that could perform the multi-temporal OPF for the network in question, while considering the storage unit, a variable load profile, and transformer and capacitor banks tap optimization.
After the development of the algorithm, the objective was to use it in order to see the influence that the storage unit would have on various aspects, namely, to determine the influence that the addition of storage would have on the system’s economic dispatch for the 24 hours of the problem.
In addition to the study of the economic dispatch, it was also interesting to see the influence that the storage unit would have in the system’s behavior, and how could certain aspects of the system’s performance could be improved by adding the storage unit and studying its installation location.
1.3 - Dissertation Structure
This dissertation is divided into seven different chapters. The first chapter is an introductory chapter, where the context of the problem is presented, and the objectives and structure of the study are presented.
3
The second chapter contains a small presentation of some of the different storage technologies that exist in electric energy systems, giving a simple explanation of how the various technologies work, the advantages and the disadvantages, and some of the scenarios where energy storage systems can be installed. This chapter is also used to present the various applications that energy storage systems can have in the energy grid, and how can they be used to improve various aspects of the energy supply.
Chapter 3 describes the mathematical formulation for the problem. The objective with this chapter was to give a simple and concise explanation of the OPF problem addressed in this dissertation and the mathematical formulation behind the simulation tools used, like MATPOWER and MOST.
Chapter 4 presents the case study to contextualize the reader with the network used for the simulations, and all its characteristics. The load profile used is also presented together with all other relevant data to better understand and reproduce the simulations made.
Chapter 5 presents the various case study that were analyzed and presents all the results and discussion of those results. Each case study consists of a different scenario and tackles a new objective that is meant to be achieved with the usage of the storage unit. Each study case has conclusions and discussion around the results obtained so that the reader can understand the logic of each result and understand the purpose of each study.
Chapter 6 is the last chapter of this dissertation and it serves to present the final conclusions that were obtained from this study, as well as presenting future research that can be done to improve this work and to explore new aspects that this dissertation did not cover.
5
Energy Storage Systems – Technologies
and applications
2.1. Introduction
This dissertation starts by providing a general look at the different technologies for electrical energy storage (EES) that currently exists. Even though the main objective of this dissertation is not the storage systems themselves, it is important to present a brief overview of the existing technologies to better contextualize the actual purpose of this study.
There are many different types of EES currently available worldwide. Energy storage is becoming more and more important in the electricity grid and its importance is growing as energy needs become more and more demanding and the control of the system is becoming more difficult.
Therefore, it is important to underline that the main goal this chapter is to contextualize the proposed study: analyze the influence of storage systems on a multi-period OPF in HV systems. For more detailed information about the different storage systems, it is recommended for the reader to consult the list of bibliographical references in this dissertation.
6
2.2. Existing Types of Energy Storage Systems
2.2.1. Pumped Hydroelectric Storage (PHS)
Pumped hydroelectric storage is one of the EES with the richest history, better technical development and larger energy storage capacity. This is represented by the following numbers: in 2012, PHS had an installed capacity of around 120 GW worldwide, and it represented 99% of global storage capacity and contributed to 3% of the world’s total power generation [1] [2].
The operation mode is very simple. A PHS plant consists of two water reservoirs, separated vertically. When power demand is lower, the excess energy will power the pumps that will move the water to the top reservoir. Then during peak hours, when load demands are greater than the production capabilities, the water flows to the lower level reservoir, running through the turbines that will act as primary units to the generators that will produce electrical energy to supply load demands [1]. Figure 2-1 shows a simple model of a PHS plant.
Figure 2-1 - Simple layout of a pump hydroelectric storage plant [3]
The storage capacity depends on the height of the reservoirs and the volume of water that they can store. The rated power of the PHS plant will depend on:
• Water Pressure
• Flow rate between reservoirs
• Rated power of turbines and motors/generation units
PHS plants can exist ranging from 1MW to up to 3000MW of installed power. They operate at approximately 70-80% efficiency and can have a lifespan of up to 40 years [4] [5].
The greatest problem in PHS systems is that they are very dependent on the geographical location of the PHS plant. The ecological impact that PHS have is also worth mentioning. PHS plants are often responsible for the alteration of the fauna of the installation locale, and can
7
cause the retaining of sand, rocks, and even fish and other living organisms that otherwise would follow the natural flow of the river [6]. Other than that, their installation cost is considerably large and the elevated construction time that it takes to build a fully operational PHS plant are also setbacks for this technology, that still is one of the most common EES technologies in the world [1].
2.2.2. Compressed Air Energy Storage (CAES)
Compressed air energy storage (CAES) is a type of ESS that can provide more than 100MW of power from a single CAES plant [1].
The way of operation is the following: during the charging mode, a reversible motor/generator group activates a chain of air compressors that will inject air into the air storage units, storing the air at high pressures for later deflation of the air tanks; in the discharging mode, which typically occurs during peak load hours, the stored air will be released, heated, and then will be directed to the turbines, activating them, who consequently activate the generator groups that will end up producing energy to supply the loads [1]. A simple scheme of how a CAES system operates is shown in Figure 2-2.
Figure 2-2 - Schematic of a Compressed Air Energy Storage System operation [1]
The compressed air energy storage powerplants can be built with a wide arrange of capacities, similarly to the PHS powerplants. The plant capacity will be dependent of the air storage unit’s capacities, the flow of air that can run through the turbines, and the motor/generator unit rated power output.
8
There are many practical uses for this kind of technology, all of them very similar to the ones found on every EES. More details on these applications can be found in 2.3
The bigger barriers to CAES powerplants is the need for an appropriate location. Many CAES systems are installed on abandoned mines or large caves, so that they can use the existing topology forcompressed air storage. This geographical requirement will end up being reflected on the overall cost for the plant installation. If the cost for building the caves and air reservoirs can be avoided, then the overall system cost will diminish. Another disadvantage of CAES plants is the low cycle efficiency, reflected on the operation costs of the plant and the energy that is lost [1].
2.2.3. Flywheel Energy Storage
Flywheel Energy Storage (FES) systems are composed by five major components [7]: • The Flywheel
• Group of bearings
• Reversible Motor Generator • Power Electronics Unit • Vacuum Chamber
FES systems use electric energy to accelerate or deaccelerate the flywheel. That will result in an increase or decrease of the amount of stored kinetic energy transferred from or to the flywheel through the integrated motor generator. When a flywheel loses speed, the energy that is lost is injected to the grid, analogously to how a battery works when it discharges [1]. Figure 2-3 shows a simple scheme of how a FHS system works.
9 FES systems can be split into two major groups [8]:
1. Low-Speed FES – These types of FES systems use steel as the main material for the flywheel and have rotation speeds of under 6000 rpm. They are usually used for short-term and medium/high power applications
2. High-Speed FES – These types of FES systems use carbon fiber as the main material for the flywheel, making it lighter, allowing for bigger rotation speed. They can operate to up to 10000 rpm. They use non-contact magnets to eliminate the wear of the bearings, improving overall system efficiency. The applications for High-Speed FES are always expanding but they are mainly used in high power quality and ride-through capacity in industries like the aerospace industry.
The main weakness of flywheel energy storage systems is that the flywheel suffers from idling losses when the system is on standby, leading to high self-discharges of up to 20% of the stored capacity per hour [9]. Another setback for FES is that they can only provide power in short notice at a very modest rate, so the rate of response to fast fluctuations of the system is not the best. FES systems usually work in parallel with other EES that can provide a fast response at punctual load fluctuations, like Battery storage systems (2.2.4) or even use fuel generators as a backup to respond to those fast responses [1].
2.2.4. Battery Energy Storage Systems (BESS)
Rechargeable batteries are one of the most used energy storage systems, not only in industrial and power grid applications, but also in the everyday life (for instance, in cellphones and laptops).
A BESS consists on several electrochemical cells connected in parallel and in series that will produce electricity at a desired voltage, being the electricity a result of chemical reactions that occur inside the battery. Each cell contains two electrodes of opposing poles (one anode and one cathode) and an electrolyte that can be solid, liquid or even viscous [10] [11].
The battery cell can convert energy in a bidirectional way: it can make the conversion from chemical to electrical energy (discharge) and from electrical to chemical (charge).
10
Figure 2-4 - Simple diagram of how a battery energy storage system works [1]
During the discharge process, the electrochemical reactions occur in both the anode and the cathode. At the eyes of the circuit to which the battery is connected, electrons are emitted by the anode and collected by the cathode. When the battery is in charge mode, the opposite reaction occurs. The battery is charged by applying an external voltage to both the electrodes. A simple scheme of the structure of a BESS, and how it operates is shown on Figure 2-4.
Battery storage systems can have different types of applications, being able to integrate almost every general application for EES. For more detail on EES applications, please attend to 2.3
A BESS applied to the energy grid is relatively fast to be built and implemented, with installation time going only up to 12 months in the worst-case scenario [12]. The installation site can be very flexible, usually with the battery being installed inside a house, a building or close to vital facilities of the installation that the battery will power.
The main setbacks for BESS are the relatively low cycling times and the still high maintenance cost. These factors are the main reason why battery storage systems are not still implemented in a larger scale in the electric system [1]. It is also important to realize that the disposal or recycling of a battery is a process that must be made with extreme care because of the toxic nature of some battery components that are released when dismantling it [13]. Batteries have various chemicals that must be treated in the appropriate manner, to avoid pollution of the ground, water, and even the atmosphere, that can also be polluted by the gasses that batteries can release.
2.2.4.1. Lead-Acid Battery
Composition: Anode – PbO2; Cathode – Pb; Electrolyte – Sulfuric Acid
Pros:
• Fast Response Times;
• Small daily self-discharge rate (less than 0,3% of total capacity); • Relatively high efficiency per operation cycle (63-90%);
11
• Low Capital Costs (50-600$/kWh) [9] [14] [15] ; Cons:
• Relatively low life cycles (Around 2000 charge-discharge cycles); • Low energy Density (50-90 Wh/L);
• Low specific energy (25-50 Wh/Kg) [14] [16]; • Bad performance at low temperatures [1]; Examples of Application:
• Secondary backup PSU for data centers and telecommunication structures; • Energy Management Applications;
• Hybrid and Electric Vehicles application [14] ;
Figure 2-5 - Example and scheme of a lead-acid battery [17]
2.2.4.2. Lithium-Ion Battery
Composition: Anode – Graphitic Carbon; Cathode – Lithium Metal Oxide (LiCoO2, LiMO2);
Electrolyte – Non-Aqueous Organic liquid with dissolved Lithium salts [18]. Pros [9] [13] [14]:
• Fast Response time (approximately few milliseconds); • Good Performance on a small-scale form (1500 – 10000 W/L) • Great values for energy density;
• High specific energy (75-200 Wh/Kg); • High cyclic Efficiency (Around 97%); Cons [1]:
• Requires an on-board computer to manage its operation, increasing the system total cost;
12
• Charge-discharge cycles can affect Li-ion batteries total lifespan, making it shorter after some cycles;
Examples of Application:
• Energy Grid applications, like frequency control, peak shaving and renewable sources integration;
• Hybrid and Electric Vehicles;
Figure 2-6 - Simple scheme of the way of operation for a Li-ion battery. The movement of the Li+ ions from the anode to the cathode forces the electrons to circulate and create electric current [19]
2.2.4.3. Sodium-Sulfur (NaOS) Battery
Composition: Molten Sodium and Molten Sulfur as electrodes. Electrolyte – Solid Beta Alumina. The chemical reactions must occur at around 574-624 Kelvin, to ensure liquid state of the electrodes and guaranteeing the correct and safe operation of the battery [20];
Pros [2] [18] [21]:
• High energy density (150 – 300 Wh/L); • Close to null daily self-discharge;
• Rather high energy capacity, compared to other batteries (up to 244.8 MWh); • High impulse operation capacity;
• Inexpensive and non-toxic materials lead to high recyclability of the batteries (approximately 99%);
Cons [1] [14] [18]:
• High Operating Costs (80$/kW/Year);
• Requires a separated System to ensure that temperatures maintain themselves at the desired range;
13
Figure 2-7 - Simple schematic of the constitution of a Sodium-Sulfur battery [22]
2.2.4.4. Nickel-cadmium (NiCd) Battery
Composition: Uses nickel hydroxide and metallic cadmium as electrodes. Electrolyte – Aqueous alkali solution [1].
Pros [1]:
• High and Robust reliabilities; • Low maintenance Costs Cons [13] [23]:
• Toxic materials used as electrodes can cause environmental disasters if not dealt with appropriately;
• Maximum capacity drastically decreases after charge-discharge cycles, if the battery isn’t fully discharged before the next charge (Memory effect).
Examples of Application [1]:
• Not many successes in using NiCd batteries at a big scale as utility ESS in the power grid. Usage has been discontinued due to the options referred before being safer and more reliable options
14
2.2.5. Flow Battery Energy Storage (FBES)
Flow batteries store energy in two soluble redox couples that are contained in external tanks with liquid electrolyte. The electrolytes in the tanks can be pumped from inside the tanks to the cell stacks, which consist in two electrolyte flow compartments that are divided by ion selective membranes. The operation of a flow battery is based on reduction-oxidation reactions of the electrolyte solutions. While the battery is charging, one of the electrolytes will be oxidized at the anode of the battery. At the same time, the other electrolyte will be reduced at the cathode, converting the electrical energy supplied to the battery to chemical energy. When the battery discharged, the process works in reverse, to convert chemical energy into electrical energy [1].
There are two possible categorizations for flow batteries: Redox Flow batteries and Hybrid flow batteries. The category depends of all electroactive components being dissolved or not in the electrolyte [1].
Figure 2-9 - Simple diagram of the operation of a redox flow battery (Vanadium Redox Flow Battery) [1]
A major advantage of FBES systems is that the rated power of the system is not dependent on the system total storage capacity: it is instead determined by the size of the electrodes and the number of cells in the stack. On the other hand, the storage capacity is determined by the concentration and the amount of the electrolyte [2] [25].
15
FBES systems also have very low self-discharge rates, since the electrolytes are stored in separated sealed tanks, thus avoiding self-discharges of the battery [14] [18].
The major setbacks for this kind of technology include the low performance of the battery that occurs from non-uniform pressure drops and the transfer limitation of the reactant mass. This technology also includes high maintenance costs and more complex system requirements for its integration in an electric system, while compared to other batteries and other ESS [26]. The practical examples of FBES systems have demonstrated the ability to operate in an interval of a few hundred kW, up to a few MW. Still, currently there are not many commercially available FBES systems available [14] [27]. Investigation is being made to diminish the operating costs of the FBES and to improve its efficiency and reliability, ultimately making this technology more suitable for practical ESS applications.
The main types of FBES are [1]:
• Vanadium Redox Flow Battery (VRB) • Zinc Bromine (ZnBr) Flow Battery • Polysulfide Bromine (PSB) Flow Battery
2.2.6. Capacitors and Supercapacitors
Capacitors are composed of at least two electrical conductors, separated by a thin layer of insulator. The conductors usually are metallic foils, and the insulators can be made of ceramic, glass or a plastic film. When the capacitor is charged, the energy is stored on the dielectric material, in the form of an electrostatic field [14]. Capacitors are traditionally selected if the amount of energy to be stored is not too large and if the operating voltage to be deployed is variable. Differently from traditional BESS (2.2.4), capacitors have a higher power density and have shorter charging times. On the other hand, their capacity is fairly limited, the energy density is lower than the ones on BESS and the high self-discharge losses [14] are points to be taken into consideration when using a capacitor as an EES. However, and bearing in mind the said characteristics, capacitors can still be used in certain situations: power quality control, and high voltage power correction. They can also be used to level out the output of power supplies and help with energy recovery in mass transit systems.
Supercapacitors, or electric double-layer capacitors, contain two conductor electrodes, an electrolyte and a porous membrane separator [18], similarly to the flow battery. Figure 2-10 shows how the composition of a supercapacitor
16
Figure 2-10 - Simple schematic of a Supercapacitor [3]
Supercapacitors have both the characteristics of traditional capacitors, but also from electrochemical batteries. Energy is charged as static charge on the surfaces between on the edges between the conductors and the electrolyte.
The main advantages of superconductors as ESS are the large lifespan, of around 10000 charging cycles, and the high energy efficiency, that can go from 84 to 97% [28]. The disadvantages of this technology are the daily self-discharge rates that can be quite high (up to 40% self-discharge rate) and the capital cost for installing a supercapacitor that can be superior than 6000$/kWh [14]. It also worth noting that supercapacitors and capacitors are usually used in short term applications rather than long-term ESS usage. They usually are used as pulse power controllers, bridging power to a certain equipment, UPS devices and other applications. [1]
2.2.7. Superconducting Magnetic Energy Storage
Superconducting Magnetic Energy Storage (SMES) systems are usually divided into three main parts of their composition: a superconducting coil unit, a power conditioning subsystem, and a refrigerator and vacuum subsystem [3] [29]. The system stores the energy in the magnetic field that is generated by the direct current that flows through the superconductor coil. The coil itself was previously cryogenically cooled to a temperature below the superconducting critical temperature.
When electric current passes through a coil, the electric energy is dissipated in the form of heat. This happens due to the resistance of the wires of the coil. However, if the coil’s wires are made of a superconducting material, like mercury or vanadium, and if they are under their superconducting state, resistance is close to null, making it able for the electric energy to be stored without significant losses.
17
When the SMES system is discharging, it can release the stored energy in the AC form using an integrated power converter. The amount of stored energy is dictated by the self-inductance of the coil and the current that flows through it [30]. Figure 2-11 shows a simple schematic of a SMES system.
Figure 2-11 - Simple scheme of the composition and operation of a SMES system [3]
The main advantages of SMES technology are its high-power density that can be up to 4000W/L, response times that can be around the 1 millisecond, quick discharge times, of around 1 minute for a full discharge of the SMES system. The high efficiency levels of around 95% and the long lifetime (up to 30 years) are also points that need to be taken into consideration when considering this technology as an ESS [28] [31] [32]. Comparing the SMES systems to the battery-based systems, SMES systems can be fully discharged with little degradation compared to conventional batteries, even after a large amount of charge-discharge cycles.
The major cons of this type of storage system are the high initial installation costs, that can be as high as 10000$/kWh, or 7200$/kW. They have a daily self-discharge rate of around 10% to 15% of total installed capacity and can contribute to damaging the environment due to their strong magnetic field. [14] [15]. Also, worth mentioning is that the coil, being supercooled, is very sensitive to small temperature variations that can end up causing a loss of stored energy in power and energy management situations. It is expected that these kinds of systems will have a growing impact on the integration of variable renewable energy sources due to their fast response times [33].
18
2.2.8. Hydrogen Storage and Fuel Cell
EES systems based on hydrogen storage and fuel cells are usually separated into two different processes: one for storing energy and the other to produce the electric energy.
Hydrogen production is commonly achieved by using a water electrolysis unit that uses water to obtain the hydrogen. Hydrogen can then be stored in high pressure containers for later use [1] [18]. For converting the hydrogen into electric energy, the fuel cell is the main part of the system, being a key technology in hydrogen-based ESS.
Fuel cells use the stored hydrogen’s chemical energy and oxygen from the air to obtain electric energy [34]. The chemical reaction is the one described on Equation 2-1:
2𝐻2+ 𝑂2→ 2𝐻2𝑂 + 𝐸𝑛𝑒𝑟𝑔𝑦 (2-1)
Apart from the electric energy that is released, heat is also a part of the products of the reaction in Equation 2-1.
There are six major groups of fuel cells [35]: • Alkaline Fuel Cell (AFC)
• Phosphoric Acid Fuel Cell (PAFC) • Solid Oxide Fuel Cell (SOFC) • Molten Carbonate Fuel Cell (MCFC)
• Proton Exchange Membrane Fuel Cell (PEMFC) • Direct Methanol Fuel Cell (DMFC)
Although there isn’t much extension over each type of fuel cell and their applications, it is worth mentioning the different types of technology that exist. In Figure 2-12 we present a simple illustration of how a Hydrogen Storage and Fuel cell system is
19
The production of electric energy using fuel cells and hydrogen storage has some advantages that are worth mentioning: electricity production using fuel cells is, in general, less noisy and produces less pollution than conventional fossil fuel energy production. It is also a more efficient electric energy production than those who use fossil fuels [36]. Besides, it is a technology that is easily scalable, variating from 1kW to hundreds of MW of installed production. Its compact design can also facilitate the integration in certain scenarios. And the combination of hydrogen storage and fuel cell technology can help providing steady electrical supply to the grid or to the system where it is applied. This technology is also a serious candidate for transportation purposes, being an alternative to fossil fuels on motorized vehicles [35]. The dual integration of hydrogen storage and fuel cell can offer power independence and capacity in energy production, storage and usage, due to the separate process. The system can store energy in the hydrogen deposit, while the fuel cell can continue to produce energy.
Although hydrogen storage with fuel cells is still in development stage, there are already some concerns with the technology. First, the disposal of exhaust fuel cells is an issue, due to the toxic materials used as electrodes or catalysts. The degradation of these materials must be taken into consideration, and in due time they must be recycled to toxic waste.
Another point of current research is the costs of implementation of this technology. Research has been made towards cost reduction and the improvement and corroboration of the durability of hydrogen storage with fuel cells [29]. These issues need to be tackled before this type of ESS can be considered for mass implementation.
2.2.9. Thermal Energy Storage
Thermal Energy Storage (TES) systems can accommodate a variety of technology that can store available heat in insulated repositories. This heat can be stored using various techniques that this paper will not detail [37].
TES systems normally are composed by a storage reservoir, a chiller or a built-up refrigeration system, pipes, pumps and control systems. They can be split into two different groups of TES, depending on the operation temperature: low temperature TES and high temperature TES.
Most common low temperature TES exploit underground aquifers or are based on the cryogenic technique. On the other hand, high-temperature TES can include latent heat TES, sensible heat TES and concrete thermal storage [14] [38].
20
Figure 2-13 - Simple schematic of a Sensible Heat storage system, being integrated into a wind generation unit [3]
The technologies before mentioned have different applications, in specific scenarios, depending on their characteristics. An example of said applications is the usage of latent heat storage systems in buildings and in situations where the space is more reduced, due to their high storage energy density, which gives the system a good performance, even with a small dimension reservoir [39]. Other example is the application of cryogenic energy storage that is being used in research and is expected to be used in future power grid management situations. TES systems have various characteristics that are worth being mentioned: They can store large amount of energy without being a major environmental and safety reliability. They also have a small self-discharge ratio that varies from 0.05 to 1% of total system capacity. As said before, they have a good energy density, allowing for small reservoirs to be used (80 to 500 Wh/L) and also possess a good specific energy for the system itself (80-250 Wh/Kg). This is a technology that is also quite cheap, with the initial capital cost variating from 3 to 60$/kWh [14] [40]. But although these aspects, it is still worth mentioning that TES systems have a low cycle efficiency rating, that variates from 30 to 60%, being this still one of the major research and development bumps that needs to be overcome.
Due to the characteristics of this technology, there are many research and study cases being developed in order to better integrate TES systems in the power grid. The main applications that TES systems are being used for are load shifting cases and even electricity generation for heat engine cycles. Peak shaving and industrial power backup are also fields where TES systems are being implemented [14].
2.2.10. Hybrid Electrical Energy Storage
Hybrid Electrical Energy Storage Systems are not an ESS technology for itself. Basically, hybrid energy storage combines two or more EES technologies into one installation in order to take advantage of the various advantages of each ESS. This can be used to achieve specific of a certain usage scenario, meet harsh conditions for the ESS operation, and overall, to improve
21
the performance of the ESS, with each technology used helping to overcome the disadvantages that each has.
One of the examples of Hybrid Electrical Energy Storage systems, ADELE, uses CAES and TES technologies to improve the overall efficiency of the storage system and to avoid the consumption of fossil fuels for energy production [41].
Other example of a hybrid storage system is the combined application of supercapacitors and storage batteries. This will offer a high storage capacity while still offering very fast charge and discharge times for prompter actuation when needed.
2.3. Energy Storage Systems Applications
2.3.1. Load Leveling
The demand in power systems varies along the day. In Portugal, peak demand usually occurs when people arrive home after work and during the evening. This variation of demand is reflected in the cost of energy [2]. Usually, electricity prices are higher during peak-demand periods and lower during the off-peak periods. This happens due to the fact that more expensive generators have to be turned on to fulfill the user demands, resulting in an increase of electricity price [2]. In Figure 2-14 we can see how the price of electricity changes during a day for the Iberian Electric Energy Market (MIBEL). The bars indicate the price of energy for each hour, the blue line indicates the total market energy, including the bilateral contracts, and the orange line indicates the total energy commercialized in the daily market.
Figure 2-14 – Variation of electric energy costs for the Iberian Market, in 10-07-2010 [42] A useful tool to even the electricity prices during the day is called Load Leveling. Load leveling consists of using the energy stored during low demand periods to supply the loads during peak demand periods. This reduces the need for drawing power from the grid, making
0.00 5 000.00 10 000.00 15 000.00 20 000.00 25 000.00 30 000.00 0.00 10.00 20.00 30.00 40.00 50.00 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 M Wh €/M W h
Time of day (Hours)
22
it less demanding for the gird infrastructure and for the peaking power plants [43]. An example of this is shown in Figure 2-15.
Figure 2-15 - Simple scheme for a load leveling solution with an ESS [43]
Being Pmax the maximum power that the grid can supply to the load through the existing
lines, when the demand is bigger than Pmax, there are only two solutions [43]:
1. Increase the grid infrastructure/generator capabilities 2. Install an ESS on the energy system
The ESS will charge during the hours of less power consumption, when the energy price is cheaper. When the demand surpasses Pmax, the ESS will discharge and suppress the needs of the
load, without needing extra energy from the grid. This allows for a postponement of investments to reinforce the infrastructure of the grid, without compromising the quality of service for the consumers. The ESS, in particular a Rechargeable Battery Storage System (BSS), is a good quality solution, being able to be easily connected to the electrical grid. They can provide advantages not just for the consumer, but also for the energy-providers, helping them meet peak-demands and critical loads, while not being constrained by the limitations of the electrical grid.
23
2.3.2. Impact on long distance energy transport
Nowadays, power grids are bigger than ever, and its complexity keeps growing as power demands are getting bigger every day. Consumers have loads that keep increasing and whose location can be very far from the generation facilities [2].
With the increasing number of disperse production (DP) sources, this problem tends to become less disturbing for the grid management. However, Disperse Production still is not a standard in every grid, so we still see a lot of the conventional production in the power systems, with that energy being transporter through the grid and distributed to the loads. Long distance transport of energy has some issues, including the high amount of losses, the higher chances of service interruption [2] and the price of the infrastructure necessary to supply the loads.
ESS can help in these scenarios. While it does need to charge with energy obtained from the grid, the ESS will help diminish the power flow during peak times. With the ESS charged, it can feed loads to which he is connected. This means that the loads will not need to request energy from the power plants, diminishing the amount of energy that needs to be transported from the generation location to the consumer. This will lead to less congestion issues and fewer losses in the grid, reflecting in the reduction of the price of delivering energy to the consumer.
Figure 2-16 - Basic representation of a conventional use of an ESS [44]
The reduction of energy flowing from the main power plants to the consumers will reflect in other ways that will be better explained thorough this chapter.
24
2.3.3. Congestion Management in the Power Grid
The congestion in the grid reflects on the problem mentioned in 2.3.2. As the distance between the loads and the generators increases, the flow of energy from one point to another tends to get bigger, as more and more energy is produced to suppress the growing needs of the consumers [2]. This can lead to the congestion of the electrical lines, who have physical limitations to the amount of energy they can transport at a given time. The loads might not be properly supplied, and it can cause problems in the safety and reliability of the system.
The grid operators try to predict when these congestions might happen, by calculating the future dispatch for the production facilities and the estimated power flow for that given day [2]. However, these predictions might be nullified as unexpected situation might occur that can lead to the congestion of some lines (per example, if one or more major lines happen to go off-service, the power flow will have to be redirected, which can lead to congesting other transmission or distribution lines).
Grid dispatch cannot solve all the congestion problems that exist in a real scenario. When these kinds of problems start to be recurrent, it is a sign that the grid needs to be reinforced in order to prevent them. The most common solutions for solving congestions in the grid is line reinforcement: replacement of older lines by new ones with larger capacity or installing new lines in parallel with the older ones [2].
ESS can help in dealing with this situation. When installed in the appropriate locations of the grid, such as key substations in the end of lines that are usually heavy loaded, the ESS can store energy during off-peak periods, when the loads are smaller [2]. Then, at peak hours, power flows in the grid will not be so big and there is less need for peak production at the powerplants. After charging, the ESS can provide energy to the loads when demand is higher, and the lines are already operating at full capacity, eliminating the problems caused by line congestion. The installation of the ESS will also allow grid upgrade postponement that would be required due to the effects of line congestion. [2]
2.3.4. Renewable Energy Sources Penetration Increase
Renewable energy sources (RES) are becoming more and more usual in the actual scenario of the energy system. Figure 2-17 shows the results of a study made by the European Environment Agency, where we can see the evolution of RES penetration in the European Energy panorama.
25
Figure 2-17 – Evolution of RES in the European scenario [45]
The tendency is for RES penetration to grow more and more, as traditional energy production methods tend to decrease [45]. A study made by the Imperial College of London shows a prediction of the evolution of the different generation capacities that will be operating in Europe up to 2030 [46]. As shown in Figure 2-18, the tendency is for the decrease of conventional fossil fuel production facilities, to be replaced by RES.
Figure 2-18 - Evolution of the different types of energy generation installed capacities [46] It is still important to consider the role of DG in this scenario. As DG will increase, and more and more consumers will have production capability, conventional thermal plants will be only used in order to complement renewable generation (due to weather reasons, intermittency, etc.).
26
Figure 2-19 - RES capacity progress up to 2030 [47]
At the same time, the consumer needs for energy will increase accordantly, as electrical vehicles and other bigger loads will start to be connected to the grid. As that happens, it is important to assure that the quality of service will not be compromised by the bigger penetration of RES on the system. Although RES can be environmental friendly and produce cheaper energy than traditional sources, that comes along with some problems for the grid and for the quality of service.
a. Frequency Regulation
RES are very weather dependent, and that results in production systems that can go from on to off very quickly. RES like solar and wind power have a very intermittent and do not contribute to frequency regulation the same way that conventional thermal generators do [43]. The conservation of energy principle states that the produced energy must be equal to the loads at all time. RES generation depends on weather conditions and have no frequency regulation abilities. With that said, in what concerns frequency regulation, a system with a large penetration of RES is more vulnerable, because conventional generators need to compensate not only load fluctuation but also RES intermittency. An ESS can help in this situation, serving as a frequency regulator for the system, maintaining the output signal of the powerplant with characteristics within the ones accepted by the network [2].
b. Power Fluctuation
Renewable Energy sources will always have the problem of being weather dependent for their operation. This means that, with the current technology, an electric system cannot count on RES alone for supplying every load of the system. If a grid only has RES with no other backup, power outages will be frequent when the weather conditions do not allow for PV and Wind production [2].
27
That is why RES, like solar and wind power, need to be backed up by conventional fossil fuel power plants, whose output is more stable and can produce energy at any given time. That way, when RES production fails, the balance between generation and consumption will be maintained by the activation of conventional power plants. It is estimated that for every 10% of wind penetration in the grid, there is a need of around 2% to 4% of wind installed capability that will need to be supplied by conventional production sources [43].
Another problem that contributes to the power fluctuation of the system is that RES production can be rather inconsistent. PV plants are very dependent of solar irradiance, which can cause fast variations of power output [48].
ESS can help in scenarios of power fluctuation [2]. Large-scale ESS can help preventing loss of load caused by RES intermittency, providing stable supply to the loads thanks to the energy arbitrage of ESS [49]. The location of storage can also be a factor In fighting power outages and output fluctuation of RES. For example, when installing an ESS next to a wind farm, the power output will be more stable and power levels will be better regulated thanks to ESS nullifying the fluctuation of the wind farm. [49].
ESS installation near consumption points is also interesting to mitigate power fluctuations for the consumer. If the user has any type of load who needs a continuous supply, an ESS can provide a stable backup in case of RES failure or a power outage [2].
Figure 2-20 - Simple Scheme of a PV system with Energy Storage [50]
2.3.5. Deployment of the Smart Grid Concept
a. What is the Smart Grid
The electric grid that exists nowadays is becoming outdated. The grid was initially built to be a one-way path from generation to consumption, without being ready for distributed generation [2]. It is not prepared for real-time communication between the grid assets and the
28
grid operators, which makes the job of operating the grid more complicated and mainly based on predictions and estimations. Grid operators rely heavily on predictions (of consumption, power flows, weather conditions and so on) to make dispatches for the future days and to predict how the grid would have to react to the expected situations.
Smart Grids consist in the implementation of new technologies in the grid that will allow for real time communication and for real time information delivery to the grid operator [2] [51]. Not only that, but Smart grids also allow for a bigger system control, being it tap control, generator output, RES control, and overall system overlook through sensors and measurement instruments located thorough the energy grid. This will make the grid operator fully aware of what is happening at any point of the grid at any given moment and provide total control of the system, being it the generation side or the demand side [2].
Advantages of the smart grid include [51]:
• Better efficiency regarding energy transmission; • Quicker restoration periods after failure; • Reduced management and grid operation costs;
• Increased integration of Renewable Energy Sources and other distributed generation;
• More information and control for the common user;
Figure 2-21 - A simple schematic of a Smart Grid, where all the active parts of the grid are connected [52]
b. ESS and Smart Grid applications
ESS can play an essential role in future Smart Grid. as it will contribute to a deeper integration of microgeneration, to congestion management, to load control (of electric vehicles, for instance) [2]. In short, it will make the system work better, more reliable and safer.
The first point worth mentioning is the ability for ESS to control power flows and to help mitigating congestions when installed on the consumer side of substations [2]. The effects of
