Development of a graphical simulator for microgrids with renewable energies

Equation Chapter 1 Section 1 Final degree project Energy Systems Engineering. Development of a graphical simulator for microgrids with renewable energies Author: Ángel Durán López Supervisor: Carlos Bordons Alba Department of Systems and Automatic Department of Energetic Engineering Higher Technical School of Engineering University of Seville Sevilla, 2019 Development of a graphical simulator for microgrids with renewable energies iii Final degree project Energy Systems Engineering Development of a graphical simulator for microgrids with renewable energies Author: Ángel Durán López Supervisor: Carlos Bordons Alba Profesor titular Department of Systems and Automatic Department of Energetic Engineering Higher Technical School of Engineering University of Seville Sevilla, 2019 Development of a graphical simulator for microgrids with renewable energies v Final degree project: Development of a graphical simulator for microgrids with renewable energies Author: Ángel Durán López Supervisor: Carlos Bordons Alba El tribunal nombrado para juzgar el Proyecto arriba indicado, compuesto por los siguientes miembros: Presidente: Vocales: Secretario: Acuerdan otorgarle la calificación de: Sevilla, 2019 El secretario del Tribunal Development of a graphical simulator for microgrids with renewable energies vii To my family To my teacher Development of a graphical simulator for microgrids with renewable energies ix ACKNOWLEDGEMENTS I would like to express my gratitude to my family because of supporting during these years of University. This work would not have been possible without the great knowledge of Carlos Bordons, who have spent time on my project. Thank you all. Ángel Durán López Sevilla, 2019 Figure 53. Scheme of charging HV1 24 Figure 54. Scheme of discharging HV1 24 Figure 55. Scheme of charging HV2 25 Figure 56. Scheme of discharging HV2 26 Figure 57. SOC vs Cycle (depending on DoD) 27 Figure 58. Generation power 1 31 Figure 59. Load Power 1.1 31 Figure 60. Gross Power 1.1 32 Figure 61. SESs power 1.1 32 Figure 62. SESs SOCs 1.1 33 Figure 63. Balance Power 1.1 33 Figure 64. Grid power 1.1 34 Figure 65. System power 1.1 34 Figure 66. Load Power 1.2 35 Figure 67. Gross power 1.2 35 Figure 68. SESs Power 1.2 36 Figure 69. Change of SOCs 1.2 36 Figure 70. Balance Power 1.2 37 Figure 71. Grid power 1.2 37 Figure 72. Load Power 1.3 38 Figure 73. Gross Power 1.3 38 Figure 74. SESs Power 1.3 39 Figure 75. Change of SOCs 1.3 39 Figure 76. Balance Power 1.3 40 Figure 77. Load Power 1.4 41 Figure 78. Gross Power 1.4 41 Figure 79. SEss Power 1.4 42 Figure 80. Change of SOCs 1.4 42 Figure 81. Balance power 1.4 43 Figure 82. Grid power 1.4 43 Figure 83. Generations 2 44 Figure 84. Load Power 2.1 44 Figure 85. Gross power 2.1 45 Figure 86. SESs power 2.1 45 Figure 87. Change of SOCs 2.1 46 Figure 88. Balance Power 2.1 46 Figure 89. Gris Power 2.1 47 Figure 90. Load power 2.2 47 Figure 91. Gross power 2.2 48 Development of a graphical simulator for microgrids with renewable energies xvii Figure 92. SESs Power 2.2 48 Figure 93. Change of SOCs 2.2 49 Figure 94. Balance Power 2.2 49 Figure 95. Grid Power 2.2 50 Figure 96. Load power 2.3 50 Figure 97. Gross power 2.3 51 Figure 98. SES Power 2.3 51 Figure 99. Change of SOCs 2.3 52 Figure 100. Balance Power 2.3 53 Figure 101. Grid Power 2.3 53 Figure 102. Load Power 2.4 54 Figure 103. Gross Power 2.41 54 Figure 104. SESs Power 2.4 55 Figure 105. Change of SOCs 2.4 55 Figure 106. Balance Power 2.4 56 Figure 107. Grid power 2.4 56 Figure 108. LOAD POWER 3 57 Figure 109. SES Power 3 57 Figure 110. Change of SOcs 3 58 Figure 111. Balance Power 3 58 Notation SES Storage energy system RES Renewable energy system PE Passsive element Inv Inverter PV Photovoltaic WT Windturbine EV Electric vehicle PL Programable load BE Better’ energy LB Lead battery LhB Lithium battery HV Hibrid vehicle SOC State of charge Development of a graphical simulator for microgrids with renewable energies xix 1 INTRODUCTION 1.1 Introduction: [1] As we all know, the renewable energy systems (RES) are increasing in last years, as it is a way of looking for a sustainable world. Renewable are source clean, inexhaustible and it helps to innovation. On the one hand, renewable resources have some troubles, these are not manageable, and these systems produce energy if there are correct meteorological conditions, for example photovoltaic plants need sun’s radiation but it cannot work if there is strong wind. On the other hand, renewable energy systems support to reduce emission of greenhouse’s gases and to raise the economy. Batteries will play a key role in few years because they can help to develop systems with different type of producers and they can solve the problem of RES. Besides, their capability of storing energy is decisive to achive the objectives of reducing use of fossils fuels. 1 In fact, the management of energy will need to use batteries if the RES begins to gain high percentage in annual production because it may be moment what it is necessary to storage energy from grid or to hand energy over to it (Figure 1). 1.2 Microgrid: [2]The aim of microgrid is to manage different way of generation like photovoltaic or micro-gas turbine, and to use it, to storage and/or sold energy. The finally of microgrid depends on situation, because it is not the same if microgrid is a public building like hospital than if it is a residential area. In the first case we are looking for saving money while in the second we can have different proposals like sold energy or saving energy and money. 1 Figure1 U.S Energy Information Administration Figure 1. 1annual energy production (outlook 2019) from U.S Energy Information Administration-eia INTRODUCTION 12 Besides we must keep in mind that the type of control because it may depend on what systems we have in our microgrid and how it is demand and generation power. The scope of microgrid is to become independent from conventional grid or at least partial independent. 1.3 The goals: There are four main objectives: • First, Developing a simulator for microgrid with RES and other systems. • Secondly, Developing a heuristic control for this microgrid. • Third, microgrid can be able to work in island. • Obtaining conclusions whether this type of control is accurate for this microgrid. Development of a graphical simulator for microgrids with renewable energies 13 2 INTA MICROGRID During the section, we are going to explain our microgrid, which is going to simulate, and how simulator is made and what simplifications have been carried out making the control and simulator. 2.1 Description of INTA microgrid. In this section, we can see the different system which are involved in our microgrid (Figure 2). We must dive systems in disparate categories and there will be four main categories. The first category is only passive elements and we put name of passive element (PE). The second category is whether the system only produces energy and we put name of generators. The third category is whether the system only consumes energy and we put name of loads. The forth category is weather the system exchange energy but depending on situation of microgrid and we put name of storage energy systems (SES). 2.2 Category. In this section, we explain the different categories, which elements belong to the specific category and their Figure 2. Scheme of INTA microgrid INTA microgrid 14 objective. 2.2.1 Passive Element: PS is element which doesn’t produce neither properly consumes energy from bus. The aim of PS is to connect different systems to one side. In our case, this side is DC bus, because it is easy to refer almost all elements to that. List of elements: We have 6 inverters. • Inverter 1-PV system 1 (inv1). • Inverter 2-PV system 2 (inv2). • Inverter 3-PV system 3 (inv3). • Inverter 4-PV system 4 (inv4). • Inverter 5-Wind turbine (inv5). • Inverter 6-Load system (inv6). Technical specification: It is only necessary to know efficiency of inverters. The efficiency may be estimated from 0.80 until 0.98, depending on level of power. Table 1Efficiency of inverters Inv1 Inv2 Inv3 Inv4 Inv5 Inv6 Efficiency 0.80 0.80 0.80 0.80 0.90 0.98 2.2.2 Generators: Generators only produce energy which will be consumed or storage, this last one will depend on situation of the microgrid. Generators are connected to DC bus thankfulness to different inverters (inv1; inv2; inv3; inv4 and inv5). List of elements: We are going to have different RES which are one wind turbine and four photovoltaic fields, which do not have equal power production (Figure 3). • PV system 1(PV1). • PV system 2(PV2). • PV system 3(PV3). • PV system 4 (PV4). • Wind turbine (WT). Development of a graphical simulator for microgrids with renewable energies 15 Technical specification PV system 1: PV1 is divided into four group which have the same peak power and then the same electrical specification. Table 2Technical data PV1 PV1(to refer to group) Wpeak 1300 W Vopen circuit (panel) 21.5 V Vmax. power (panel) 16 V Currentshort circuit (panel) 3.35 A Parallel panels 2 Series panels 17 PV system 2: PV2’ Panels are of brand “Solar Innova” and model ESF-M-BIPV-GG-P156-40-161W. Table 3 Technical data PV2 PV2 Wpeak 2415 W Vopen circuit (panel) 22,82 V Vmax. power (panel) 14,6 V Figure 3. Scheme of mainly inverters INTA microgrid 22 • Nominal capacity (C10h): 83,33 Ah. (The same as EV). Electrolyser and storage of hydrogen Electrolyser is brand of NITIDOR (Figure 9). we are going to have some technical specification which are important for our microgrid. • Maximum Consumption power: 5 kW. Figure 8. HV1 & HV2 Development of a graphical simulator for microgrids with renewable energies 23 • Hydrogen production: 1Nm3/h. In case of Hydrogen’ storage, we only need to know capacity of storage and it is 50 l 3 SYSTEM SIMULATION In this section, we are going to describe the simulator and the different [6] blocks, which we are going to use of doing simulations. The software, which we are going to use, is “Simulink”, moreover we are also going to develop some function for simulations. Almost all model blocks have been developed by other members of the research group, except of the block named “vehicle management”, this has been performed by my-self. 3.1 Simplifications: • loss bus power equal 0 W. • Not consider ultracapacitor because it has such a low level of energy storage if we compare to the rest of SES (Ultracapacitor energy is 0,440 Wh while LB energy 36 kWh). • Not consider consume hydrogen from INTA laboratory because this data is unknow. • Efficiency of SESs is around 100% because they are stationary. • Electrolyser only consume energy if there is energy excess. Figure 9. Electrolyser System simulation 24 3.2 Subsystem categories: In the simulator, we are going to have different subsystem. Besides, we are dived SES in two different subsystems, this distinction is going to be explained in the section Subsystem of storage energy systems:. 3.2.1 Subsystem of generators: In this subsystem, we are only going to have generators and to define specification for each block (Figure 10). Besides, we can select the efficiency of each inverter, but we are going to use of specifications of Table 1Efficiency of inverters (14) Parameters of generators are defined in the 2.2.2.2Technical specification for generators. In addition, we are going to display mask about these systems. In the mask of SESs (Figure 11) have to add a file which indicates meteorological conditions, in case of PV the name is “Irradiancy file” while in case of WT the name is “Wind velocity file”. Both of them, we can select the type of condition for our simulations. These files have to be previously loading. In the Test and results, we are going to explain different conditions which we are going to simulate. Figure 10. Subsystem of generators Development of a graphical simulator for microgrids with renewable energies 25 Sun and wind multiplicator have been selected in function to be able to obtain peak power of each RES. Inverters: The mask of inverters is the following (Figure 12). we must only specify the efficiencies which we want. PV system 1: The mask of PV-1 is the following (Figure 13). Figure 12. Mask of inverters for generators Figure 11. Example of RES ‘Mask System simulation 26 We must specify the following technical. PV system 2: The mask of PV-2 is the following (Figure 14). We must specify the following technical data. PV system 3: The mask PV-3 is the following (Figure 15). We must specify the following technical data. Figure 13. Mask of PV-1 Figure 14. Mask of PV-2 Development of a graphical simulator for microgrids with renewable energies 27 PV system 4: The mask PV-4 is the following (Figure 16). We must specify the following technical data. Figure 15. Mask of PV-3 Figure 16. Mask of PV-4 System simulation 28 Wind turbine: The mask of WT is the following (Figure 17). We must specify the following technical data. 3.2.2 Subsystem of loads: In this subsystem, we are only going to have generators and to define specification for each block (Figure 18). Besides, we can select the efficiency of the demand inverter, but we are going to use of specification of ¡Error! No se encuentra el origen de la referencia.. The general mask of subsystem: The mask has different fields which we are going to define (Figure 19). Figure 17. Mask of WT Figure 18. Scheme of loads Development of a graphical simulator for microgrids with renewable energies 29 Table 5 Field and unit of the loads’ Mask Field Unit Power of EV ‘charge Watt Power of EV ‘discharge Watt Power of programable load Watt Time of programable load Hour Maximum SOC of EV Percentage Efficiency of inverter dimensionless Demand: The mask of demand is the following. We are only going to load data of demand profile, which we want. Figure 19. The general mask of loads System simulation 30 Demand Multiplicator has been used to increasing it power. Besides, we are going to define efficiency of inverter for that in a value of 0.90. Programable load: All data necessary for PL has to be defined in the general mask of demand (Figure 19). • Power of programable load (W). • Time of programable load (h). • These values depend on user, so we are going to define the following table (Table 6values of PL): You can define N-value, there isn’t limit. Table 6values of PL value 1 2 3 4 Power of PL (W) 100 500 600 800 Time of PL (h) 1 8 15 22 Electric vehicle: In case of EV there are there mask, which we are going to describe hereunder. The first is the general mask, which you can define (Figure 19 Figure 21): • Power of EV ‘charge (W). • Power of EV ‘discharge (W). • Maximum SOC (%). Figure 20. The mask of demand Development of a graphical simulator for microgrids with renewable energies 31 Table 7Value of EV in the general mask of loads Power of EV ‘charge (W). 5000 Power of EV ‘discharge (W). 50000 Maximum SOC of EV (%) 95 [7]EV has as maximum limit charging in 50 kW, this power is only in fast charge while in half-fast can be as maximum 7,3 kW. Therefore, if we wanted to use of conventional charge Power would be around 3,7 kW. Then, we have decided an intermediate value between conventional charge and half-fast charge. EV has a maximum limit discharge in 80 kW. 8 The second mask is about technical data of battery (Figure 21). We have to calculate the value of C120h because we have the value of C10h. We are going to suppose that relation1𝐶120ℎ 𝐶10ℎ = 1,25 . Using relation1, we have obtained C120h. • C120h: 95,00 Ah. Voltage is known from technical specifications. • Voltage: 360 V. Finally, last mask is vehicle management (Figure 22). • 8 Endesa (company). Figure 21. Mask of battery System simulation 38 3.2.4 Subsystem of hybrid vehicles: The reason why hvs aren’t in SESs is because HVs is sometimes connected to microgrid, so that the subsystem is only formed by hybrid vehicle 1 and hybrid vehicle 2. The general mask of subsystem: The mask has different fields which we are going to define. Table 10 Field of the general mask of hybrid vehicle Field Unit Power 1 Watt Power 2 Watt Initial SOC 1 Percentage Initial SOC 2 Percentage Both powers (1&2) is about discharge vehicle and NOT about charge vehicle, because vehicle are going to charge using exceed power. However, it is going to explain with more details in the section add Hierarchy of control. Figure 31. Scheme of hybrid vehicle Development of a graphical simulator for microgrids with renewable energies 39 Hybrid vehicle-1: In case of hy1 there are there mask, which we are going to describe hereunder. The first is the general mask, which you can define (Figure 34): • Power 1 (hy1’charge) (W). • Maximum SOC (%). Table 11Value of hv-1 in the general mask of loads Power 1 1000 W Initial SOC of hv1 50 % We have to calculate the value of C120h because we have the value of C10h. We are going to suppose that relation1𝐶120ℎ 𝐶10ℎ = 1,25 . Using relation1, we have obtained C120h. • C120h: 95,00 Ah. Voltage is known from technical specifications. • Voltage: 48V. Figure 32. The general mask of hybrid vehicle System simulation 40 Finally, last mask is vehicle management (Figure 35). This has two out signals, and both are type Boolean. In the section Subsystem of vehicle management:, we are going to explain in more details that. We are going to use it because it introduces different periods (): • Period of useful vh1 (use). • Period of charged vh1 (signal). Figure 34. Mask of technical data of vh1 Figure 33. Mask of vh1 management Development of a graphical simulator for microgrids with renewable energies 41 The mask is the following. Table 12 value of vh1 times Value 1 2 3 Get to Charge point (h) 2 9 21 Leave Charge point (h) 6 11 24 Start time of use vh1 (h) 7 12 18 Finish time of use vh1 (h) 8 16 20 You can define N-value, there isn’t limit. Hybrid vehicle-2: In case of hy2 there are there mask, which we are going to describe hereunder. The first is the general mask, which you can define (Figure 32): • Power 2 (hy2’charge) (W). • Initial SOC (%). Table 13Value of hv-2 in the general mask of loads Power 1 1000 W Initial SOC of hv2 50 % We have to calculate the value of C120h because we have the value of C10h. We are going to suppose that Figure 35. Mask of vh1 times System simulation 42 relation1𝐶120ℎ 𝐶10ℎ = 1,25 . Using relation1, we have obtained C120h. • C120h: 95,00 Ah. Voltage is known from technical specifications. • Voltage: 78V. Finally, last mask is vehicle management (Figure 37). This has two out signals, and both are type Boolean. In the section Subsystem of vehicle management:, we are going to explain in more details that. We are going to use it because it introduces different periods (Figure 38): • Period of useful vh2 (use). • Period of charged vh2 (signal). Figure 36. Mask of techincal data of hv2 Figure 37. Mask of vh2 management Development of a graphical simulator for microgrids with renewable energies 43 The mask is the following. Table 14value of vh2 times Value 1 2 3 Get to Charge point (h) 1 8 20 Leave Charge point (h) 5 10 23 Start time of use vh2 (h) 6 11 17 Finish time of use vh2 (h) 7 15 19 You can define N-value, there isn’t limit. 3.2.5 Subsystem of grid: This subsystem represents conventional grid. 3.2.6 Subsystem of vehicle management: This subsystem has been made by the author of this document. The aim of vehicle management is to send a signal which represent gotten and left vehicles of charge point and Figure 38. Mask of vh2 times Figure 39. The subsystem of conventional grid System simulation 44 useful time. We have used of MATLAB for making up a function which is able to read input date from interface and depending on simulation time, output is true or false. If output is true meaning that vehicle is at charge point or being used. If output is false meaning that vehicle isn’t at charge point or isn’t being used. Features of the function: • 3 input data: o Time 1 (gotten or stared to use). o Time 2 (left or finished to use). o Simulation time. • 1 output data: o Signal: True or False. Scrip of the function: function [ out ] = gestor_vehiculos( in ) %% en esta funcion buscamos experimentar el comportamiento de los vehiculos con baterias variando. Development of a graphical simulator for microgrids with renewable energies 45 t1= []; t2=[]; out=double(0.00); sensor=0; N=length(in); n_1=N-1; M=(N-1)/2; M_1=(N-1)/2; m=1; p=1; t1=in(1:M_1); t2=in(M_1+1:n_1); r=length(t1); t_s=in(N); aux_1=t1.*3600; aux_2=t2.*3600; for k=1:r if aux_1(k)<t_s && t_s<aux_2(k) sensor=1; end end if sensor == 1 ; out=1; else out=0; end end Scheme of the vehicle management: In the figure shows the structure of vehicle management, which you can see that it is referred to the charge point because there gotten and left time. The structure is similar in case of another case (useful time). Different data are read from mask. Figure 41. Scheme of vehicle management Figure 40. Example of mask. Energy management in the microgrid 18 18 4.4.1 Blocks of the SESs’ control. We are going to show in detail the control of different SESs. The general mask of SESs’ control. This mask has 9 fields which we are going to define. Table 15Fields of the general mask Field Unit Maximum LB SOC Percentage Minimum operational LB SOC Percentage Maximum LhB SOC Percentage Minimum LhB SOC Percentage Maximum hydrogen SOC Percentage Security LB SOC Percentage Minimum hv1 SOC Percentage Minimum hv2 SOC Percentage Maximum hv SOC Percentage We are going to explain difference between security and minimum LB SOC. It is known that LB can discharge twice, hence it needs to have two level of SOC. Minimum SOC is referred to the first time LB discharges while security SOC is referred to the second time LB does. Development of a graphical simulator for microgrids with renewable energies 19 Lead battery control We are going to dived in three different part because LB may discharge twice, then in first time LB dischargese, we are going to name stage 2 while the second time we are going to name stage 3. Stage 1 if LB is charging. LB’ SOC is reading and it is compared with maximum or minimum SOC, which is defined by user, depending on gross power. Stage 1 This situation happens when LB are charging, and it is simple . Figure 45. Mask of SES' control Energy management in the microgrid 20 20 Stage 2 It is the first time LB’ battery discharges. Stage 2 This situation is when LB’s battery discharge until security SOC and It is last SESs. Figure 46. Scheme ofControl Figure 47. Scheme of control Development of a graphical simulator for microgrids with renewable energies 21 Lithium battery We are going to dived in two different part. We are going to name stage 1 if LhB is charging while stage 2 if LhB is discharging. LhB’ SOC is reading and it is compared with maximum or minimum SOC, which is defined by user, depending on gross power. Stage 1 This situation happens when LhB are charging, and it is simple. Figure 48. Scheme of control Figure 49. Scheme of control Energy management in the microgrid 22 22 Stage 2 this situation happens when LhB are discharging, and it is simple . Electrolyser Electrolyser can only work if there is power excess, hence it is simple. 4.4.2 Blocks of the hvs’ control. We are going to show in detail the control of different hybrid vehicles. Besides, we shouldn’t forget hybrid vehicle aren’t always connected to microgrid. The general mask of hv’ control: The general mask has four fields. Table 16 FIelds of the general mask of hv' control Field Unit Maximum hv1 SOC Percentage Maximum hv2 SOC Percentage Figure 50. Scheme of control Figure 51. Scheme of control Development of a graphical simulator for microgrids with renewable energies 23 Minimum hv1 SOC Percentage Minimum hv2 SOC Percentage Hybrid vehicle 1 Hv1 has more preference than hv2. We are going to dived in three different part because HV1 may charge in two way, then in first time HV1 chargese, we are going to name stage 1 while the second time we are going to name stage 2 andStage 3 if LB is discharging. HV1’ SOC is reading and it is compared with maximum or minimum SOC, which is defined by user, depending on gross power. Stage 1&2 This situation happens when hv1 are charging, and it is simple. Stage 1 is refered to only charge HV and Electrolyser isn’t working. Figure 52. Mask of HV control Energy management in the microgrid 24 24 Stage 2 is refered to charge HV and Electrolyser is working. Stage 3 this situation happens when hv1 are discharging, and it is simple (). Figure 54. Scheme of discharging HV1 Figure 53. Scheme of charging HV1 Development of a graphical simulator for microgrids with renewable energies 25 Hybrid vehicle 2: We are going to dived in three different part because HV1 may charge in two way, then in first time HV12chargese, we are going to name stage 1 while the second time we are going to name stage 2 andStage 3 if LB is discharging. HV2’ SOC is reading and it is compared with maximum or minimum SOC, which is defined by user, depending on gross power. Stage 1 & 2 This situation happens when hv1 are charging, and it is simple. Stage 1 is refered to only charge HV and Electrolyser isn’t working. Stage 2 is refered to charge HV and Electrolyser is working. Stage 3 This situation happens when hv2 are discharging, and it is simple (). Figure 55. Scheme of charging HV2 Energy management in the microgrid 26 26 4.5 Variable of control We are going to have few input variable which control the system and we are going to have output variables which are controlled. Table 17 Control variable INPUT OUTPUT LB’ SOC LB’ Power LhB’ SOC LhB’ Power Hydrogen’ SOC Electrolyser’ Power HV1’ SOC HV1’ Power HV2’ SOC HV2’ Power 4.5.1 Control of SESs: We are going to show value of control variable of each SESs and hv. The value of variable are selected by users Variable values are the following. Table 18Value of different variables Field Value Maximum LB SOC 80% Minimum operational LB SOC 30% Maximum LhB SOC 80% Figure 56. Scheme of discharging HV2 Development of a graphical simulator for microgrids with renewable energies 27 Minimum LhB SOC 30% Maximum hydrogen SOC 99% Security LB SOC 10% Minimum hv1 SOC 50% Minimum hv2 SOC 50% Maximum hv SOC 95% The reason why LB and LB don’t have as maximum SOC of 100% because if they worked within values of 80% their cycle life is longer than if they worked within values of 100%. These similar happen if they work with high DoD, hence we have preferred to work within value of 30%. 9 Reference • Ultracel (company) • 9 Ultracel (company) Figure 57. SOC vs Cycle (depending on DoD) Test and results 34 34 Grid power The conventional Grid absorbs power excess. System power Last graph only shows that system power is 0 W and it is our main goal, hence we aren’t going to show againg this graph. Subtest-2. We are going to have a situation within high level of SOCs, which are near maximum SOC. Load power Figure 64. Grid power 1.1 Figure 65. System power 1.1 Development of a graphical simulator for microgrids with renewable energies 35 In this case, EV’ SOC is of 85%, so it consumes less power than previous subtest. Gross power As we can see, gross power is positive a long time, hence we are going to work in operational excess mode above all. Figure 66. Load Power 1.2 Figure 67. Gross power 1.2 Test and results 36 36 SESs’ power It is expected that SESs storage power excess because of having a long time that, but the best way of seeing this aspect is to show the SOC’ graphic Change of SOSs In this graph, it is easy to see that control is working correctly because SESs are following the control hierarchy. Besides, it validates our control in case of power excess because SESs are absorbing the power excess until maximum SOCs of each SESs. Figure 68. SESs Power 1.2 Figure 69. Change of SOCs 1.2 Development of a graphical simulator for microgrids with renewable energies 37 Balance power Grid power In this graph, we can see that we are going to inject a mount of power in conventional grid. System power The system power is 0 W and it is our main goal. Figure 70. Balance Power 1.2 Figure 71. Grid power 1.2 Test and results 38 38 Subtest-3 We are going to have a situation whose SOCs are near minimum SOC. Load power It is expected that EV’ power raise due to have initial low level of SOC ( 30%). Gross power If we compeer this graph with the case of subtest1.2 we can realize that system is divided in two part essentially, excess and deficit of power, hence the control is going to change both modes. Figure 72. Load Power 1.3 Figure 73. Gross Power 1.3 Development of a graphical simulator for microgrids with renewable energies 39 SESs’ power In this graph shows as SESs have to work injecting and absorbing power, so we can satisfy with control because it is working correctly. Change of SOSs In this situation, SOCs of LB and LhB work within the minimum limits and moreover LB is working almost until security SOC. Then, we can suppose that control is working accurately. Figure 74. SESs Power 1.3 Figure 75. Change of SOCs 1.3 Test and results 40 40 Balance power Although It isn’t 0 W, we can consider that system is right because of having difference of power of 10-12 W. Regardless that is admissible because it is difficult to measure with that tolerance (1x10-12 W). We can considerer Balance power equal 0 W. Grid power System power The system power is 0 W and it is our main goal. Figure 76. Balance Power 1.3 Development of a graphical simulator for microgrids with renewable energies 41 Subtest-4 We are going to have a situation which is a mixture of subtes2-3. Load power Gross power Figure 77. Load Power 1.4 Figure 78. Gross Power 1.4 Test and results 42 42 SESs’ power In this case, SESs can work in both modes. Change of SOSs This graph supports us to see that system is seemed to subtest 1 because of working within limits but not extreme limit (security LB’ SOC). Figure 79. SEss Power 1.4 Figure 80. Change of SOCs 1.4 Development of a graphical simulator for microgrids with renewable energies 43 Balance power This graph is similar of subtest1.Then it shows that EV’ SOC has such important effect on operational modes. Because in both of subtest (1&4) EV’s SOC is same. Grid power System power The power system is 0 W and it is our main goal. Figure 81. Balance power 1.4 Figure 82. Grid power 1.4 Test and results 50 50 Grid power System power The power system is 0 W. Subtest-3 Load power It is expected that EV’ power raise due to have initial low level of SOC Figure 95. Grid Power 2.2 Figure 96. Load power 2.3 Development of a graphical simulator for microgrids with renewable energies 51 Gross power If we compeer this graph with the case of subtest2.2 we can realize that system is divided in two part essentially, excess and deficit of power, hence the control is going to change both operational modes. SESs power In this graph shows as SESs have to work injecting and absorbing power, so we can satisfy with control because it is working correctly. Figure 97. Gross power 2.3 Figure 98. SES Power 2.3 Test and results 52 52 Change of SOCs In this situation, SOCs of LB and LhB work within the minimum limits and moreover LB is working almost until security SOC. We can suppose that the control is working correctly. Besides, HV cannot discharge because they have a SOC under of minimum one. Figure 99. Change of SOCs 2.3 Development of a graphical simulator for microgrids with renewable energies 53 Balance power We need to buy electricity from conventional grid because we don’t have more storage energy. In fact, hybrid vehicle can’t inject power because their SOCs are less than minimum ones. Grid power System power The power system is 0 W. Figure 100. Balance Power 2.3 Figure 101. Grid Power 2.3 Test and results 54 54 Subtest-4 We are going to have a situation which is a mixture of subtes2-3. Load power Gross power Figure 102. Load Power 2.4 Figure 103. Gross Power 2.41 Development of a graphical simulator for microgrids with renewable energies 55 SESs power In this case, SESs can work in both operational modes thought, it has to work in operational deficit mode. Change of SOCs This graph supports us to see that system is seemed to subtest 1 because of working within limits but not extreme limit (security LB’ SOC). Figure 104. SESs Power 2.4 Figure 105. Change of SOCs 2.4 Test and results 56 56 Balance power Amount of sold energy is little. Grid power System power The power system is 0 W. Figure 106. Balance Power 2.4 Figure 107. Grid power 2.4 Development of a graphical simulator for microgrids with renewable energies 57 5.2.3 Test3: In these tests, we aren’t going to have generation power. Load power We can see that EV’ SOC is maximum then EV consumes power further less. SESs power It is obviously that SESs are going to inject power to DC bus even there are able to inject all necessary power. Figure 109. SES Power 3 Figure 108. LOAD POWER 3 Test and results 58 58 Change of SOCs This graph shows that microgrid is operating in Island respect to conventional grid. Balance power we can assume that Balance power is 0 W because the real value is 1x10-12 W. Figure 110. Change of SOcs 3 Figure 111. Balance Power 3 Development of a graphical simulator for microgrids with renewable energies 59 6 CONCLUSIONS. In the last chapter, we have simulated different situation which can be happened with different initial conditions. In the whole of tests, Controller has been able to respond correlty. In fact, the system can work in Island mode for one day, this we have seen in Test3. Furthermore, we can conclude that using a simple stategy and control (heuristic rule in our case), we can satisfy our objectives and reach our goals (Satisfy demadand of electrical energy.). It will be likely interesting that as future projects develop different type of controls for example MPC or fuzzy control and even new strategy of that. We are going to compare with another type of control. MPC is interesting because we are woking with multivariable such as power, voltage and current (which we haven’t paid attention in this project the whole of them), then we can obtain an optimized system. Then, at future MPC can be used in distribution generation. However, it is known that MPC has high level of computational cost therefore MPC is slower than HR. I suppose that MPC will have great tolerance because of having computational cost. Besides, MPC isn’t commercial while HR is that. If we compere FC and HR, FC can work with a large range of systems using a simple model while we have seen that HR begings to complate when we have a lot of systems. Nevetheless, FC needs to stablish set-point which is necessary to have diferene experiences (it is difficult to know), therefore using FC we may modify statagy of control easer than HR. We are going to summary and to compare with HR. Heuristic rules Fuzzy control MPC Strenght • Easy to develop. • Fast. • Comercial. • Simple • Easy to change of strategy. • Set-points • Optimized. • Working with multivariable. Weakness • Not optimized. • Difficul to change of strategy. • Set-points (necessary to have experience). • Less commercial. • More optimized • Very complex. • No commercial. • High computational cost.