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+# Sphinx build info version 1
+# This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
+config: cea4a2da1636e71c934a01d37f0bc81f
+tags: 645f666f9bcd5a90fca523b33c5a78b7

_sources/developer/start.md.txt

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+# Developer's Documenation
+
+> Comming soon...

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+.. Illuminator documentation master file, created by
+   sphinx-quickstart on Wed Jul 31 14:38:44 2024.
+   You can adapt this file completely to your liking, but it should at least
+   contain the root `toctree` directive.
+
+Illuminator documentation
+=========================
+
+The Illuminator is an easy-to-use Energy System Integration 
+Development kit to demystify energy system operation, illustrate challenges 
+that arise due to the energy transition and test 
+state-of-the-art energy management concepts. we utilise Raspberry Pis
+as the individual components of the energy system emulator, 
+and the simulation engine is based on `Mosaik. <https://mosaik.offis.de/>`_
+
+.. toctree::
+   :maxdepth: 2
+   :caption: Contents:
+
+   quick-start
+
+.. toctree::
+   :maxdepth: 2
+   :caption: User's Documentation:
+
+   user/start
+   user/user-guide
+   user/models
+
+.. toctree::
+   :maxdepth: 2
+   :caption: Developer's Documentation:
+
+   developer/start
+
+
+

_sources/quick-start.md.txt

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+# Quick Start
+
+> Comming soon...

_sources/user/start.md.txt

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+# User Documentation
+
+> Comming soon...

_sources/user/user-guide.md.txt

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+# User's Guide
+
+## Configuration
+There are three methods to configurate the cases.
+
+
+### 1. Using Existing Cases
+
+You can use the  provided `config.xml` and `connection.xml` files in the `Cases/` directory. 
+We provide four example in `Cases` folder: 
+  * Residential Case study(`ResidentialCase`) 
+  * Multienergy system case study(`MultienergyCase`) 
+  * Electricity market game case study (`GameCase`) For more information about the electricity market case study, you can reference the [Msc thesis](https://repository.tudelft.nl/islandora/object/uuid:58029e39-5541-4a17-90cd-cc487383beec?collection=education), and 
+  * Distribution voltage control case study (`DNcontrolCase`) .
+
+
+The `config.xml` file is used to define the models in the case and where to 
+run the model. 
+For example in the `config.xml` below, we built a simulation with only Wind and PV models.
+In the configuration below, the wind model runs (localy? in the master?) and the PV model runs in a **client** with IP '192.168.0.1', and the **master** get the PV model's information from the port the **client**'s port `5123`.
+
+```xml
+  #'Wind' ,'python','Models.Wind.wind_mosaik:WindSim'
+  #'PV','connect', '192.168.0.1:5123'
+
+  <?xml version='1.0' encoding='utf-8'?>
+  <data>
+    <row>
+      <index>0</index>
+      <model>Wind</model>
+      <method>python</method>
+      <location>Models.Wind.wind_mosaik:WindSim</location>
+    </row>
+    <row>
+      <index>1</index>
+      <model>PV</model>
+      <method>connect</method>
+      <location>192.168.0.1:5123</location>
+    </row>
+```
+
+The `connection.xml` file sets how the message are transfered from one model to others. 
+For example in the snippet below, the `ctrl` model sends information about 'flow2e' to `electrolyser` to control its hydrogen generating speed. 
+The `electrolyser` send the 'h2_gen' information to model `h2storage` ‘h2_in’ to control the hydrogen storing speed.
+
+```xml
+    #['ctrl', 'electrolyser', 'flow2e'],
+    #['electrolyser', 'h2storage', 'h2_gen', 'h2_in'],
+
+    <row>
+        <index>13</index>
+        <send>ctrl</send>
+        <receive>electrolyser</receive>
+        <message>flow2e</message>
+        <more/>
+      </row>
+      <row>
+        <index>14</index>
+        <send>electrolyser</send>
+        <receive>h2storage</receive>
+        <message>h2_gen</message>
+        <more>h2_in</more>
+```
+
+### 2. Using the 'build configuration' Script
+
+User can configure a case using the python scripts `build_configuration_xml` in the folder `configuration/` directory. By executing the script, the `config.xml` and `connection.xml`
+file will be automatically built. Use  change the configuration by changing the parameters `sim_config` and `connection`.
+
+
+### 3. Drawing Configurations
+
+The Illuminator also provide visualized method to create configuration. The user can use a smart board, touch screen or mouse to configurate 
+the case. To to this, firstly, run `drawpptx.py`. 
+Secondly, draw a configuration by hand and save as a PowerPoint file with a `.pptx` file extension. For example:
+
+<div align="center">
+	<img align="center" src="../_static/img/config.png" width="400">
+</div>
+
+Thirdly, run the script `readppt_connectionxml.py` to build the configuration files.
+
+## Defining Models
+Model parameters, results presentation and real-time simulation are all set in the file `buildmodelse.py`.
+
+```python
+    Battery_initialset = {'initial_soc': 20}
+    Battery_set = {'max_p': 500, 'min_p': -500, 'max_energy': 500,
+            'charge_efficiency': 0.9, 'discharge_efficiency': 0.9,
+            'soc_min': 10, 'soc_max': 90, 'flag': 0, 'resolution': 15}  #p in kW
+    #Set flag as 1 to show fully discharged state; -1 show fully charged,0 show ready to charge and discharge
+
+    h2storage_initial = {'initial_soc': 50}
+    ttrailers_initial = {'initial_soc': 20}
+    h2_set = {'h2storage_soc_min': 10, 'h2storage_soc_max': 90, 'max_h2': 0.3,
+              'min_h2': -0.3, 'flag': 0, 'capacity':30, 'eff': 0.94, 'resolution':resolution}
+    h2trailer_set = {'h2storage_soc_min': 10, 'h2storage_soc_max': 90, 'max_h2': 0.3,
+              'min_h2': -0.3, 'flag': 0, 'capacity':3000, 'eff': 0.94, 'resolution':resolution}
+    # max_h2 min_h2 in m^3/min;
+    # flag as 1 to show fully discharged state; -1 show fully charged,0 show ready to charge and discharge
+    # approx efficiency of compressed hydrogen storage tanks. Roundtrip efficiency
+    # Capacity is max m3 of hydrogen that it can contain
+
+    pv_panel_set ={'Module_area': 1.26, 'NOCT': 44, 'Module_Efficiency': 0.198, 'Irradiance_at_NOCT': 800,
+              'Power_output_at_STC': 250,'peak_power':600}
+    pv_set={'m_tilt':14,'m_az':180,'cap':500,'output_type':'power'}
+    # 'NOCT':degree celsius; 'Irradiance_at_NOCT':W/m2 This is the irradiance that falls on the panel under NOCT conditions
+    # KW. Available in spec sheet of a module
+    load_set={'houses':1000, 'output_type':'power'}
+
+    Wind_set={'p_rated':300, 'u_rated':10.3, 'u_cutin':2.8, 'u_cutout':25, 'cp':0.40, 'diameter':22, 'output_type':'power'}
+    Wind_on_set={'p_rated':300, 'u_rated':10.3, 'u_cutin':2.8, 'u_cutout':25, 'cp':0.40, 'diameter':22, 'output_type':'power'}
+    Wind_off_set={'p_rated':200, 'u_rated':7.5, 'u_cutin':2.8, 'u_cutout':15, 'cp':0.40, 'diameter':15, 'output_type':'power'}
+    #  p_rated  # kW power it generates at rated wind speed and above
+    # u_rated  # m/s #windspeed it generates most power at
+    #  u_cutin  # m/s #below this wind speed no power generation
+    # u_cutout  # m/s #above this wind speed no power generation. Blades are pitched
+    # cp  # coefficient of performance of a turbine. Usually around0.40. Never more than 0.59
+    # powerout = 0  # output power at wind speed u
+    fuelcell_set={'eff':0.45, 'term_eff': 0.2,'max_flow':100, 'min_flow':0,'resolution':resolution}
+
+    electrolyser_set={'eff':0.60,'resolution':resolution, 'term_eff': 0.2,'rated_power':2.3,'ramp_rate':1.5}
+    # term_eff:  percentage of power transformed in effective heat
+
+    RESULTS_SHOW_TYPE={'write2csv':True, 'dashboard_show':False, 'Finalresults_show':True,'database':False,'mqtt':False}
+    #'write2csv':True/Flause   Write the results to csv file
+    # #'Realtime_show':True/Flause, show the results in dashboard
+    # 'Finalresults_show':True/Flause, show the results after finish the simulation
+    # 'mqtt'::True/Flause, send the results outside through mqtt protocol. When this is True, you must set the receiver correctly.
+
+    enetwork_set={'max_congestion': 1000, 'p_loss_m': 0.56, 'length': 300}
+
+    h2network_set={'max_congestion': 700, 'V': 0.0314, 'leakage': 0.03, 'ro': 0.0899}
+    # max_congestion: max internal pressure bar
+    # leakage: % of internal flow loss
+    # ro: gas density kg/m^2 at STP
+
+    heatnetwork_set = {'max_temperature': 300 + 275.15, 'insulation': 0.02, 'ext_temp': 25 + 275.15, 'therm_cond': 0.05,
+                    'length': 100, 'diameter': 0.3, 'density': 1000,  'c': 4.18}
+    # max_temperature : max_temperature allowed before congestion # K
+    # insulation:  insulation layer diameter #m
+    # ext_temp: external temperature # K
+    # therm_cond: thermal conductivity # W/(m·K)
+    # leght: lenght of pipeline # m
+    # diameter: pipe diameter # m
+    # density: water density # kg/m^3
+    # c : Thermal capacity of the medium #kJ/(kg·K)
+
+    h2demand_r_set={'houses':0.5}
+    h2demand_fs_set={'tanks':1}
+    h2demand_ev_set={'cars':1}
+    h2product_set={'houses':1}
+
+
+    heatstorage_set = {'soc_init': 20, 'max_temperature': 300 + 275.15, 'min_temperature': 25+275.15, 'insulation': 0.20,
+                    'ext_temp': 25 + 275.15, 'therm_cond': 0.03,
+                    'length': 2.5, 'diameter': 1.5, 'density': 1000,  'c': 4.18, 'eff': 0.85, 'max_q': 300, 'min_q': -300}
+    # max_temperature : max_temperature allowed before soc max # K
+    # min_temperature : max_temperature allowed before soc min # K
+    # insulation:  insulation layer diameter #m
+    # ext_temp: external temperature # K
+    # therm_cond: thermal conductivity # W/(m·K)
+    # leght: lenght of pipeline # m
+    # diameter: pipe diameter # m
+    # density: water density # kg/m^3
+    # c: Thermal capacity of the medium #kJ/(kg·K)
+    # eff: charge/discharge efficiency
+
+    # Seasonal storage
+    heatstorage_s_set = {'soc_init': 80, 'max_temperature': 300 + 275.15, 'min_temperature': 25+275.15, 'insulation': 0.20,
+                    'ext_temp': 25 + 275.15, 'therm_cond': 0.03,
+                    'length': 10, 'diameter': 2, 'density': 1000,  'c': 4.18, 'eff': 0.85, 'max_q': 300, 'min_q': -300}
+    # Daily storage
+    heatstorage_d_set = {'soc_init': 80, 'max_temperature': 300 + 275.15, 'min_temperature': 25+275.15, 'insulation': 0.20,
+                    'ext_temp': 25 + 275.15, 'therm_cond': 0.03,
+                    'length': 0.5, 'diameter': 1, 'density': 1000,  'c': 4.18, 'eff': 0.85, 'max_q': 300, 'min_q': -300}
+
+    heatdemand_i_set={'factories':1}
+    heatdemand_r_set={'houses':1}
+    heatproduct_set={'utilities':1}
+
+    hp_params = {'hp_model': 'Air_8kW',
+                 'heat_source': 'air',
+                 'cons_T': 35,
+                 'heat_source_T': 4,
+                 'T_amb': 25,
+                 'calc_mode': 'fast',
+                 'number': 15}
+
+    eboiler_set = { 'capacity':30, 'min_load':5, 'max_load':10, 'standby_loss':0.2,
+                    'efficiency':0.8,'resolution':resolution}
+
+    realtimefactor=0
+    #0 as soon as possible. 1/60 using 1 second simulate 1 mintes
+
+    metrics = {'prosumer_s1_0': {'MC': [0.07, 0.10], 'MB': [0.12],'MO': [0.05, 0.25], 'MR': [0.40]},
+               'prosumer_s1_1': {'MC': [0.27], 'MB': [0.20], 'MO': [0], 'MR': [0.33]},
+               'prosumer_s1_2': {'MC': [0.33, 0.07], 'MB': [0.18], 'MO': [0.09, 0.22], 'MR': [0.15]},
+               'prosumer_s1_3': {'MC': [0], 'MB': [0.50], 'MO': [0], 'MR': [0.50]},
+               'prosumer_s1_4': {'MC': [0.10,0.37], 'MB': [0.44], 'MO': [0.01, 0.20], 'MR': [0.20]},
+               'prosumer_s1_5': {'MC': [0.12], 'MB': [0.28], 'MO': [0.17], 'MR': [0.19]},
+    }
+```
+
+## Running Simulations
+
+> This was set up as a shortcut to collect data and do plotting
+
+Run the `simulation creator_**.py` to create and run the simulation based on the provided case and scenario. 
+To see the results via the dashboard, you need Internet and sign up in [wandb software](https://wandb.ai/site).
+The `simple_test.py` shows a simple case with the configuration inside of the file.
+
+
+## Demos
+Four case studies show how to use Illuminator, and to verify the Illuminator’s performance. 
+
+
+### 1. Residencial Case 
+
+The first demo shows a residential energy community system which include Households,
+PV panels, Wind generators, Battery and Hydrogen system
+to achieve electric power self-sufficiency. 
+The controller’s algorithm in this case runs in the **master** RasPi `Controllers/ResidentialController`, and
+the rest **client** simulators are separately deployed in different 
+RasPis. The data flow between the simulators (clients) is also shown in
+the figure below. Based on the inputs, including the generated power
+from PV and Wind, the consuming power of households, and
+the state of charge (Soc) of the Battery and Hydrogen, the
+controller decides the power from the Battery and Fuel cell
+and the power to the Electrolyser. 
+
+In the case study, we use
+simple logic to achieve self-sufficiency. If Battery has enough
+capacity for charging or discharging to achieve power balance,
+use the Battery first. If Battery doesn’t have enough capacity
+to achieve power balance, then use Electrolyser or Fuel cell
+to achieve power balance. All the input data are in the `Scenarios/` directory and all the output data are in file `Result/ResidentialCase/`.
+
+<div align="center">
+	<img align="center" src="../_static/img/case study.jpg" width="300">
+</div>
+
+### 2. Multi-carriers Case 
+The second demo shows the Multi-carriers energy system, which incorporate the electricity
+network, hydrogen network and heat network. All the energy assets are shown in the below figure. 
+
+<div align="center">
+	<img align="center" src="../_static/img/Multienergy.jpg" width="400">
+</div>
+
+### 3. Electricity Trade Game 
+The third demo shows the electricity trade game and more details please refer to this [Msc thesis](https://repository.tudelft.nl/islandora/object/uuid:58029e39-5541-4a17-90cd-cc487383beec?collection=education)
+
+### 4. CIGRE LV Case
+The fourth demo shows the voltage control in the CIGRE LV voltage network. The network model is in the `Models/EleDisNetworkSim/` directory, and the control method is in `Controllers/NetVoltageControllerSim/`