├── .gitignore ├── docs ├── assets │ ├── angles.png │ ├── sun_position.jpeg │ └── cover_position.jpeg └── template.md ├── hacs.json ├── .github └── workflows │ └── validate.yml ├── LICENSE ├── auto_sun_blind.jinja ├── README.md ├── blueprints └── auto_sun_blind.yaml └── python-sim └── blind_simulation.ipynb /.gitignore: -------------------------------------------------------------------------------- 1 | 2 | .vscode/settings.json 3 | -------------------------------------------------------------------------------- /docs/assets/angles.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/langestefan/auto-sun-blind/HEAD/docs/assets/angles.png -------------------------------------------------------------------------------- /docs/assets/sun_position.jpeg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/langestefan/auto-sun-blind/HEAD/docs/assets/sun_position.jpeg -------------------------------------------------------------------------------- /docs/assets/cover_position.jpeg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/langestefan/auto-sun-blind/HEAD/docs/assets/cover_position.jpeg -------------------------------------------------------------------------------- /hacs.json: -------------------------------------------------------------------------------- 1 | { 2 | "name": "Auto Sun Blind", 3 | "filename": "auto_sun_blind.jinja", 4 | "render_readme": true 5 | } -------------------------------------------------------------------------------- /.github/workflows/validate.yml: -------------------------------------------------------------------------------- 1 | name: Validate 2 | 3 | on: 4 | push: 5 | pull_request: 6 | schedule: 7 | - cron: "0 0 * * *" 8 | workflow_dispatch: 9 | 10 | jobs: 11 | validate-hacs: 12 | runs-on: "ubuntu-latest" 13 | steps: 14 | - uses: "actions/checkout@v2" 15 | - name: HACS validation 16 | uses: "hacs/action@main" 17 | with: 18 | category: "template" -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | MIT License 2 | 3 | Copyright (c) 2023 Stefan de Lange 4 | 5 | Permission is hereby granted, free of charge, to any person obtaining a copy 6 | of this software and associated documentation files (the "Software"), to deal 7 | in the Software without restriction, including without limitation the rights 8 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell 9 | copies of the Software, and to permit persons to whom the Software is 10 | furnished to do so, subject to the following conditions: 11 | 12 | The above copyright notice and this permission notice shall be included in all 13 | copies or substantial portions of the Software. 14 | 15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR 16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, 17 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE 18 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER 19 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, 20 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE 21 | SOFTWARE. 22 | -------------------------------------------------------------------------------- /auto_sun_blind.jinja: -------------------------------------------------------------------------------- 1 | {%- macro auto_sun_blind(azimuth, distance, height, min_height, def_height, fov_left, fov_right, elev_min, elev_max ) -%} 2 | {% set deg2rad = pi/180 %} 3 | 4 | {%- macro norm(x, min, max) %} 5 | {{ (x - min) / (max - min) }} 6 | {%- endmacro %} 7 | 8 | {%- macro h2perc(x) %} 9 | {{ 100 * float(norm(x, h_min, h_max)) }} 10 | {%- endmacro %} 11 | 12 | {%- macro clipv(x, x_min, x_max) %} 13 | {{ max(min(x, x_max), x_min) }} 14 | {%- endmacro %} 15 | 16 | {% set win_azi = azimuth | default(136) %} 17 | {% set d = distance | default(0.5) %} 18 | {% set h_max = height | default(1.96) %} 19 | {% set h_min = min_height | default(0) %} 20 | 21 | {# FOV #} 22 | {% set azi_left = deg2rad * -(fov_left | default(90)) %} {# Minimum: -90 #} 23 | {% set azi_right = deg2rad * (fov_right | default(90)) %} {# Maximum: 90 #} 24 | {% set elev_high = deg2rad * (elev_max | default(90)) %} {# Maximum: 90 #} 25 | {% set elev_low = deg2rad * (elev_min | default(0)) %} {# Minimum: 0 #} 26 | 27 | {% set sun_azi = state_attr('sun.sun', 'azimuth') %} 28 | {% set sun_ele = state_attr('sun.sun', 'elevation') %} 29 | 30 | {% set def_h = (def_height | default(60)) / 100 * h_max %} 31 | 32 | {% set alpha = deg2rad * sun_ele %} 33 | {% set gamma = deg2rad * ((win_azi - sun_azi + 180) % 360 - 180) %} 34 | 35 | {% set h = (d / cos(gamma)) * tan(alpha) %} 36 | 37 | {# gamma is outside of FOV #} 38 | {% if gamma < azi_left or gamma > azi_right or alpha < elev_low or alpha > elev_high %} 39 | {{ clipv(h2perc(def_h) | round(0) | int , 0, 100) }} 40 | {# gamma is inside of FOV #} 41 | {% else %} 42 | {{ clipv(h2perc(h) | round(0) | int , 0, 100) }} 43 | {% endif %} 44 | {%- endmacro-%} -------------------------------------------------------------------------------- /docs/template.md: -------------------------------------------------------------------------------- 1 | # Custom Template 2 | 3 | A jinja macro to track the position of a vertical cover based on the sun position to block out direct sunlight. 4 | 5 | ### How to import 6 | Home Assistant 2023.4.0 or higher is required to use custom templates. 7 | 8 | You can install it using HACS. HACS only supports custom templates in `experimental mode`. Click on the button to go directly to the right section. 9 | 10 | Manual install is done by copying the contents of [`auto_sun_blind.jinja`](https://github.com/langestefan/auto-sun-blind/blob/main/auto_sun_blind.jinja) to a `.jinja` file in your `config/custom_templates` folder. Run the `homeassistant.reload_custom_templates` service call to load the file. 11 | 12 | ```yaml 13 | {% from 'auto_sun_blind.jinja' import 'auto_sun_blind' %} 14 | {{ auto_sun_blind() }} 15 | ``` 16 | 17 | ## Variables 18 | 19 | |name|default|unit|range|description| 20 | |---|---|---|---|---| 21 | |`azimuth`| 136 | degrees| [0, 359] | The angle of the window measured from the North. | 22 | |`distance`| 0.5 |M| [0,] |The distance from the window you want the beginning of the shadow to fall.| 23 | |`height`| 1.96 |M| [0,]|The height of your window in meters (or actually the maximum height of your blinds, but for most people this will be the same number ofcourse)| 24 | |`min_height`| 0 |M| [0,] |The minimum height in meters when the blinds are fully open. This will be 0 in most cases.| 25 | |`def_height`| 60|%| [0, 100] | The position for the cover to return to when the sun is not within the specified range| 26 | |`fov_left`| 90 |degrees |[0, 90] |The angle on the left side of the window that falls within the range.| 27 | |`fov_right`| 90 |degrees| [0, 90] |The angle on the right side of the window that falls within the range.| 28 | |`elev_min`| 0 |degrees| [0, 90] | The minimal elevation angle | 29 | |`elev_max`| 90 |degrees| [0, 90] |The maximum elevation angle| -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # Auto Sun Blind 2 | Automatically control your sun blinds via home assistant based on the position of the sun. 3 | 4 | This repo contains a `custom_template`, `blueprint`. 5 | 6 | This [forum post](https://community.home-assistant.io/t/automatic-blinds-sunscreen-control-based-on-sun-platform/573818) explains the math behind the project. 7 | 8 | ![example-image](/docs/assets/angles.png) 9 | ## Custom Template 10 | `version 1.0.1` 11 | 12 | A jinja macro to track the position of a vertical cover based on the sun position to block out direct sunlight. 13 | 14 | ### How to import 15 | Home Assistant 2023.4.0 or higher is required to use custom templates. 16 | 17 | You can install it using HACS. HACS only supports custom templates in `experimental mode`. Click on the button to go directly to the right section. 18 | 19 | Manual install is done by copying the contents of [`auto_sun_blind.jinja`](https://github.com/langestefan/auto-sun-blind/blob/main/auto_sun_blind.jinja) to a `.jinja` file in your `config/custom_templates` folder. Run the `homeassistant.reload_custom_templates` service call to load the file. 20 | 21 | ```yaml 22 | {% from 'auto_sun_blind.jinja' import 'auto_sun_blind' %} 23 | {{ auto_sun_blind() }} 24 | ``` 25 | [Click here for additional documentation and instructions on how to use it.](https://github.com/langestefan/auto-sun-blind/blob/main/docs/template.md) 26 | ## Blueprint 27 | `version 1.1.2` 28 | 29 | This project includes a blueprint that you can use without setting up a sensor. 30 | 31 | [![Open your Home Assistant instance and show the blueprint import dialog with a specific blueprint pre-filled.](https://my.home-assistant.io/badges/blueprint_import.svg)](https://my.home-assistant.io/redirect/blueprint_import/?blueprint_url=https%3A%2F%2Fgithub.com%2Flangestefan%2Fauto-sun-blind%2Fblob%2Fmain%2Fblueprints%2Fauto_sun_blind.yaml) 32 | 33 | Features: 34 | 35 | - Multiple cover control (`since v1.1.0`) 36 | - Easy variable control with sliders 37 | - Time-out to save battery or reduce the amount of changing the cover position 38 | - Minimum percentage change to prevent the amount of changing the cover position by small percentage changes 39 | - Add additional actions such as notifications to the automation 40 | - Add conditions like the time of day, minimum amount of lux 41 | - Default height can be templated, which allows for conditions if the sun is not in front of the window. 42 | 43 | -------------------------------------------------------------------------------- /blueprints/auto_sun_blind.yaml: -------------------------------------------------------------------------------- 1 | --- 2 | #version 1.1.3 3 | blueprint: 4 | name: Cover Height 5 | description: "`version 1.1.3` \n 6 | Set cover position based on direct sunlight exposed to window \n\n 7 | Calculations are done internally in the blueprint removing the need to use a sensor to input a value 8 | \n for in depth information on the calculations and variables, check this forum [post](https://community.home-assistant.io/t/automatic-blinds-sunscreen-control-based-on-sun-platform/573818) 9 | \n **Code Owner:** [`@langestefan`](https://community.home-assistant.io/u/langestefan/) 10 | \n **Blueprint by:** [`@basbruss`](https://community.home-assistant.io/u/basbruss/)\n 11 | ![Azimuth/Elevation](https://community-assets.home-assistant.io/original/4X/9/f/9/9f973bf5477df545015516e08fe050f279846b9b.jpeg)" 12 | 13 | domain: automation 14 | input: 15 | cover_entity: 16 | name: Cover 17 | description: "Cover(s) to change position based on sun. \n *Only select entities. Devices will not work!*" 18 | selector: 19 | target: 20 | entity: 21 | domain: cover 22 | azimuth: 23 | name: Azimuth 24 | description: The azimuth of the window/cover [**?**](https://community-assets.home-assistant.io/original/4X/5/2/7/527029c7c138eb6146aac68d34e92376b4560fb6.png) 25 | default: 180 26 | selector: 27 | number: 28 | min: 0 29 | max: 359 30 | mode: slider 31 | step: 1 32 | distance: 33 | name: Distance 34 | description: Distance from the cover to shaded area ![**?**](https://community-assets.home-assistant.io/original/4X/f/2/6/f26221689c32f55b731c5931de5a52791b760e90.jpeg). 35 | default: 0.5 36 | selector: 37 | number: 38 | min: 0.1 39 | max: 3 40 | mode: slider 41 | step: 0.1 42 | unit_of_measurement: "M" 43 | max_height: 44 | name: Cover Height 45 | description: Max height of the cover in Meters. 46 | default: 2.1 47 | selector: 48 | number: 49 | min: 0.1 50 | max: 4 51 | step: 0.1 52 | unit_of_measurement: "M" 53 | min_height: 54 | name: Minimun Height 55 | description: The minimum height in meters when the blinds are fully open. This will be 0 in most cases. 56 | default: 0 57 | selector: 58 | number: 59 | min: 0 60 | max: 4 61 | step: 0.1 62 | unit_of_measurement: "M" 63 | default_height: 64 | name: Default Cover Height 65 | description: The default height of the cover when the sun is not within the range of the window/cover 66 | default: 60 67 | selector: 68 | number: 69 | min: 0 70 | max: 100 71 | mode: slider 72 | step: 1 73 | unit_of_measurement: "%" 74 | default_template: 75 | name: Default height template 76 | description: Overrules set value in **Default Cover Height** 77 | default: "" 78 | selector: 79 | template: 80 | minimum_position: 81 | name: Minimum position cover 82 | description: The lowest position allowed to change the cover to. 83 | default: 0 84 | selector: 85 | number: 86 | min: 0 87 | max: 100 88 | mode: slider 89 | step: 1 90 | unit_of_measurement: "%" 91 | degrees: 92 | name: Field of view 93 | description: Amount of degrees relative to the sun' azimuth; (90 degrees equals 180 fov) 94 | default: 90 95 | selector: 96 | number: 97 | min: 0 98 | max: 90 99 | mode: slider 100 | step: 1 101 | unit_of_measurement: "°" 102 | azimuth_left: 103 | name: "Field of view Left" 104 | description: "**Only change when left and right angles are different** 105 | \n Amount of degrees from left side of the window \n 106 | Only use when left and right angles are not equal" 107 | default: 90 108 | selector: 109 | number: 110 | min: 0 111 | max: 90 112 | mode: slider 113 | step: 1 114 | unit_of_measurement: "°" 115 | azimuth_right: 116 | name: "Field of view Right" 117 | description: "**Only change when left and right angles are different** 118 | \n Amount of degrees from left side of the window \n 119 | Only use when left and right angles are not equal" 120 | default: 90 121 | selector: 122 | number: 123 | min: 0 124 | max: 90 125 | mode: slider 126 | step: 1 127 | unit_of_measurement: "°" 128 | max_elevation: 129 | name: Maximum Elevation 130 | description: Maximum angle of elevation 131 | default: 90 132 | selector: 133 | number: 134 | min: 0 135 | max: 90 136 | mode: slider 137 | step: 1 138 | unit_of_measurement: "°" 139 | min_elevation: 140 | name: Minimum Elevation 141 | description: Minimum angle of elevation 142 | default: 0 143 | selector: 144 | number: 145 | min: 0 146 | max: 90 147 | mode: slider 148 | step: 1 149 | unit_of_measurement: "°" 150 | change_threshold: 151 | name: Minimun percentage change 152 | description: The minimum percentage change to current position of the cover(s) to change position (to save battery) 153 | default: 1 154 | selector: 155 | number: 156 | min: 1 157 | max: 100 158 | mode: slider 159 | step: 1 160 | unit_of_measurement: "%" 161 | time_out: 162 | name: Time-out 163 | description: Minimum time between updates (to save battery) 164 | default: 1 165 | selector: 166 | number: 167 | min: 0 168 | max: 60 169 | mode: slider 170 | step: 1 171 | unit_of_measurement: minutes 172 | condition_mode: 173 | name: Condition mode 174 | description: Set mode of above conditions to AND or OR 175 | default: and 176 | selector: 177 | select: 178 | options: 179 | - label: AND 180 | value: and 181 | - label: OR 182 | value: or 183 | condition: 184 | name: Extra Conditions 185 | description: Extra conditions for the automation 186 | default: [] 187 | selector: 188 | condition: {} 189 | action: 190 | name: Extra Actions 191 | description: Extra actions to run before intial service 192 | default: [] 193 | selector: 194 | action: {} 195 | variables: 196 | cover_entity: !input cover_entity 197 | azimuth: !input azimuth 198 | distance: !input distance 199 | max_height: !input max_height 200 | min_height: !input min_height 201 | default_height: !input default_height 202 | min_position: !input minimum_position 203 | degrees: !input degrees 204 | default_template: !input default_template 205 | azimuth_left: !input azimuth_left 206 | azimuth_right: !input azimuth_right 207 | max_elevation: !input max_elevation 208 | min_elevation: !input min_elevation 209 | cover_height: > 210 | {%- set deg2rad = pi/180 -%} 211 | {# normalize in range [0,1] #} 212 | {%- macro norm(x, min, max) %} 213 | {{ (x - min) / (max - min) }} 214 | {%- endmacro %} 215 | {# convert blind height h to percentage [0,100] #} 216 | {%- macro h2perc(x) %} 217 | {{ 100 * float(norm(x, h_min, h_max)) }} 218 | {%- endmacro %} 219 | {# clip value between [min, max] #} 220 | {%- macro clipv(x, x_min, x_max) %} 221 | {{ max(min(x, x_max), x_min) }} 222 | {%- endmacro %} 223 | {# constants #} 224 | {%- set win_azi = azimuth -%} 225 | {%- set left_azi = azimuth_left | default(90) -%} 226 | {%- set right_azi = azimuth_right | default(90) -%} 227 | {%- set elev_high = deg2rad * (max_elevation | default(90)) -%} {# Maximum: 90 #} 228 | {%- set elev_low = deg2rad * (min_elevation| default(0)) -%} {# Minimum: 0 #} 229 | {%- set d = distance | default(0.5) -%} 230 | {%- set h_max = max_height | default(2.10) -%} 231 | {%- set h_min = min_height | default(0) -%} 232 | {%- set deg = degrees | default(90) -%} 233 | {%- set def = default_height | default(60) -%} 234 | {%- set min_pos = min_position | default(0) -%} 235 | {%- set def_temp = default_template | default('') -%} 236 | {% if def_temp | int(-1) >= 0 %} 237 | {% set def = def_temp %} 238 | {%endif%} 239 | 240 | {# FOV #} 241 | {%- if left_azi != right_azi-%} 242 | {%- set azi_left = deg2rad * -left_azi -%} {# Minimum: -90 #} 243 | {%- set azi_right = deg2rad * right_azi -%} {# Maximum: 90 #} 244 | {%-else-%} 245 | {%- set azi_left = deg2rad * -deg -%} {# Minimum: -90 #} 246 | {%- set azi_right = deg2rad * deg -%} {# Maximum: 90 #} 247 | {%-endif-%} 248 | {%- set fov = deg2rad * deg -%} 249 | {# get sun elevation / azimuth from sun.sun #} 250 | {%- set sun_azi = state_attr('sun.sun', 'azimuth') -%} 251 | {%- set sun_ele = state_attr('sun.sun', 'elevation') -%} 252 | {# default height, when automatic control is off. #} 253 | {%- set def_h = def / 100 * h_max -%} 254 | {%- set alpha = deg2rad * sun_ele -%} 255 | {% set gamma = deg2rad * ((win_azi - sun_azi + 180) % 360 - 180) %} 256 | {%- set h = (d / cos(gamma)) * tan(alpha) -%} 257 | {# gamma is outside of FOV #} 258 | {%- if gamma < azi_left or gamma > azi_right or alpha < elev_low or alpha > elev_high -%} 259 | {{ clipv(h2perc(def_h) | round(0) | int , 0, 100) }} 260 | {# gamma is inside of FOV #} 261 | {%- else -%} 262 | {{ clipv(h2perc(h) | round(0) | int , min_pos, 100) }} 263 | {%- endif -%} 264 | change_threshold: !input change_threshold 265 | time_out: !input time_out 266 | condition_mode: !input condition_mode 267 | dict_var: > 268 | {%- set ns = namespace(list_1=[],name_1=[],list_2=[],name_2=[]) %} 269 | {%- set entity = cover_entity['entity_id'] -%} 270 | {%- if entity is iterable and (entity is not string and entity is not mapping) -%} 271 | {%- set cover = entity -%} 272 | {%- else -%} 273 | {%- set cover = [entity] -%} 274 | {%- endif -%} 275 | {%- for c in cover %} 276 | {%- set position = state_attr(c,'current_position') | int -%} 277 | {%- set con_1 = ((position - cover_height | float) | abs >= change_threshold) 278 | or (cover_height in [default_height, default_template] and position not in [default_height, default_template])%} 279 | {%- set ns.list_1 = ns.list_1 + [con_1] -%} 280 | {%- set con_2 = now() - timedelta(minutes=time_out) >= states[c].last_updated %} 281 | {%- set ns.list_2 = ns.list_2 + [con_2] %} 282 | {%- if con_1 == true -%} 283 | {%- set ns.name_1 = ns.name_1 + [c] -%} 284 | {% endif %} 285 | {%if con_2 == true%} 286 | {%- set ns.name_2 = ns.name_2 + [c] -%} 287 | {% endif %} 288 | {%endfor%} 289 | {%- set dict = { 290 | 'condition_1':ns.list_1, 291 | 'condition_2':ns.list_2, 292 | 'names_1':ns.name_1, 293 | 'names_2':ns.name_2 294 | } %} 295 | {{dict}} 296 | condition_1: > 297 | {{true is in dict_var['condition_1']}} 298 | condition_2: > 299 | {{true is in dict_var['condition_2']}} 300 | entities_1: > 301 | {{dict_var['names_1']}} 302 | entities_2: > 303 | {{dict_var['names_2']}} 304 | trigger: 305 | - platform: state 306 | entity_id: 307 | - sun.sun 308 | condition: !input condition 309 | action: 310 | - choose: 311 | - conditions: 312 | - condition: template 313 | value_template: "{{condition_mode == 'and'}}" 314 | sequence: 315 | - condition: and 316 | conditions: 317 | - condition: template 318 | value_template: "{{condition_1}}" 319 | - condition: template 320 | value_template: "{{condition_2}}" 321 | - choose: [] 322 | default: !input action 323 | - service: cover.set_cover_position 324 | data: 325 | position: "{{ cover_height | int(0) }}" 326 | target: 327 | entity_id: > 328 | {%- if condition_1 == true -%} 329 | {{entities_1}} 330 | {%- else -%} 331 | {{entities_2}} 332 | {%endif%} 333 | - conditions: 334 | - condition: template 335 | value_template: "{{condition_mode == 'or'}}" 336 | sequence: 337 | - condition: or 338 | conditions: 339 | - condition: template 340 | value_template: "{{condition_1}}" 341 | - condition: template 342 | value_template: "{{condition_2}}" 343 | - choose: [] 344 | default: !input action 345 | - service: cover.set_cover_position 346 | data: 347 | position: "{{ cover_height | int(0) }}" 348 | target: 349 | entity_id: > 350 | {%- if condition_1 == true -%} 351 | {{entities_1}} 352 | {%- else -%} 353 | {{entities_2}} 354 | {%endif%} 355 | mode: single 356 | -------------------------------------------------------------------------------- /python-sim/blind_simulation.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "attachments": {}, 5 | "cell_type": "markdown", 6 | "metadata": {}, 7 | "source": [ 8 | "Imports" 9 | ] 10 | }, 11 | { 12 | "cell_type": "code", 13 | "execution_count": 1, 14 | "metadata": {}, 15 | "outputs": [], 16 | "source": [ 17 | "from pvlib import solarposition\n", 18 | "import pandas as pd\n", 19 | "import numpy as np\n", 20 | "np.set_printoptions(suppress=True)\n", 21 | "import matplotlib.pyplot as plt" 22 | ] 23 | }, 24 | { 25 | "attachments": {}, 26 | "cell_type": "markdown", 27 | "metadata": {}, 28 | "source": [ 29 | "Solar position" 30 | ] 31 | }, 32 | { 33 | "cell_type": "code", 34 | "execution_count": 2, 35 | "metadata": {}, 36 | "outputs": [ 37 | { 38 | "data": { 39 | "image/png": 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", 40 | "text/plain": [ 41 | "
" 42 | ] 43 | }, 44 | "metadata": {}, 45 | "output_type": "display_data" 46 | } 47 | ], 48 | "source": [ 49 | "tz = 'CET'\n", 50 | "lat, lon = 52.35850757579532, 4.881107791550871\n", 51 | "\n", 52 | "# summer\n", 53 | "start_date = '2022-06-05'\n", 54 | "end_date = '2022-06-06'\n", 55 | "\n", 56 | "# winter\n", 57 | "# start_date = '2022-12-05'\n", 58 | "# end_date = '2022-12-06'\n", 59 | "\n", 60 | "times = pd.date_range(start=start_date, end=end_date, freq='5min', tz=tz)\n", 61 | "solpos = solarposition.get_solarposition(times, lat, lon)\n", 62 | "\n", 63 | "# plot of elevation and azimuth\n", 64 | "plt.figure(figsize=(15, 5))\n", 65 | "solpos['elevation'].plot(label='elevation')\n", 66 | "solpos['azimuth'].plot(label='azimuth')\n", 67 | "plt.ylabel('Angle [°]')\n", 68 | "plt.xlabel('Time [HH:MM]')\n", 69 | "plt.legend()\n", 70 | "plt.show()" 71 | ] 72 | }, 73 | { 74 | "attachments": {}, 75 | "cell_type": "markdown", 76 | "metadata": {}, 77 | "source": [ 78 | "Calculate heights of blind" 79 | ] 80 | }, 81 | { 82 | "cell_type": "code", 83 | "execution_count": 3, 84 | "metadata": {}, 85 | "outputs": [], 86 | "source": [ 87 | "from numpy import cos, tan\n", 88 | "from numpy import radians as rad\n", 89 | "\n", 90 | "def calculate_blind_height(sol_elev: float, sol_azi: float, win_azi, azi_min, azi_max, d: float, h_def: float) -> np.ndarray:\n", 91 | " \"\"\"\n", 92 | " Calculate the height of the blind based on the sun position and the panel tilt and azimuth.\n", 93 | "\n", 94 | " :param sol_elev: elevation of the sun in degrees\n", 95 | " :param sol_azi: azimuth of the sun in degrees\n", 96 | " :param win_azi: azimuth of the panel in degrees from north\n", 97 | " :param win_tilt: tilt of the panel in degrees\n", 98 | " :param d: distance between the working area and window facade in meters\n", 99 | " \"\"\"\n", 100 | " # clip azi_min and azi_max to 90\n", 101 | " azi_min = min(azi_min, 90)\n", 102 | " azi_max = min(azi_max, 90)\n", 103 | "\n", 104 | " # surface solar azimuth\n", 105 | " gamma = (win_azi - sol_azi + 180) % 360 - 180\n", 106 | "\n", 107 | " # valid sun positions are those within the blind's azimuth range and above the horizon (FOV)\n", 108 | " valid = (gamma < azi_min) & (gamma > -azi_max) & (sol_elev > 0)\n", 109 | "\n", 110 | " # calculate blind height\n", 111 | " return np.where(valid, (d / cos(rad(gamma))) * tan(rad(sol_elev)), h_def), valid" 112 | ] 113 | }, 114 | { 115 | "attachments": {}, 116 | "cell_type": "markdown", 117 | "metadata": {}, 118 | "source": [ 119 | "Plot heights of blind" 120 | ] 121 | }, 122 | { 123 | "cell_type": "code", 124 | "execution_count": 4, 125 | "metadata": {}, 126 | "outputs": [ 127 | { 128 | "data": { 129 | "image/png": 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", 130 | "text/plain": [ 131 | "
" 132 | ] 133 | }, 134 | "metadata": {}, 135 | "output_type": "display_data" 136 | } 137 | ], 138 | "source": [ 139 | "# variables\n", 140 | "win_azi = 0\n", 141 | "win_tilt = 0\n", 142 | "h_max = 2.0\n", 143 | "dis_workplane = 0.1\n", 144 | "time = solpos.index\n", 145 | "\n", 146 | "# azi min and max\n", 147 | "azi_min = 90\n", 148 | "azi_max = 90\n", 149 | "\n", 150 | "# default height\n", 151 | "h_def = 2.0\n", 152 | "\n", 153 | "# calculate blind height and valid solpos\n", 154 | "blind_height, valid = calculate_blind_height(solpos['elevation'], solpos['azimuth'], win_azi, azi_min=azi_min, azi_max=azi_max, d=dis_workplane, h_def=h_def)\n", 155 | "\n", 156 | "# plot of blind height\n", 157 | "ax, fig = plt.subplots(figsize=(15, 5))\n", 158 | "plt.title(f\"Window azimuth: {win_azi}°, azi_min: {azi_min}°, azi_max: {azi_max}°\")\n", 159 | "plt.plot(solpos['elevation'].values, label='elevation')\n", 160 | "plt.plot(solpos['azimuth'].values, label='azimuth')\n", 161 | "plt.legend(loc='upper left')\n", 162 | "plt.ylabel('Angle [°]')\n", 163 | "\n", 164 | "ax2 = fig.twinx()\n", 165 | "ax2.plot(np.clip(blind_height, 0, h_max), label='blind height', color='red')\n", 166 | "ax2.set_ylim(0, h_max + 0.1)\n", 167 | "ax2.legend(loc='upper right')\n", 168 | "\n", 169 | "plt.xticks(np.arange(0, len(time), 12), time[::12].strftime('%H:%M'), rotation=90)\n", 170 | "\n", 171 | "# plt labels\n", 172 | "plt.xlabel('Time [HH:MM]')\n", 173 | "plt.ylabel('Blind height [m]')\n", 174 | "plt.show()" 175 | ] 176 | } 177 | ], 178 | "metadata": { 179 | "kernelspec": { 180 | "display_name": "pysolar", 181 | "language": "python", 182 | "name": "python3" 183 | }, 184 | "language_info": { 185 | "codemirror_mode": { 186 | "name": "ipython", 187 | "version": 3 188 | }, 189 | "file_extension": ".py", 190 | "mimetype": "text/x-python", 191 | "name": "python", 192 | "nbconvert_exporter": "python", 193 | "pygments_lexer": "ipython3", 194 | "version": "3.10.11" 195 | }, 196 | "orig_nbformat": 4 197 | }, 198 | "nbformat": 4, 199 | "nbformat_minor": 2 200 | } 201 | --------------------------------------------------------------------------------