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Welcome to Demand Response Events Simulator

Build StatusDocumentationCoverageDOI

Incentive Based DR Program: Overview

Incentive based Demand Response programs are voluntary programs offered to residential, commercial, and industrial customer. The participants are offered financial incentives if they voluntarily reduce loads during stressful times for the grid, which are notified as DR events. There are different flavors of these DR programs across the country, with different rules that constitute when the events are called, how often they are called, the duration of these calls and much more. The DR Simulator tool uses various program and simulation parameters to model these incentive-based demand response programs across the country. This enables the user to configure any DR programs from any ISOs and simulate DR events once they provide the simulation parameters based on historical distribution or based on a custom distribution.

Features

  • Use custom or historic distribution
  • Simulate Monte-Carlo samples
  • Customize and configure DR events using marimo app

Installation

Stable Release:pip install dr-simulator

Development Head:pip install git+https://github.com/we3lab/dr-simulator.git

Documentation

For full package documentation please visit we3lab.github.io/dr-simulator.

Development

See CONTRIBUTING.rst for information related to developing the code.

The Commands You Need To Know

  1. pip install -e .[dev]

    This will install your package in editable mode with all the required development dependencies (i.e. tox).

Visualizing the DR Simulator using marimo notebook

You can visualize the DR Simulator using marimo notebook.

  1. Install marimo using pip install marimo
  2. From the terminal, run marimo run dr_events_simulator.py. This will open a new tab in your browser with the marimo notebook in app mode.
  3. You can also run marimo edit dr_events_simulator.py to open the notebook in edit mode.

Upcoming release features

Watch out for the upcoming release features:

  • Optimization framework for the simulated DR events using cvxpy library and finding the optimal capacity bid
  • Include program parametes data for other ISO's DR programs
  • Case study of using DR simulator for finding the optimal capacity bid of SVCW water resource recovery facility in participating in the PG&E's Capacity Bidding Program

About

No description, website, or topics provided.

Resources

Readme
MIT license

Code of conduct

Code of conduct

Contributing

Contributing
Activity
Custom properties

Stars

2 stars

Watchers

2 watching

Forks

0 forks
Report repository

Releases

Packages

Used by

Contributors

Languages

, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all 
 blocks\n(function() {\n function addCopyButtons() {\n document.querySelectorAll('pre code').forEach(function(codeBlock) {\n if (codeBlock.parentElement.hasAttribute('data-copy-added')) return;\n codeBlock.parentElement.setAttribute('data-copy-added', 'true');\n \n var btn = document.createElement('button');\n btn.textContent = 'Copy';\n btn.style.cssText = 'position:absolute;top:4px;right:4px;padding:2px 8px;font-size:11px;background:#4ecdc4;border:none;border-radius:4px;color:#1a1a2e;cursor:pointer;opacity:0.7;transition:opacity 0.2s;';\n btn.onmouseover = function() { this.style.opacity = '1'; };\n btn.onmouseout = function() { this.style.opacity = '0.7'; };\n btn.onclick = function() {\n navigator.clipboard.writeText(codeBlock.textContent).then(function() {\n btn.textContent = 'Copied!';\n setTimeout(function() { btn.textContent = 'Copy'; }, 1500);\n });\n };\n codeBlock.parentElement.style.position = 'relative';\n codeBlock.parentElement.appendChild(btn);\n });\n }\n \n addCopyButtons();\n \n // Re-run on dynamic content\n var observer = new MutationObserver(addCopyButtons);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Add Copy Buttons to Code Blocks");
}
} catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); }
})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '

Skip to content
BranchesTags
Repository files navigation
Welcome to Demand Response Events Simulator
Build StatusDocumentationCoverageDOI
Incentive Based DR Program: Overview
Incentive based Demand Response programs are voluntary programs offered to residential,
commercial, and industrial customer. The participants are offered financial incentives
if they voluntarily reduce loads during stressful times for the grid, which are notified
as DR events. There are different flavors of these DR programs across the country,
with different rules that constitute when the events are called, how often they are
called, the duration of these calls and much more. The DR Simulator tool uses various
program and simulation parameters to model these incentive-based demand response
programs across the country. This enables the user to configure any DR programs from
any ISOs and simulate DR events once they provide the simulation parameters based on
historical distribution or based on a custom distribution.
Features
  • Use custom or historic distribution
  • Simulate Monte-Carlo samples
  • Customize and configure DR events using marimo app
Installation
Stable Release:pip install dr-simulator
Development Head:pip install git+https://github.com/we3lab/dr-simulator.git
Documentation
For full package documentation please visit
we3lab.github.io/dr-simulator.
Development
See CONTRIBUTING.rst for information related to
developing the code.
The Commands You Need To Know
  1. pip install -e .[dev]
    This will install your package in editable mode with all the required
development dependencies (i.e. tox).
Visualizing the DR Simulator using marimo notebook
You can visualize the DR Simulator using marimo notebook.
  1. Install marimo using pip install marimo
  2. From the terminal, run marimo run dr_events_simulator.py. This will open a new tab in your browser with the marimo notebook in app mode.
  3. You can also run marimo edit dr_events_simulator.py to open the notebook in edit mode.
Upcoming release features
Watch out for the upcoming release features:
  • Optimization framework for the simulated DR events using cvxpy library and finding the optimal capacity bid
  • Include program parametes data for other ISO's DR programs
  • Case study of using DR simulator for finding the optimal capacity bid of SVCW water resource recovery facility in participating in the PG&E's Capacity Bidding Program
About
No description, website, or topics provided.
Resources
Readme
MIT license
Code of conduct
Code of conduct
Contributing
Contributing
Activity
Custom properties
Stars
2 stars
Watchers
2 watching
Forks
0 forks
Report repository
Releases
Packages
Used by
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Force GitHub README to respect dark mode\n(function() {\n var style = document.createElement('style');\n style.textContent = '\n .markdown-body {\n color-scheme: dark light;\n }\n .markdown-body pre { background: #161b22 !important; }\n .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }\n .markdown-body table th, .markdown-body table td { border-color: #30363d !important; }\n .markdown-body img { background: #0d1117; }\n .markdown-body blockquote { border-left-color: #8b949e; }\n .markdown-body hr { border-color: #30363d; }\n ';\n document.head.appendChild(style);\n})();", "GitHub Dark Mode README Fix");
}
} catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
Repository files navigation
Welcome to Demand Response Events Simulator
Build StatusDocumentationCoverageDOI
Incentive Based DR Program: Overview
Incentive based Demand Response programs are voluntary programs offered to residential,
commercial, and industrial customer. The participants are offered financial incentives
if they voluntarily reduce loads during stressful times for the grid, which are notified
as DR events. There are different flavors of these DR programs across the country,
with different rules that constitute when the events are called, how often they are
called, the duration of these calls and much more. The DR Simulator tool uses various
program and simulation parameters to model these incentive-based demand response
programs across the country. This enables the user to configure any DR programs from
any ISOs and simulate DR events once they provide the simulation parameters based on
historical distribution or based on a custom distribution.
Features
  • Use custom or historic distribution
  • Simulate Monte-Carlo samples
  • Customize and configure DR events using marimo app
Installation
Stable Release:pip install dr-simulator
Development Head:pip install git+https://github.com/we3lab/dr-simulator.git
Documentation
For full package documentation please visit
we3lab.github.io/dr-simulator.
Development
See CONTRIBUTING.rst for information related to
developing the code.
The Commands You Need To Know
  1. pip install -e .[dev]
    This will install your package in editable mode with all the required
development dependencies (i.e. tox).
Visualizing the DR Simulator using marimo notebook
You can visualize the DR Simulator using marimo notebook.
  1. Install marimo using pip install marimo
  2. From the terminal, run marimo run dr_events_simulator.py. This will open a new tab in your browser with the marimo notebook in app mode.
  3. You can also run marimo edit dr_events_simulator.py to open the notebook in edit mode.
Upcoming release features
Watch out for the upcoming release features:
  • Optimization framework for the simulated DR events using cvxpy library and finding the optimal capacity bid
  • Include program parametes data for other ISO's DR programs
  • Case study of using DR simulator for finding the optimal capacity bid of SVCW water resource recovery facility in participating in the PG&E's Capacity Bidding Program
About
No description, website, or topics provided.
Resources
Readme
MIT license
Code of conduct
Code of conduct
Contributing
Contributing
Activity
Custom properties
Stars
2 stars
Watchers
2 watching
Forks
0 forks
Report repository
Releases
Packages
Used by
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length > 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms");
}
} catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
Repository files navigation
Welcome to Demand Response Events Simulator
Build StatusDocumentationCoverageDOI
Incentive Based DR Program: Overview
Incentive based Demand Response programs are voluntary programs offered to residential,
commercial, and industrial customer. The participants are offered financial incentives
if they voluntarily reduce loads during stressful times for the grid, which are notified
as DR events. There are different flavors of these DR programs across the country,
with different rules that constitute when the events are called, how often they are
called, the duration of these calls and much more. The DR Simulator tool uses various
program and simulation parameters to model these incentive-based demand response
programs across the country. This enables the user to configure any DR programs from
any ISOs and simulate DR events once they provide the simulation parameters based on
historical distribution or based on a custom distribution.
Features
  • Use custom or historic distribution
  • Simulate Monte-Carlo samples
  • Customize and configure DR events using marimo app
Installation
Stable Release:pip install dr-simulator
Development Head:pip install git+https://github.com/we3lab/dr-simulator.git
Documentation
For full package documentation please visit
we3lab.github.io/dr-simulator.
Development
See CONTRIBUTING.rst for information related to
developing the code.
The Commands You Need To Know
  1. pip install -e .[dev]
    This will install your package in editable mode with all the required
development dependencies (i.e. tox).
Visualizing the DR Simulator using marimo notebook
You can visualize the DR Simulator using marimo notebook.
  1. Install marimo using pip install marimo
  2. From the terminal, run marimo run dr_events_simulator.py. This will open a new tab in your browser with the marimo notebook in app mode.
  3. You can also run marimo edit dr_events_simulator.py to open the notebook in edit mode.
Upcoming release features
Watch out for the upcoming release features:
  • Optimization framework for the simulated DR events using cvxpy library and finding the optimal capacity bid
  • Include program parametes data for other ISO's DR programs
  • Case study of using DR simulator for finding the optimal capacity bid of SVCW water resource recovery facility in participating in the PG&E's Capacity Bidding Program
About
No description, website, or topics provided.
Resources
Readme
MIT license
Code of conduct
Code of conduct
Contributing
Contributing
Activity
Custom properties
Stars
2 stars
Watchers
2 watching
Forks
0 forks
Report repository
Releases
Packages
Used by
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links");
}
} catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); }
})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '

Skip to content
BranchesTags
Repository files navigation
Welcome to Demand Response Events Simulator
Build StatusDocumentationCoverageDOI
Incentive Based DR Program: Overview
Incentive based Demand Response programs are voluntary programs offered to residential,
commercial, and industrial customer. The participants are offered financial incentives
if they voluntarily reduce loads during stressful times for the grid, which are notified
as DR events. There are different flavors of these DR programs across the country,
with different rules that constitute when the events are called, how often they are
called, the duration of these calls and much more. The DR Simulator tool uses various
program and simulation parameters to model these incentive-based demand response
programs across the country. This enables the user to configure any DR programs from
any ISOs and simulate DR events once they provide the simulation parameters based on
historical distribution or based on a custom distribution.
Features
  • Use custom or historic distribution
  • Simulate Monte-Carlo samples
  • Customize and configure DR events using marimo app
Installation
Stable Release:pip install dr-simulator
Development Head:pip install git+https://github.com/we3lab/dr-simulator.git
Documentation
For full package documentation please visit
we3lab.github.io/dr-simulator.
Development
See CONTRIBUTING.rst for information related to
developing the code.
The Commands You Need To Know
  1. pip install -e .[dev]
    This will install your package in editable mode with all the required
development dependencies (i.e. tox).
Visualizing the DR Simulator using marimo notebook
You can visualize the DR Simulator using marimo notebook.
  1. Install marimo using pip install marimo
  2. From the terminal, run marimo run dr_events_simulator.py. This will open a new tab in your browser with the marimo notebook in app mode.
  3. You can also run marimo edit dr_events_simulator.py to open the notebook in edit mode.
Upcoming release features
Watch out for the upcoming release features:
  • Optimization framework for the simulated DR events using cvxpy library and finding the optimal capacity bid
  • Include program parametes data for other ISO's DR programs
  • Case study of using DR simulator for finding the optimal capacity bid of SVCW water resource recovery facility in participating in the PG&E's Capacity Bidding Program
About
No description, website, or topics provided.
Resources
Readme
MIT license
Code of conduct
Code of conduct
Contributing
Contributing
Activity
Custom properties
Stars
2 stars
Watchers
2 watching
Forks
0 forks
Report repository
Releases
Packages
Used by
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default");
}
} catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
Repository files navigation
Welcome to Demand Response Events Simulator
Build StatusDocumentationCoverageDOI
Incentive Based DR Program: Overview
Incentive based Demand Response programs are voluntary programs offered to residential,
commercial, and industrial customer. The participants are offered financial incentives
if they voluntarily reduce loads during stressful times for the grid, which are notified
as DR events. There are different flavors of these DR programs across the country,
with different rules that constitute when the events are called, how often they are
called, the duration of these calls and much more. The DR Simulator tool uses various
program and simulation parameters to model these incentive-based demand response
programs across the country. This enables the user to configure any DR programs from
any ISOs and simulate DR events once they provide the simulation parameters based on
historical distribution or based on a custom distribution.
Features
  • Use custom or historic distribution
  • Simulate Monte-Carlo samples
  • Customize and configure DR events using marimo app
Installation
Stable Release:pip install dr-simulator
Development Head:pip install git+https://github.com/we3lab/dr-simulator.git
Documentation
For full package documentation please visit
we3lab.github.io/dr-simulator.
Development
See CONTRIBUTING.rst for information related to
developing the code.
The Commands You Need To Know
  1. pip install -e .[dev]
    This will install your package in editable mode with all the required
development dependencies (i.e. tox).
Visualizing the DR Simulator using marimo notebook
You can visualize the DR Simulator using marimo notebook.
  1. Install marimo using pip install marimo
  2. From the terminal, run marimo run dr_events_simulator.py. This will open a new tab in your browser with the marimo notebook in app mode.
  3. You can also run marimo edit dr_events_simulator.py to open the notebook in edit mode.
Upcoming release features
Watch out for the upcoming release features:
  • Optimization framework for the simulated DR events using cvxpy library and finding the optimal capacity bid
  • Include program parametes data for other ISO's DR programs
  • Case study of using DR simulator for finding the optimal capacity bid of SVCW water resource recovery facility in participating in the PG&E's Capacity Bidding Program
About
No description, website, or topics provided.
Resources
Readme
MIT license
Code of conduct
Code of conduct
Contributing
Contributing
Activity
Custom properties
Stars
2 stars
Watchers
2 watching
Forks
0 forks
Report repository
Releases
Packages
Used by
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers");
}
} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
Repository files navigation
Welcome to Demand Response Events Simulator
Build StatusDocumentationCoverageDOI
Incentive Based DR Program: Overview
Incentive based Demand Response programs are voluntary programs offered to residential,
commercial, and industrial customer. The participants are offered financial incentives
if they voluntarily reduce loads during stressful times for the grid, which are notified
as DR events. There are different flavors of these DR programs across the country,
with different rules that constitute when the events are called, how often they are
called, the duration of these calls and much more. The DR Simulator tool uses various
program and simulation parameters to model these incentive-based demand response
programs across the country. This enables the user to configure any DR programs from
any ISOs and simulate DR events once they provide the simulation parameters based on
historical distribution or based on a custom distribution.
Features
  • Use custom or historic distribution
  • Simulate Monte-Carlo samples
  • Customize and configure DR events using marimo app
Installation
Stable Release:pip install dr-simulator
Development Head:pip install git+https://github.com/we3lab/dr-simulator.git
Documentation
For full package documentation please visit
we3lab.github.io/dr-simulator.
Development
See CONTRIBUTING.rst for information related to
developing the code.
The Commands You Need To Know
  1. pip install -e .[dev]
    This will install your package in editable mode with all the required
development dependencies (i.e. tox).
Visualizing the DR Simulator using marimo notebook
You can visualize the DR Simulator using marimo notebook.
  1. Install marimo using pip install marimo
  2. From the terminal, run marimo run dr_events_simulator.py. This will open a new tab in your browser with the marimo notebook in app mode.
  3. You can also run marimo edit dr_events_simulator.py to open the notebook in edit mode.
Upcoming release features
Watch out for the upcoming release features:
  • Optimization framework for the simulated DR events using cvxpy library and finding the optimal capacity bid
  • Include program parametes data for other ISO's DR programs
  • Case study of using DR simulator for finding the optimal capacity bid of SVCW water resource recovery facility in participating in the PG&E's Capacity Bidding Program
About
No description, website, or topics provided.
Resources
Readme
MIT license
Code of conduct
Code of conduct
Contributing
Contributing
Activity
Custom properties
Stars
2 stars
Watchers
2 watching
Forks
0 forks
Report repository
Releases
Packages
Used by
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Universal Dark Mode - works on any site\n(function() {\n var enabled = true;\n \n function applyDarkMode() {\n if (!enabled) return;\n \n // Create style element if it doesn't exist\n var style = document.getElementById('universal-dark-mode-style');\n if (!style) {\n style = document.createElement('style');\n style.id = 'universal-dark-mode-style';\n document.head.appendChild(style);\n }\n \n // Dark mode CSS - inverts colors but preserves images/video\n style.textContent = '\n /* Invert everything except media */\n html {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #1a1a2e !important;\n }\n \n /* Restore images, videos, iframes, canvas */\n img, video, iframe, canvas, svg, picture, [style*=\"background-image\"] {\n filter: invert(1) hue-rotate(180deg) !important;\n }\n \n /* Preserve specific elements that should not be inverted */\n .no-dark-mode, .no-dark-mode *,\n [data-theme=\"light\"], [data-theme=\"light\"],\n .ace_editor, .ace_editor *,\n .CodeMirror, .CodeMirror *,\n .monaco-editor, .monaco-editor *,\n .markdown-body pre, .markdown-body pre *,\n .highlight, .highlight *,\n pre code, pre code * {\n filter: none !important;\n }\n \n /* Fix common UI elements */\n .modal, .popup, .dropdown-menu, .tooltip, .popover {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #2d2d44 !important;\n border-color: #444 !important;\n }\n \n /* Scrollbars */\n ::-webkit-scrollbar { background: #1a1a2e !important; }\n ::-webkit-scrollbar-thumb { background: #444 !important; }\n ::-webkit-scrollbar-thumb:hover { background: #555 !important; }\n \n /* Selection */\n ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ';\n }\n \n function removeDarkMode() {\n var style = document.getElementById('universal-dark-mode-style');\n if (style) style.remove();\n }\n \n // Toggle with Alt+Shift+D\n document.addEventListener('keydown', function(e) {\n if (e.altKey && e.shiftKey && e.key === 'D') {\n e.preventDefault();\n enabled = !enabled;\n if (enabled) {\n applyDarkMode();\n console.log('[Universal Dark Mode] Enabled');\n } else {\n removeDarkMode();\n console.log('[Universal Dark Mode] Disabled');\n }\n }\n });\n \n // Apply on load\n applyDarkMode();\n \n // Re-apply on dynamic content\n var observer = new MutationObserver(function(mutations) {\n if (enabled && !document.getElementById('universal-dark-mode-style')) {\n applyDarkMode();\n }\n });\n observer.observe(document.head, { childList: true });\n \n console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');\n})();", "Universal Dark Mode");
}
} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
})();

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Welcome to Demand Response Events Simulator
Build StatusDocumentationCoverageDOI
Incentive Based DR Program: Overview
Incentive based Demand Response programs are voluntary programs offered to residential,
commercial, and industrial customer. The participants are offered financial incentives
if they voluntarily reduce loads during stressful times for the grid, which are notified
as DR events. There are different flavors of these DR programs across the country,
with different rules that constitute when the events are called, how often they are
called, the duration of these calls and much more. The DR Simulator tool uses various
program and simulation parameters to model these incentive-based demand response
programs across the country. This enables the user to configure any DR programs from
any ISOs and simulate DR events once they provide the simulation parameters based on
historical distribution or based on a custom distribution.
Features
  • Use custom or historic distribution
  • Simulate Monte-Carlo samples
  • Customize and configure DR events using marimo app
Installation
Stable Release:pip install dr-simulator
Development Head:pip install git+https://github.com/we3lab/dr-simulator.git
Documentation
For full package documentation please visit
we3lab.github.io/dr-simulator.
Development
See CONTRIBUTING.rst for information related to
developing the code.
The Commands You Need To Know
  1. pip install -e .[dev]
    This will install your package in editable mode with all the required
development dependencies (i.e. tox).
Visualizing the DR Simulator using marimo notebook
You can visualize the DR Simulator using marimo notebook.
  1. Install marimo using pip install marimo
  2. From the terminal, run marimo run dr_events_simulator.py. This will open a new tab in your browser with the marimo notebook in app mode.
  3. You can also run marimo edit dr_events_simulator.py to open the notebook in edit mode.
Upcoming release features
Watch out for the upcoming release features:
  • Optimization framework for the simulated DR events using cvxpy library and finding the optimal capacity bid
  • Include program parametes data for other ISO's DR programs
  • Case study of using DR simulator for finding the optimal capacity bid of SVCW water resource recovery facility in participating in the PG&E's Capacity Bidding Program
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