gridsingularity · spyrostz · Jun 3, 2026 · Jun 3, 2026 · Jun 3, 2026
diff --git a/wiki/.circleci/config.yml b/wiki/.circleci/config.yml
@@ -3,14 +3,12 @@ version: 2
 jobs:
   tests:
     docker:
-      - image: python:3.6-alpine3.9
+      - image: python:3.12-alpine
     steps:
       - checkout
       - run:
           command: |
-            pip install virtualenv
-
-            python3.6 -mvirtualenv --no-site-packages --no-download .
+            python3 -m venv .
 
             source bin/activate
 
@@ -30,7 +28,7 @@ jobs:
           command: |
             pip install pylinkvalidator html5lib
 
-            sed -i -e 's/\(decode("ascii")\)/\1.replace(" ", "%20")/g' /usr/local/lib/python3.6/site-packages/pylinkvalidator/urlutil.py
+            sed -i -e 's/\(decode("ascii")\)/\1.replace(" ", "%20")/g' /usr/local/lib/python3.12/site-packages/pylinkvalidator/urlutil.py
 
             pylinkvalidate.py --parser=html5lib -P http://localhost:8000
 

diff --git a/wiki/docs/assets-installation.md b/wiki/docs/assets-installation.md
@@ -47,7 +47,7 @@ For example, a user can input 5 hrs_per_day and give a wider range for hrs_of_da
 - If there is sufficient energy at affordable rates, the load will consume in the first 5 hours, i.e. from 02:00 until 07:00, with no energy demand unmatched.
 - In case energy prices are too high during the time-interval from 04:00 to 16:00, the load will consume from 02:00 until 04:00, turn off, and consume from 16:00 until 18:00, resulting in one hour of energy demand unmatched.
 
-For information on changes in buying and selling rates, please see: [Trading strategies](trading-agents-and-strategies)
+For information on changes in buying and selling rates, please see: [Trading strategies](trading-agents-and-strategies.md)
 
 ## Batteries
 

diff --git a/wiki/docs/battery.md b/wiki/docs/battery.md
@@ -43,7 +43,7 @@ Note: The default setting of the battery component is 100% energy conversion eff
 
 In general all bids and offers follow the physical constraint of the set `max_abs_battery_power_kW value. The accumulated energy per market slot cannot exceed this power value times the length of the market slot, in hours. Energy sold and bought cancel each other out, meaning that if 2kWh are both sold and bought in the same market slot, the relative power remains 0kW.
 
-For the buying rate increase and selling rate decrease behaviour, please see the [Trading Strategies page](trading-agents-and-strategies).
+For the buying rate increase and selling rate decrease behaviour, please see the [Trading Strategies page](trading-agents-and-strategies.md).
 
 ###Buying energy in the [One-Sided Market](market-types.md#one-sided-pay-as-offer-market)
 

diff --git a/wiki/docs/community-settings.md b/wiki/docs/community-settings.md
@@ -33,9 +33,9 @@ In the advanced tab, there are settings referring to the market type information
 
 1. Description: add an optional description of the simulated community
 2. Spot market type: select either the one-sided or the two-sided market type
-      - In the [One-Sided Pay-as-Offer spot market](market-types.md#one-sided-pay-as-offer-market), agents representing energy producers, including prosumers (sellers), post offers in the market with an energy price determined by the assets' [trading strategy](trading-agents-and-strategies)
+      - In the [One-Sided Pay-as-Offer spot market](market-types.md#one-sided-pay-as-offer-market), agents representing energy producers, including prosumers (sellers), post offers in the market with an energy price determined by the assets' [trading strategy](trading-agents-and-strategies.md)
       - In the two-sided spot market, where buyers are able to place bids in the market alongside the offers placed by sellers, users can choose the [Two-Sided Pay-as-Bid Market](market-types.md#two-sided-pay-as-bid-market) or the [Two-Sided Pay-as-Clear Market](market-types.md#two-sided-pay-as-clear-market)
-3. Matching algorithm: select pay-as-bid, pay-as-clear or an external [trading algorithm](trading-agents-and-strategies)
+3. Matching algorithm: select pay-as-bid, pay-as-clear or an external [trading algorithm](trading-agents-and-strategies.md)
 4. Spot markets number: set the number of active spot markets where the energy assets represented by trading agents can trade
 5. Spot market length: set the [length of the spot market](market-types.md#market-slots) in minutes
 6. Tick length: set the [length of ticks](market-types.md#market-ticks) in seconds

diff --git a/wiki/docs/configuration.md b/wiki/docs/configuration.md
@@ -1 +1 @@
-There are four different types of energy assets a user can currently configure when modelling energy communities on Grid Singularity’s web-based simulation user interface, the [Singularity Map](https://gridsingularity.com/singularity-map){target=_blank} - [solar panels (PVs)](solar-panels.md), [consumption (load) profiles](consumption.md), [batteries (storages)](battery.md) and [heat pumps](heat-pumps-general.md). Each simulated community can consist of at least two participating members (homes representing households, buildings or other community members) and up to 1000 digital agents representing assets and/or homes. Simulation users can model an energy community quickly by adding template homes and assets using the express options, or they can configure the technical details and trading parameters by exploring the advanced options for each asset. Each asset within a community can  [trade energy](trading-agents-and-strategies) with other assets, as well as  with the external suppliers via grid network (also termed the grid market). By default, assets shall buy/sell energy locally, interacting with their neighbours, and only in case of any gaps in the local market (either caused by insufficient energy production / consumption in the community, or by inefficient or not affordable trading settings), purchase the energy from the external energy supplier (usually a utility). Trading occurs in [market slots](market-types.md#market-slots), which are by default 15-minute time slots in which energy assets can exchange energy at market rates. The market slot length can be changed by a user to reflect the spot market length of any region of the world. Users can set custom market rates based on a smart trading algorithm that can be applied to any asset, or use default rates when adding assets to their communities, with the latter conditioned upon the provided [Market Maker](model-market-maker.md) (utility) rate and any applicable feed-in-tariff.
+There are four different types of energy assets a user can currently configure when modelling energy communities on Grid Singularity’s web-based simulation user interface, the [Singularity Map](https://gridsingularity.com/singularity-map){target=_blank} - [solar panels (PVs)](solar-panels.md), [consumption (load) profiles](consumption.md), [batteries (storages)](battery.md) and [heat pumps](heat-pumps-general.md). Each simulated community can consist of at least two participating members (homes representing households, buildings or other community members) and up to 1000 digital agents representing assets and/or homes. Simulation users can model an energy community quickly by adding template homes and assets using the express options, or they can configure the technical details and trading parameters by exploring the advanced options for each asset. Each asset within a community can  [trade energy](trading-agents-and-strategies.md) with other assets, as well as  with the external suppliers via grid network (also termed the grid market). By default, assets shall buy/sell energy locally, interacting with their neighbours, and only in case of any gaps in the local market (either caused by insufficient energy production / consumption in the community, or by inefficient or not affordable trading settings), purchase the energy from the external energy supplier (usually a utility). Trading occurs in [market slots](market-types.md#market-slots), which are by default 15-minute time slots in which energy assets can exchange energy at market rates. The market slot length can be changed by a user to reflect the spot market length of any region of the world. Users can set custom market rates based on a smart trading algorithm that can be applied to any asset, or use default rates when adding assets to their communities, with the latter conditioned upon the provided [Market Maker](model-market-maker.md) (utility) rate and any applicable feed-in-tariff.
diff --git a/wiki/docs/general-settings.md b/wiki/docs/general-settings.md
@@ -41,7 +41,7 @@ Once the modelling is completed, the user goes to the [Results page](results.md)
 
 ## Backend Simulation Configuration
 
-In the backend, the simulation process is slightly different. There is no need to login to set up a simulation. The user first needs to download the code from our Github Repository (Installation Instructions for [Linux](linux-installation-instructions.md), [Mac](ios-installation-instructions.md) and [Windows](vm-installation-instructions.md)). In the setup-file (in Python programming language), general and [trading strategy](trading-agents-and-strategies) settings can be defined. Examples can be found in the relevant [Grid Singularity GitHub](https://github.com/gridsingularity/gsy-e/tree/master/src/gsy_e/setup){target=_blank} folder.
+In the backend, the simulation process is slightly different. There is no need to login to set up a simulation. The user first needs to download the code from our Github Repository (Installation Instructions for [Linux](linux-installation-instructions.md), [Mac](ios-installation-instructions.md) and [Windows](vm-installation-instructions.md)). In the setup-file (in Python programming language), general and [trading strategy](trading-agents-and-strategies.md) settings can be defined. Examples can be found in the relevant [Grid Singularity GitHub](https://github.com/gridsingularity/gsy-e/tree/master/src/gsy_e/setup){target=_blank} folder.
 
 This is the most basic skeleton for a setup-file:
 

diff --git a/wiki/docs/heat-pumps-general.md b/wiki/docs/heat-pumps-general.md
@@ -4,6 +4,6 @@ A heat pump is an energy asset used to heat water and premises by extracting hea
 
 For homes (or other energy community participants) that are connected to district heating we have developed a digital twin of a heat pump that mimics and replaces the heat demand currently satisfied by a district heating network, modelled as a virtual heat pump (VHP) with storage and a related trading strategy. This VHP implementation is [available exclusively in the backend source code](virtual-heat-pump.md), since it will likely be used exclusively by energy researchers to simulate how district heating could be replaced by a heat pump to compare their respective performance. Inversely, the VHP can also be used to calculate the heat demand of homes or other energy community participants, and consequently enable the simulation of a district heating connection that would satisfy this heat demand as opposed to electricity assets.
 
-Finally, for simulations that simply want to account for the district heating connection without considering a potential replacement with heat pumps, the digital twin of the district heating supply for the measured heat demand can be modelled as a "heat market maker", i.e. digital trading agent with a specific [trading strategy](trading-agents-and-strategies) representing the district heating provider, which will only sell heat energy to the heat demand digital twin of the respective community member. The selling price of this market maker will be the district heating price that the heat consumer currently pays, in cents/kWh. The heat demand digital twin, in turn, is modelled as a load with a “consumption profile” defined by the measured heat demand in kWh. Thus, the “heat market maker” will only be used in order to cover the heat demand of the heat load, accounting for the monetary cost of heating.
+Finally, for simulations that simply want to account for the district heating connection without considering a potential replacement with heat pumps, the digital twin of the district heating supply for the measured heat demand can be modelled as a "heat market maker", i.e. digital trading agent with a specific [trading strategy](trading-agents-and-strategies.md) representing the district heating provider, which will only sell heat energy to the heat demand digital twin of the respective community member. The selling price of this market maker will be the district heating price that the heat consumer currently pays, in cents/kWh. The heat demand digital twin, in turn, is modelled as a load with a “consumption profile” defined by the measured heat demand in kWh. Thus, the “heat market maker” will only be used in order to cover the heat demand of the heat load, accounting for the monetary cost of heating.
 
 The heat pump and the virtual heat pump development has been undertaken in the framework of the [HYPERGRYD Project](https://hypergryd.eu/){target=_blank}, funded by the European Union’s H2020 Programme under Grant Agreement No. 101036656.
diff --git a/wiki/docs/model-storage.md b/wiki/docs/model-storage.md
@@ -57,7 +57,7 @@ As an example, considering an `initial_selling_rate` of 30 cents/kWh and a `fina
 
 In general all bids and offers follow the physical constraint of the set `max_abs_battery_power_kW` value. The accumulated energy per market slot cannot exceed this power value times the length of the market slot. Energy sold and bought cancel each other out, meaning that if 2kWh are both sold and bought in the same market slot, the relative power remains 0kW.
 
-For the buying rate increase and selling rate decrease behaviour, please see the [Trading Strategies page](trading-agents-and-strategies).
+For the buying rate increase and selling rate decrease behaviour, please see the [Trading Strategies page](trading-agents-and-strategies.md).
 
 ###Buying Energy in [One-Sided Market](market-types.md#one-sided-pay-as-offer-market):
 

diff --git a/wiki/docs/releases.md b/wiki/docs/releases.md
@@ -74,7 +74,7 @@ The following features were implemented :
 * [Grid fees](grid-fee-accounting.md#constant-grid-fee-calculation) integrated in the Results page - [Energy Pricing](results.md#energy-pricing) graph for each market
 * Total grid fees reported in the Scoreboard page that demonstrates market performance metrics for each collaboration simulation.
 * Net Energy calculation added to Results page - [Energy Trade Profile](results.md#energy-trade-profile) graph in order to calculate the peak energy at a market node in the simulation. The current peak imports and exports were previously calculated based on the cumulative trades, but are now calculated from the net energy consumption, which can be a net import or export.
-* Updated load final selling rate and PV initial buying rate in the [template strategies](trading-agents-and-strategies) now take the total grid fees into account in addition to the market maker (usually utility) rate.
+* Updated load final selling rate and PV initial buying rate in the [template strategies](trading-agents-and-strategies.md) now take the total grid fees into account in addition to the market maker (usually utility) rate.
 * Users can now run three simulations and/or collaborations at once (previous limit was two)
 
 

diff --git a/wiki/docs/setup-configuration.md b/wiki/docs/setup-configuration.md
@@ -1,6 +1,6 @@
 ##Backend Simulation Configuration
 
-In the backend, the simulation process is slightly different compared to the user interface simulations. There is no need to login to set up a simulation. The user first needs to download the code from our Github Repository (Installation Instructions for [Linux](linux-installation-instructions.md), [Mac](ios-installation-instructions.md) and [Windows](vm-installation-instructions.md)). In the setup-file (in Python programming language), general and [trading strategy](trading-agents-and-strategies) settings can be defined. Examples can be found in the relevant [Grid Singularity GitHub](https://github.com/gridsingularity/gsy-e/tree/master/src/gsy_e/setup){target=_blank} folder.
+In the backend, the simulation process is slightly different compared to the user interface simulations. There is no need to login to set up a simulation. The user first needs to download the code from our Github Repository (Installation Instructions for [Linux](linux-installation-instructions.md), [Mac](ios-installation-instructions.md) and [Windows](vm-installation-instructions.md)). In the setup-file (in Python programming language), general and [trading strategy](trading-agents-and-strategies.md) settings can be defined. Examples can be found in the relevant [Grid Singularity GitHub](https://github.com/gridsingularity/gsy-e/tree/master/src/gsy_e/setup){target=_blank} folder.
 
 This is the most basic skeleton for a setup-file:
 

diff --git a/wiki/docs/solar-panels.md b/wiki/docs/solar-panels.md
@@ -32,10 +32,10 @@ In the advanced PV configuration mode, there are settings referring to the Capac
         3. Upload own / custom generation profile in the form of a [csv file](data-requirements.md).
 
 2. Trading Strategy
-    3. Initial selling rate: set the initial (and [consequently the maximum](trading-agents-and-strategies)) rate that the PV offers at the beginning of each market slot in cents/kWh by selecting the [Market Maker](grid-market-settings.md) rate or by entering your own custom rate as ‘user input’
+    3. Initial selling rate: set the initial (and [consequently the maximum](trading-agents-and-strategies.md)) rate that the PV offers at the beginning of each market slot in cents/kWh by selecting the [Market Maker](grid-market-settings.md) rate or by entering your own custom rate as ‘user input’
     4. Final selling rate: set the final rate that the PV offers at the end of each market slot in cents/kWh
     5. Rate decrease: enter a value for the explicit rate decrease increment update interval in cents/kWh
-    6. Linear pricing: If activated, the rate decrease per amount of time (update interval) is calculated automatically in a way that the price decreases linearly over the market slot time. The rate is calculated starting at the Initial selling rate at the start of the market slot and ending at the Final selling rate at the end of the market slot, while updating the rate at each Update Interval: `energy_rate_decrease_per_update = (initial_selling_rate - final_selling_rate) / max(int((slot_length / update_interval) -1), 1)`; note: you can derive the [bidding behavior](trading-agents-and-strategies)  from a linear fitted curve of a selling rate ranging from initial_selling_rate to final_selling_rate within the bidding interval.
+    6. Linear pricing: If activated, the rate decrease per amount of time (update interval) is calculated automatically in a way that the price decreases linearly over the market slot time. The rate is calculated starting at the Initial selling rate at the start of the market slot and ending at the Final selling rate at the end of the market slot, while updating the rate at each Update Interval: `energy_rate_decrease_per_update = (initial_selling_rate - final_selling_rate) / max(int((slot_length / update_interval) -1), 1)`; note: you can derive the [bidding behavior](trading-agents-and-strategies.md)  from a linear fitted curve of a selling rate ranging from initial_selling_rate to final_selling_rate within the bidding interval.
     7. Update interval: set the frequency at which the rate is updated
 
 3. Orientation: If the Local Generation Profile (Custom PV) is selected, the parameters describing the orientation of the solar panels can be set in the basic or advanced mode:
Original file line number	Diff line number	Diff line change
		@@ -1 +1 @@
		There are four different types of energy assets a user can currently configure when modelling energy communities on Grid Singularity’s web-based simulation user interface, the [Singularity Map](https://gridsingularity.com/singularity-map){target=_blank} - [solar panels (PVs)](solar-panels.md), [consumption (load) profiles](consumption.md), [batteries (storages)](battery.md) and [heat pumps](heat-pumps-general.md). Each simulated community can consist of at least two participating members (homes representing households, buildings or other community members) and up to 1000 digital agents representing assets and/or homes. Simulation users can model an energy community quickly by adding template homes and assets using the express options, or they can configure the technical details and trading parameters by exploring the advanced options for each asset. Each asset within a community can [trade energy](trading-agents-and-strategies) with other assets, as well as with the external suppliers via grid network (also termed the grid market). By default, assets shall buy/sell energy locally, interacting with their neighbours, and only in case of any gaps in the local market (either caused by insufficient energy production / consumption in the community, or by inefficient or not affordable trading settings), purchase the energy from the external energy supplier (usually a utility). Trading occurs in [market slots](market-types.md#market-slots), which are by default 15-minute time slots in which energy assets can exchange energy at market rates. The market slot length can be changed by a user to reflect the spot market length of any region of the world. Users can set custom market rates based on a smart trading algorithm that can be applied to any asset, or use default rates when adding assets to their communities, with the latter conditioned upon the provided [Market Maker](model-market-maker.md) (utility) rate and any applicable feed-in-tariff.
		There are four different types of energy assets a user can currently configure when modelling energy communities on Grid Singularity’s web-based simulation user interface, the [Singularity Map](https://gridsingularity.com/singularity-map){target=_blank} - [solar panels (PVs)](solar-panels.md), [consumption (load) profiles](consumption.md), [batteries (storages)](battery.md) and [heat pumps](heat-pumps-general.md). Each simulated community can consist of at least two participating members (homes representing households, buildings or other community members) and up to 1000 digital agents representing assets and/or homes. Simulation users can model an energy community quickly by adding template homes and assets using the express options, or they can configure the technical details and trading parameters by exploring the advanced options for each asset. Each asset within a community can [trade energy](trading-agents-and-strategies.md) with other assets, as well as with the external suppliers via grid network (also termed the grid market). By default, assets shall buy/sell energy locally, interacting with their neighbours, and only in case of any gaps in the local market (either caused by insufficient energy production / consumption in the community, or by inefficient or not affordable trading settings), purchase the energy from the external energy supplier (usually a utility). Trading occurs in [market slots](market-types.md#market-slots), which are by default 15-minute time slots in which energy assets can exchange energy at market rates. The market slot length can be changed by a user to reflect the spot market length of any region of the world. Users can set custom market rates based on a smart trading algorithm that can be applied to any asset, or use default rates when adding assets to their communities, with the latter conditioned upon the provided [Market Maker](model-market-maker.md) (utility) rate and any applicable feed-in-tariff.