# Data types and formats

Pharoes tools use a highly flexible and structured data model that allows users to represent power systems in a consistent and scenario-aware format. This section describes the main data types and structures used when building datasets.

Understanding these data types is key to accurately modeling the behavior of physical assets, their interactions, and the evolution of the system across time and scenarios.

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## 1. Standard Properties

These represent the **core attributes** of objects such as generators, storage units, nodes, or demands. Each property can be assigned using one of several formats depending on its temporal or scenario variability.

### Property Formats:

* **Static**:
A single, constant value assigned to the object across all times and scenarios.
*Example: Maximum capacity = 100 MW*

* **Profile-linked**:
The value is linked to a **time series profile** defined in a separate CSV file. This is useful for representing temporal patterns such as demand, solar irradiance, or wind speed.
*Example: Daily load shape of a demand object over a year.*

* **Variant-based**:
The property changes based on a specific **scenario variant**, allowing you to model alternative futures (e.g., policy cases, high-renewables, high-demand).
*Example: Efficiency = 45% in "BaseCase" and 50% in "GreenScenario".*

* **Date-based**:
The property changes on specific dates within the simulation horizon. This is useful for modeling commissioning, retirements, or staged expansions.
*Example: Capacity increases from 100 MW to 150 MW starting in 2030.*

Each of these formats can be used **independently or in combination**, depending on the modeling needs. For example, a property can be both **variant-dependent and date-sensitive**.

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## 2. Relationships Between Objects

In addition to object properties, the dataset must define the **relationships between objects**. These relationships describe how the elements of the system are connected and interact.

### Common Examples:

* A generator is connected to a specific node.
* A demand object is linked to a region or substation.
* A transmission line connects two nodes in the network.

Each relationship is defined by:

* **Primary Object** (e.g., Generator)
* **Property** (e.g., “connected_to”)
* **Associated Object** (e.g., Node A)

These links ensure that the model correctly maps physical connectivity, operational dependencies, and control structures.

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## 3. Attributes Associated with Relationships

Beyond defining connections, Pharoes allows you to **assign attributes to relationships** themselves. This is useful when a relationship carries a quantitative or qualitative value.

### Examples:

* The **share** of a demand object "Industry" that is allocated to multiple nodes.
*e.g., 60% to "Node North", 40% to "Node East".*