eelib.core.control.EMS.EMS_model

The eElib EMS model was developed as an energy management system on the building level and is therefore connected to all of the building’s components. The control gathers all of the component’s power flows, calculates the energy balance at the building node and the component’s flexibility, and then sends out power set values in each step. Hereby, available solar power is favored to grid consumption, as well as charging / discharging limits of the charging stations, and batteries are considered.

Regarding charging stations, different charging strategies are implemented: Default / Maximum power charging, balanced charging, solar charging and night charging.

Author: elenia@TUBS

Copyright 2024 elenia

This file is part of eELib, which is free software under the terms of the GNU GPL Version 3.

Module Contents

Classes

HEMS	Models an home energy managament system on building level.
HEMS_default	Default strategy for Energy Management System.
GCP_Aggregator_HEMS	Aggregation of power flows for depiction of uncontrolled devices in a building.
HEMS_forecast_base	Baseclass for EMS strategies using forecasts (and optimizations).
HEMS_forecast_default	Default forecast strategy for Energy Management System.
HEMS_forecast_opt	Optimization-based forecast/schedule strategy for Energy Management System.

class HEMS(ename: str, step_size: int, cs_strategy: str = 'max_p', bss_strategy: str = 'surplus')

Bases: abc.ABC

Models an home energy managament system on building level.

_VALID_PARAMETERS

classmethod get_valid_parameters()

Returns dictionary containing valid parameter types and values.

Returns:

valid parameters for this model

Return type:

dict

add_controlled_entity(entities_dict: dict)

Adds a controlled entity to the corresponding EMS’s lists (controlled components and type-specific).

Parameters:

entities_dict (dict) – Input list with all models of a type (e.g. charging_station) which will be connected to the controller.

_get_component_by_type(type: str)

Gets all controlled components of passed type.

Parameters:

type (str) – Query to determine all controlled components of this type.

Returns:

Returns all entities of queried type.

Return type:

dict

abstract step(time: int)

Handles stepping of energy managament systems by checking power values.

Parameters:

time (int) – Current simulation time

_calc_power_energy(time: int)

Gathers current power flows, aggregates limits, and calculates energy balances.

Parameters:

time (int) – Current simulation time

_set_pv_max()

Calculate pv system setpoints for all devices by using the maximum power.

_set_cs_p()

Calculate charging station setpoints using the chosen charging strategy.

_set_hp_p_th()

Calculate heatpump thermal power setpoints by reducing needed power at this step.

_set_bss_p()

Calculate battery storage system setpoints for all devices using the chosen strategy.

_reset_financial_values()

Reset all financial values (at the beginning of a new timestep).

_handle_incoming_signals()

Retrieve tariff settings for this timestep from an incoming tariff signal.

_calc_financial_output()

Calculate financial values like cost, profit and revenue for this timestep.

class HEMS_default(ename: str, step_size: int = 900, **kwargs)

Bases: HEMS

Default strategy for Energy Management System. Should be copied and adapted for the use of a specific EMS concept.

classmethod get_valid_parameters()

Returns dictionary containing valid parameter types and values.

Returns:

valid parameters for this model

Return type:

dict

step(time: int)

Calculates power set values for each connected component according to the strategy.

Parameters:

time (int) – Current simulation time

class GCP_Aggregator_HEMS(ename: str, step_size: int = 900, **kwargs)

Bases: HEMS

Aggregation of power flows for depiction of uncontrolled devices in a building.

classmethod get_valid_parameters()

Returns dictionary containing valid parameter types and values.

Returns:

valid parameters for this model

Return type:

dict

step(time)

Aggregation of power values.

Parameters:

time (int) – Current simulation time

class HEMS_forecast_base(ename: str, step_size: int, forecast_horizon_hours: int = 24, forecast_frequency_hours: int = 24, forecast_type: str = 'household_only', cs_strategy: str = 'max_p', bss_strategy: str = 'surplus')

Bases: HEMS

Baseclass for EMS strategies using forecasts (and optimizations).

forecast_types

classmethod get_valid_parameters()

Returns dictionary containing valid parameter types and values.

Returns:

valid parameters for this model

Return type:

dict

_request_forecast()

Set models with their attributes and time horizon for forecast request.

_set_schedule_values()

Take schedules of the devices and convert them into set values.

_set_power_in_limits(power: float, p_min: float, p_max: float) → float

Set a power value with regard to a maximum and minimum value, if given.

Parameters:

• power (float) – current power value to start with

• p_min (float) – minimum power limit

• p_max (float) – maximum power limit

Returns:

power value within the limiting bounds

Return type:

float

_set_schedule_values_pv()

Take schedules of pv systems and convert them to set values by using the power limits.

_set_schedule_values_cs()

Take schedules of charging stations and convert to set values by using the limits.

_set_schedule_values_hp()

Take schedules of heatpumps and convert them to set values by using the power limits.

_set_schedule_values_bss()

Take schedules of battery storage systems and convert to set values using the limits.

abstract step(time: int)

Gathers current energy flows and calculates energy balances.

Parameters:

time (int) – Current simulation time

class HEMS_forecast_default(ename: str, step_size: int = 900, **kwargs)

Bases: HEMS_forecast_base

Default forecast strategy for Energy Management System. Should be copied and adapted for the use of a specific EMS concept.

classmethod get_valid_parameters()

Returns dictionary containing valid parameter types and values.

Returns:

valid parameters for this model

Return type:

dict

step(time: int)

Calculates power set values for each connected component according to the strategy.

Parameters:

time (int) – Current simulation time

class HEMS_forecast_opt(ename: str, step_size: int = 900, **kwargs)

Bases: HEMS_forecast_base

Optimization-based forecast/schedule strategy for Energy Management System.

classmethod get_valid_parameters()

Returns dictionary containing valid parameter types and values.

Returns:

valid parameters for this model

Return type:

dict

step(time: int)

Calculates power set values for each connected component according to the strategy.

Parameters:

time (int) – Current simulation time