Electric Boiler Use Excess Power
Electric Boiler Use Excess Power - Title
Electric Boiler Use Excess Power Test System Model
Electric Boiler Use Excess Power - overview
Test System Model Overview
Author / organization: Benedikt Leitner / AIT
Component Models:
Test Parameters: All parameters according to system configuration
Outputs/Measured Parameters:
- External electric grid:
- Power flows to and from
- Base district heating boiler
- heat generation
- District heating network
- Supply temperatures at substations
- Differential pressures at substations
- Low voltage distribution network
- Voltages at consumer connection points
- Transformer loading
Electric Boiler Use Excess Power - input
Input
Related System Configuration
SmartDorf System Configuration
Related Test Case
Related Use Case
Electric Boiler Use Excess Power - description
Short Description
This test system model is used to verify that self-consumption of renewable energy sources in a coupled heat and power network improved using distributed power-to-heat appliances compared to a base scenario without power-to-heat. This means that energy flows flowing out of the network are reduced. At the same time energy imports should not increase. Relevant effort variables of both networks, i.e., bus voltages, supply temperatures and differential pressures, must stay within the allowable range. Also, the loading of the transformer is not allowed to reach critical levels. Otherwise the test fails.
Electric boilers are used as power-to-heat appliances. They consist of an electric heater, for the conversation of power to heat, and a thermal energy storage, for the (short-term) storage of generated heat. To plan the operation of the storage unit and the electric heater, a model predictive controller is used. The aim of the controller is to minimize negative residual load of the electric network. To enable this planning, negative residual load in the electric as well as heat demand in the heat network need to be known/predicted. This test assumes perfect knowledge of these time-series data and, thus, does not focus on the quality of predictions.
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Electric Boiler Use Excess Power - details
Test System Model Details
| Title of Test | ElectricBoilersUseExcessPower | ||
| Author / Organization | Benedikt Leitner / AIT | ||
| Reference to Test Case | IncreasedRESSelfConsumption | ||
| Test Rationale | This test aims at self-consumption of excess power generated from distributed renewable power generators, such as rooftop photovoltaic generators. The excess power is feed into a district heating network. The local use of excess power helps mitigate problems in the electric distribution network, such as reversed power flows, high loading of equipment and voltage band violations. On the other side, distributed infeed into the district heating network might cause problems due to reversed mass flows, fluctuating supply temperatures or differential pressure problems. Electric boilers are used as power-to-heat appliances. They consist of an electric heater, for the conversation of power to heat, and a thermal energy storage, for the (short-term) storage of generated heat. The test is successfully passed if power flows to the external network are reduced compared to a scenario without power-to-heat. Simultaneously, power import into the network is not allowed to increase by more than 1%. Thus, the electric boilers need to follow the negative residual load curve closely without increasing loading at other times or consuming more than the available excess power. Moreover, relevant network constraints need to be met. |
| Specific Test System | The controller uses heat demand and excess power predictions together with current storage temperatures, electric boiler power consumption and heat discharge to calculate new setpoints for the electric boilers. The district heating network/electric boiler simulation send actual power consumption of electric boilers to electric network simulation.
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| Test and Output Parameters | Test Parameters: All parameters according to system configuration Outputs / Measured Parameters: External electric grid:
Base district heating boiler:
External electric grid:
District heating network:
Low voltage distribution network:
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| Test Design | A dynamic modelling approach was chosen for the district heating network to include time delays and heat dissipation of the piping network, mixing of flows from different pipes, supplies or substations and to account for different controls in the system. A quasi-static approach, based on consecutive power flow calculations, was chosen to study the medium to long-term effects of time-varying loads and generators on the electrical distribution network. Such a quasi-static approach is appropriate to assess the behaviour of the network in timescales of minutes to hours. This assessment comprises the calculation of the active and reactive power flows for all branches and the voltage magnitude and phase for all nodes. A model predictive control approach was chosen to control the electric boilers. This enables a planning of discharging and charging the thermal storage units with regards to excess power availability. E.g., thermal storages can be emptied before times with high excess power but low heat demand and thus makes the use of the electric heater still possible. This test needs to run for an entire year to cover the daily/seasonal variations of loads/generators and the impact of the model predictive control, as it usually has planning horizons of multiple hours/days. |
| Component Models | The following models are of special interest as they represent the coupling points between the heat and power network. They are described in more detail in the following model description forms:
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| Initial System State |
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| Temporal Resolution | District heating and electric boilers:
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| Evolution of System State and Test Signals | Every 15 minutes model predictive controllers receive current heat generation and heat discharge from respective electric boilers together with predicted residual load of electric network and heat demand of district heating network. Thus, electric boilers receive new setpoints for heat generation & heat discharge from model predictive controllers. Every 15 minutes electric network receives current power consumption from electric boilers. Otherwise subsystems are independent from each other. | ||
| Source of Uncertainty Stopping Criteria |
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| Storage of Data | SmILES data format
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