Title of Test

KIT.TC2.TS1 (Electrical Peak Shaving BESS Sizing)

Author / Organization

Zhichao Wu / KIT

Reference to Test Case

Test Rationale

The test aims at shaving electrical peaks in the FlexOffice/SmartFab system. This means that the electrical peak power delivered by the grid should be minimized. The grid and PV panels (renewable energy source) supply electricity for the system. When excess power is available from PV, and the battery is not full at this time, the surplus electricity is stored in the battery. If there is still remaining power, the redundant electricity is fed into the grid. The renewable energy is supposed to be utilized as much as possible.
Typically, the electrical load includes the production machines in the smart factory, the electric devices and the heat pump in the office. The heat pump acts as power-to-heat component, which uses electricity to heat up the room to keep the temperature in the office comfortable when necessary.
This test should be run repetitively in order to find the optimal battery capacity size that minimizes the object function. The simulation is executed for one week in four different seasons to cover the seasonal variation in temperature and solar irradiation.

Specific Test System

An overview of the test system configuration is shown in Figure F.2. The test system consists of:

• Electric grid, which is considered as an external infinite energy source and sink. We only concern the power imported and exported and record it as simulation output.
• Internal electricity supplier: PV.
• Internal electricity consumers: factory and office (includes heat pump and electricity user). The electric load from factory, office consumers and electric heat pump are sum up together with PV generation as residual load.
• Batteries provide power bi-directionally, acting as sink and source.

The controller uses electric demand, renewable generation power and current battery state of charge to calculate the power set-point for the battery. The control function is described in KIT_ControlFunction_Electrical_Testcase (see deliverable D5.1).

Test and Output Parameters

Test Parameters:

Time-series input:

• Solar radiation: Ee
• Factory electrical load: P_load_prod
• Office electrical load: P_load_office
• Thermal disturbance: disturbanceZ
• control signal of the electric heat pump: b_Ctrl-HP

Solar radiation is given as measured irradiance flux density to calculate the PV power generation.
Factory electric load is given as power flow vector, derived from the machines in the smart factory.
Office electric load is the power consumption in the office building.
Thermal disturbance is the input data of the building model. The disturbance includes external environment (outside temperature, radiation on the building) and internal thermal gain (occupancy and electric devices).
The input data of the electric heat pump is the binary signal b_Ctrl-HP, which is provided by the controller during the simulation. Thus, the input signal b_Ctrl-HP is not given in the dataset.
All input data are time series described in the SmILES data format (see deliverable D5.1).

Outputs / Measured Parameters:

Electrical grid

• Power imported from/exported to the grid
• Total electricity energy required from the grid
• Peak electrical power caused by the process

Battery

• State of charge

Test Design

1. Set up models required for the simulation. The battery is using an equivalent circuit model, estimating the state of charge with coulomb counting method. The relationship between the state of charge and the open-circuit-voltage of the battery is simplified as lookup table (see deliverable D4.1, Appendix E.1, page 85). The thermal characteristic of the office building is modelled as state space equation (see deliverable D4.1, Appendix D.1, page 77).
2. Run the simulation with calculated PV generation and electrical load data. The controller gets the input power demand from factory and office, and the supply from PV. The charging and discharging of the battery is controlled based on the load and state of the battery to keep the battery under proper working condition and calculate the power required from the external grid.
3. Each run of the simulation represents a week in a different season. Four weeks are selected to cover the seasonal variation in temperature and solar irradiation.
4. Vary the battery size from 0 to the upper limit and repeat step 2 & step 3. The upper battery size is limited by the maximum daily renewable generation. The optimal battery capacity can be derived from the minimum costs calculated by means of the objective function.

Component Models

• Battery
• PV
• Factory: Electrical consumers
• Office: Electrical Consumption
• Controller
• Heat Pump

Initial System State

• Batteries are empty (SOC=0)
• All initial temperatures in the building are 21°C.

Temporal Resolution

Evolution of System State and Test Signals

Source of Uncertainty

Stopping Criteria

-

Invalid battery state of charge calculation.

Storage of Data