Centralised coordination of EVs charging and PV active power curtailment over multiple aggregators in low voltage networks
Description
This directory contains the following datasets: SOURCE CODE Four scripts in Python are included to obtain the parameters of the whole network and test the proposed optimisation approaches. SENSITIVITY MATRICES, INITIAL VOLTAGES AND LOADING LEVELS OF THE LOW-VOLTAGE FEEDERS Voltage sensitivity matrices are obtained according to the description in Section 4.2, which is implemented in the file "Get_Sensitivity_Coeff_PowerFactory_Aggregator.py" Voltage and loading time series were obtained using the above file for a test period of 30 hours with a 10-minute interval (i.e., 180 slots of time) per phase for every household node using the unbalanced quasi-dynamic power flow (QDPF) POWER/ENERGY BOUNDARIES OF EVs The proposed model in Sections 2.3 to 2.5 is computed through the file "EV_Energy_Power_Bounds_from_Zero.py" It is also included the LV network in PowerFactory V2016 with a series of EVs and PVs. Although these devices have a time-series profile assigned, these are not used for optimisation. However, these can be changed by the profiles derived from the second optimisation strategy to perform further analysis in PowerFactory.
Files
Steps to reproduce
1. The network must be imported in PowerFactory (V2016 or later) and located in a folder named "LV UK networks". Add or remove the desired number of EVs and PVs in the network in PowerFactory in order to evaluate a particular penetration level. 2. Python files must be in the same folder. In the file "EV_Energy_Power_Bounds_from_Zero.py", you can change the EV parameters, as well as the sample period "ts" and the length of the simulation through the variable "days". This file will return the energy boundaries and time availability of all EVs, along with other required parameters. 3. "Get_Sensitivity_Coeff_PowerFactory_Aggregator.py" compute the sensitivity matrices, the initial voltage and loading levels of the network, and other input parameters for the EVs and PVs. Modify the variable "exportSel" to 1 if you want to export the data to a particular folder, which has to be previously defined. 4. There are two main files for each optimisation strategy: "LP_EVandPV__Single_Objevtive_Aggregators QP.py" and "LP_EVandPV__Single_Objevtive_Aggregators_Network_Constraints.py". These must be individually executed to call the above-described files. Modify the variable "exrporRes" to 1 if you want to export the data to a particular folder, which has to be previously defined. Note: For reading the load profiles, you must define the path for the file "Load_Profiles_Concatenated.txt" in each "ChaTime" object.