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Privacy-Preserving Feasibility Assessment method for Voltage Limits-Based on Closed-form Power Flow Approximation

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privacy_preserving_feasibility_assesment

This file contain the code related to the paper:

Parikshit Pareek, Anshuman Singh, L.P. Mohasha Isuru Sampath, H. B. Gooi and Hung D Nguyen, "Privacy-Preserving Feasibility Assessment for P2P Energy Trading and Storage Integration" Accepted for 2022 PESGM", Preprint

Cite As:

@article{pareek2022privacy,
  title={Privacy-Preserving Feasibility Assessment for P2P Energy Trading and Storage Integration,
  author={Pareek, Parikshit and Singh, Anshuman and Sampath, LP Mohasha Isuru and Gooi, HB and Nguyen, Hung D},
 booktitle={2022 IEEE Power Engineering Society General Meeting--Accepted},
  pages={1--5},
  year={2022},
  organization={IEEE}
}

In perticular, the code generates figure 2 of the manusript and provides the all the results in cell array R.

Details of Files:

  • CFPF_QD_Kernel_DER_bus.m : Function obtaining the CFPF Approximation using Quadratic Kernel.
  • input_dataset_Load.m : Creating load data set for training and testing
  • MCS_output.m : Monte-Carlo Simulation to obtain testing data points
  • rand_sample_x.m : Generating random samples
  • runpf_complete.m : MATPOWER codes combined together to avid downloading
  • Sampling_Jaco.m : Cover to 'runpf' for obtaining power flow datasets
  • main_final.m : Main file to run

Results:

  • R{1, hr_idx}.f : Index of probabilisitically feasible injections of battery at the bus_ESSnode
  • R{1, hr_idx}.Xb_f Nx2 double : Probabilisitically feasible injections of battery at the bus_ESSnode (N is feasible points)
  • R{1, hr_idx}.s_limits : Dx2 double : Minimum and Maximum injection limits at that hour at each node P and Q (D = #Loadbus x 2)
  • R{1, hr_idx}.ind_cap: Indvidual PV injection (max)
  • R{1, hr_idx}.XPb : The physical battery space of real power (grid for min and max possible P)
  • R{1, hr_idx}.XQb : The physical battery space of reactive power (grid for min and max possible Q)

Dependencies:

GAUSSIAN PROCESS REGRESSION AND CLASSIFICATION Toolbox version 4.2 for GNU Octave 3.2.x and Matlab 7.x and higher. Copyright (c) by Carl Edward Rasmussen and Hannes Nickisch, 2018-06-11. Link

  • Newer GPML toolbox might require matching hyperparameter initialization. To avoid such issues, I have uploaded the GPML Toolbox version here.

  • Look here for more details about Closed-form Power Flow (CFPF).
  • Other variable names are self-explaintory
  • All the codes are tested on MATLAB R2020b

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Privacy-Preserving Feasibility Assessment method for Voltage Limits-Based on Closed-form Power Flow Approximation

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