Data-Driven Time Series Reconstruction for Modern Power Systems Research

10/26/2021
by   Minas Chatzos, et al.
0

A critical aspect of power systems research is the availability of suitable data, access to which is limited by privacy concerns and the sensitive nature of energy infrastructure. This lack of data, in turn, hinders the development of modern research avenues such as machine learning approaches or stochastic formulations. To overcome this challenge, this paper proposes a systematic, data-driven framework for reconstructing high-fidelity time series, using publicly-available grid snapshots and historical data published by transmission system operators. The proposed approach, from geo-spatial data and generation capacity reconstruction, to time series disaggregation, is applied to the French transmission grid. Thereby, synthetic but highly realistic time series data, spanning multiple years with a 5-minute granularity, is generated at the individual component level.

READ FULL TEXT

page 1

page 2

page 3

page 4

page 7

page 8

research
09/30/2019

Generating High-fidelity, Synthetic Time Series Datasets with DoppelGANger

Limited data access is a substantial barrier to data-driven networking r...
research
07/15/2022

FLIP: A Utility Preserving Privacy Mechanism for Time Series

Guaranteeing privacy in released data is an important goal for data-prod...
research
04/01/2022

Synthetic Photovoltaic and Wind Power Forecasting Data

Photovoltaic and wind power forecasts in power systems with a high share...
research
06/01/2022

SolarGAN: Synthetic Annual Solar Irradiance Time Series on Urban Building Facades via Deep Generative Networks

Building Integrated Photovoltaics (BIPV) is a promising technology to de...
research
01/06/2023

A Robust Data-driven Process Modeling Applied to Time-series Stochastic Power Flow

In this paper, we propose a robust data-driven process model whose hyper...
research
07/17/2018

A Data-Driven Approach for Predicting Vegetation-Related Outages in Power Distribution Systems

This paper presents a novel data-driven approach for predicting the numb...
research
06/23/2023

Higher-order Motif-based Time Series Classification for Forced Oscillation Source Location in Power Grids

Time series motifs are used for discovering higher-order structures of t...

Please sign up or login with your details

Forgot password? Click here to reset