Explanipedia

Solar Data Tools: a Python library for automated analysis of unlabeled PV data Open

Sara Miskovich, Bennet Meyers, Elpiniki Apostolaki-Iosifidou, Claire Berschauer, Chengcheng Ding , et al. · 2025

ANOMALY DETECTION in photovoltaic fleet data via INTERPRETABLE MACHINE LEARNING Open

Bennet Meyers · 2025

GOAL: use neighboring systems to detect partial outages

Interpretable Net Load Forecasting Using Smooth Multiperiodic Features Open

Mehmet Giray Ogut, Bennet Meyers, Kirsten Perry, Stephen Boyd · 2025

Automatic loss factor modeling and attribution on unlabeled PV energy data [Slides] Open

Bennet Meyers, Michael G. Deceglie · 2024

Solar Data ToolsVersion 1 release, features, applications, and future work Open

Bennet Meyers · 2024

Agenda\n1. Introduction to Solar Data Tools\n2. Brief overview of signal decomposition\n3. New SDT features available as of version 1.3.2\n4. New methods for executing SDT: Dask and Marimo

Interpretable Net Load Forecasting Using Smooth Multiperiodic Features Open

Mehmet Öğüt, Bennet Meyers, Stephen Boyd · 2024

We consider the problem of forecasting net load over a horizon such as one day,\nusing a trailing window of past net load values as well as date and time. We focus\non three variations on this problem: point forecasts, marginal quantile fo…

Time Dilated Bundt Cake Analysis of PV Output [Poster] Open

Mehmet Öğüt, Bennet Meyers, Aramis Dufour, Stephen Boyd · 2024

We present a novel method for modeling time-dependent statistics in the power signal generated by a photovoltaic (PV) system. Our white-box machine learning method is interpretable and auditable, based on principles of multiperiodic basis …

Survey of Time Shift Detection Algorithms for Measured PV Data Open

Kirsten Perry, Bennet Meyers, Matthew Muller · 2023

In this research, three variations of time shift detection algorithms were tested for their ability to detect time shift issues (including daylight savings time and random time shifts) in measured PV data sets. Two algorithms from the Pyth…

Perspective: Performance Loss Rate in Photovoltaic Systems Open

Michael G. Deceglie, Kevin Anderson, Daniel Fregosi, William B. Hobbs, Mark A. Mikofski , et al. · 2023

Photovoltaic systems may underperform expectations for several reasons, including inaccurate initial estimates, suboptimal operations and maintenance, or component degradation. Accurate assessment of these loss factors aids in addressing r…

PV Fleet Modeling via Smooth Periodic Gaussian Copula Open

Mehmet G. Ogut, Bennet Meyers, Stephen Boyd · 2023

We present a method for jointly modeling power generation from a fleet of photovoltaic (PV) systems. We propose a white-box method that finds a function that invertibly maps vector time-series data to independent and identically distribute…

Determining circuit model parameters from operation data for PV system degradation analysis: PVPRO Open

Baojie Li, Todd Karin, Bennet Meyers, Xin Chen, Dirk Jordan , et al. · 2023

Physics-based circuit parameters like series and shunt resistance are essential to provide insights into the degradation status of photovoltaic (PV) arrays. However, calculating these parameters typically requires a full current–voltage ch…

Signal Decomposition Using Masked Proximal Operators Open

Bennet Meyers, Stephen Boyd · 2023

Estimation of Shade Losses in Unlabeled PV Data Open

Bennet Meyers, David Jose Florez Rodriguez · 2022

We provide a methodology for estimating the losses due to shade in power generation data sets produced by real-world photovoltaic (PV) systems. We focus this work on estimating shade loss from data that are unlabeled, i.e. power measuremen…

Estimation of Soiling Losses in Unlabeled PV Data Open

Bennet Meyers · 2022

We provide a methodology for estimating the losses due to soiling for photovoltaic (PV) systems. We focus this work on estimating the losses from historical power production data that are unlabeled, i.e. power measurements with time stamps…

slacgismo/StatisticalClearSky: Refined CI/CD + badges Open

Bennet Meyers, Tadatoshi Takahashi · 2022

What's Changed Update status badge by @Thistleman in https://github.com/slacgismo/StatisticalClearSky/pull/42 Updates/remove review by @Thistleman in https://github.com/slacgismo/StatisticalClearSky/pull/43 Full Changelog:…

Signal Decomposition Using Masked Proximal Operators Open

Bennet Meyers, Stephen Boyd · 2022

We consider the well-studied problem of decomposing a vector time series signal into components with different characteristics, such as smooth, periodic, nonnegative, or sparse. We describe a simple and general framework in which the compo…

slacgismo/pv-system-profiler: v0.1.4 - tilt_azimuth initialized Open

Bennet Meyers, Elpiniki Apostolaki-Iosifidou, Derin Serbetcioglu · 2021

Estimating PV array location and orientation from real-world power datasets.

PVInsight (Final Technical Report) Open

Bennet Meyers · 2021

Data generated from real-world photovoltaic (PV) systems represent significant opportunities for the industry–from digital operations and maintenance to real-time planning and forecasting. However, these data also come with substantial, un…

International collaboration framework for the calculation of performance loss rates: Data quality, benchmarks, and trends (towards a uniform methodology) Open

Sascha Lindig, David Moser, Alan J. Curran, Kunal Rath, Arash Khalilnejad , et al. · 2021

The IEA PVPS Task 13 group, experts who focus on photovoltaic performance, operation, and reliability from several leading R&D centers, universities, and industrial companies, is developing a framework for the calculation of performance lo…

Reliability and Power Degradation Rates of PERC Modules Using Differentiated Packaging Strategies and Characterization Tools Open

Roger H. French, Bryan D. Huey, Alexandra Longacre, Michael Martin, Thomas Moran , et al. · 2021

The reliability, durability and lifetime performance of passivated emitter, rear cell (PERC) modules used in real-world PV power plants is a critical challenge underlying the rapid adoption and bankability of these PERC cells, whose high e…

solar-data-tools Open

Bennet Meyers, Duncan Ragsdale, Derin Serbetcioglu, Jonathan Goncalves, Elpiniki Apostolaki-Iosifidou , et al. · 2021

Tools for performing common tasks on solar PV data signals. These tasks include finding clear days in a data set, common data transforms, and fixing time stamp issues. These tools are designed to be automatic and require little if any inpu…

solar-fingerprinting Open

Bennet Meyers · 2020

An algorithm for creating a low-dimensional representation (fingerprint) of daily photovoltaic solar power generation signals.

Signal Processing on PV Time-Series Data: Robust Degradation Analysis Without Physical Models Open

Bennet Meyers, Michael G. Deceglie, Chris Deline, Dirk Jordan · 2019

A novel unsupervised machine learning approach for analyzing time-series data is applied to the topic of photovoltaic (PV) system degradation rate estimation, sometimes referred to as energy-yield degradation analysis. This approach only r…

Statistical Clear Sky Fitting Algorithm Open

Bennet Meyers, Michaelangelo D. Tabone, Emre Can Kara · 2019

We present an algorithm that estimates a clear sky performance signal from the measured power of a PV system. The algorithm uses only observed power output, and assumes no knowledge of weather, irradiance data, or system configuration meta…

slacgismo/scsf-cluster-deploy Open

Bennet Meyers · 2018

Code for running SCSF on an AWS cluster.

Accurate Modeling Of Partially Shaded Pv Arrays Open

Bennet Meyers, Mark A. Mikofski · 2017

Partial shading is the condition of nearby objects casting shade onto part of a photovoltaic (PV) array, causing the PV modules to receive non-uniform irradiance. Non-uniform shading causes electrical mismatch between elements within the a…

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