Does Oversizing Improve Prosumer Profitability in a Flexibility Market? - A Sensitivity Analysis using PV-battery System

Overview

Does Oversizing Improve Prosumer Profitability in a Flexibility Market? - A Sensitivity Analysis using PV-battery System

The possibilities to involve small-scale prosumers for ancillary services in the distribution grid through aggregators and local flexibility markets, question whether it is profitable for prosumers to oversize proactively. In this analysis, a Python model is developed to identify the cost optimal operation plan of the PV-battery system and to evaluate the device flexibility. An economic assessment is carried out to derive the cost-benefit of sizing based on the mean electricity price. A sensitivity analysis is performed with the above results to study the profitable sizing of PV-battery systems with flexibility services. The results show promising advantage of oversizing although limitations prevail with the extent of flexibility services offered.

Understanding sizing and flexibility

  1. Use flexgenerator.py to create optimized operation plan with flexibility quantification.
  2. Create a 'var' folder to save the output as pickle files.
  3. Run 'analysis/main.py' to evaluate the impact of system size on prosumer profitability.
  4. Make sure to include all necessary paths to your IDE.

OpenTUMFlex

An open-source python-based flexibility model to quantify and price the flexibility of household devices.

Documentation

Find detailed documentation about OpenTUMFlex here.

Owner
Babu Kumaran Nalini
Researcher in energy optimization
Babu Kumaran Nalini
"Moshpit SGD: Communication-Efficient Decentralized Training on Heterogeneous Unreliable Devices", official implementation

Moshpit SGD: Communication-Efficient Decentralized Training on Heterogeneous Unreliable Devices This repository contains the official PyTorch implemen

Yandex Research 21 Oct 18, 2022
Scene-Text-Detection-and-Recognition (Pytorch)

Scene-Text-Detection-and-Recognition (Pytorch) Competition URL: https://tbrain.t

Gi-Luen Huang 9 Jan 02, 2023
A Sign Language detection project using Mediapipe landmark detection and Tensorflow LSTM's

sign-language-detection A Sign Language detection project using Mediapipe landmark detection and Tensorflow LSTM. The project is built for a vocabular

Hashim 4 Feb 06, 2022
Zero-shot Synthesis with Group-Supervised Learning (ICLR 2021 paper)

GSL - Zero-shot Synthesis with Group-Supervised Learning Figure: Zero-shot synthesis performance of our method with different dataset (iLab-20M, RaFD,

Andy_Ge 62 Dec 21, 2022
An NVDA add-on to split screen reader and audio from other programs to different sound channels

An NVDA add-on to split screen reader and audio from other programs to different sound channels (add-on idea credit: Tony Malykh)

Joseph Lee 7 Dec 25, 2022
This is the source code for generating the ASL-Skeleton3D and ASL-Phono datasets. Check out the README.md for more details.

ASL-Skeleton3D and ASL-Phono Datasets Generator The ASL-Skeleton3D contains a representation based on mapping into the three-dimensional space the coo

Cleison Amorim 5 Nov 20, 2022
Multiple Object Tracking with Yolov5!

Tracking with yolov5 This implementation is for who need to tracking multi-object only with detector. You can easily track mult-object with your well

9 Nov 08, 2022
Monocular Depth Estimation - Weighted-average prediction from multiple pre-trained depth estimation models

merged_depth runs (1) AdaBins, (2) DiverseDepth, (3) MiDaS, (4) SGDepth, and (5) Monodepth2, and calculates a weighted-average per-pixel absolute dept

Pranav 39 Nov 21, 2022
Vision Deep-Learning using Tensorflow, Keras.

Welcome! I am a computer vision deep learning developer working in Korea. This is my blog, and you can see everything I've studied here. https://www.n

kimminjun 6 Dec 14, 2022
MIRACLE (Missing data Imputation Refinement And Causal LEarning)

MIRACLE (Missing data Imputation Refinement And Causal LEarning) Code Author: Trent Kyono This repository contains the code used for the "MIRACLE: Cau

van_der_Schaar \LAB 15 Dec 29, 2022
Vector Quantized Diffusion Model for Text-to-Image Synthesis

Vector Quantized Diffusion Model for Text-to-Image Synthesis Due to company policy, I have to set microsoft/VQ-Diffusion to private for now, so I prov

Shuyang Gu 294 Jan 05, 2023
classify fashion-mnist dataset with pytorch

Fashion-Mnist Classifier with PyTorch Inference 1- clone this repository: git clone https://github.com/Jhamed7/Fashion-Mnist-Classifier.git 2- Instal

1 Jan 14, 2022
Code for EMNLP2020 long paper: BERT-Attack: Adversarial Attack Against BERT Using BERT

BERT-ATTACK Code for our EMNLP2020 long paper: BERT-ATTACK: Adversarial Attack Against BERT Using BERT Dependencies Python 3.7 PyTorch 1.4.0 transform

Linyang Li 142 Jan 04, 2023
Code for training and evaluation of the model from "Language Generation with Recurrent Generative Adversarial Networks without Pre-training"

Language Generation with Recurrent Generative Adversarial Networks without Pre-training Code for training and evaluation of the model from "Language G

Amir Bar 253 Sep 14, 2022
Model Zoo for AI Model Efficiency Toolkit

We provide a collection of popular neural network models and compare their floating point and quantized performance.

Qualcomm Innovation Center 137 Jan 03, 2023
A modular, research-friendly framework for high-performance and inference of sequence models at many scales

T5X T5X is a modular, composable, research-friendly framework for high-performance, configurable, self-service training, evaluation, and inference of

Google Research 1.1k Jan 08, 2023
A stock generator that assess a list of stocks and returns the best stocks for investing and money allocations based on users choices of volatility, duration and number of stocks

Stock-Generator Please visit "Stock Generator.ipynb" for a clearer view and "Stock Generator.py" for scripts. The stock generator is designed to allow

jmengnyay 1 Aug 02, 2022
This is the research repository for Vid2Doppler: Synthesizing Doppler Radar Data from Videos for Training Privacy-Preserving Activity Recognition.

Vid2Doppler: Synthesizing Doppler Radar Data from Videos for Training Privacy-Preserving Activity Recognition This is the research repository for Vid2

Future Interfaces Group (CMU) 26 Dec 24, 2022
This is official implementaion of paper "Token Shift Transformer for Video Classification".

This is official implementaion of paper "Token Shift Transformer for Video Classification". We achieve SOTA performance 80.40% on Kinetics-400 val. Paper link

VideoNet 60 Dec 30, 2022