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
An implementation of "MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing" (ICML 2019).

MixHop and N-GCN ⠀ A PyTorch implementation of "MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing" (ICML 2019)

Benedek Rozemberczki 393 Dec 13, 2022
A framework for annotating 3D meshes using the predictions of a 2D semantic segmentation model.

Semantic Meshes A framework for annotating 3D meshes using the predictions of a 2D semantic segmentation model. Paper If you find this framework usefu

Florian 40 Dec 09, 2022
MVS2D: Efficient Multi-view Stereo via Attention-Driven 2D Convolutions

MVS2D: Efficient Multi-view Stereo via Attention-Driven 2D Convolutions Project Page | Paper If you find our work useful for your research, please con

96 Jan 04, 2023
This is an open-source toolkit for Heterogeneous Graph Neural Network(OpenHGNN) based on DGL [Deep Graph Library] and PyTorch.

This is an open-source toolkit for Heterogeneous Graph Neural Network(OpenHGNN) based on DGL [Deep Graph Library] and PyTorch.

BUPT GAMMA Lab 519 Jan 02, 2023
Unofficial implementation of Fast-SCNN: Fast Semantic Segmentation Network

Fast-SCNN: Fast Semantic Segmentation Network Unofficial implementation of the model architecture of Fast-SCNN. Real-time Semantic Segmentation and mo

Philip Popien 69 Aug 11, 2022
Flower - A Friendly Federated Learning Framework

Flower - A Friendly Federated Learning Framework Flower (flwr) is a framework for building federated learning systems. The design of Flower is based o

Adap 1.8k Jan 01, 2023
Official Implementation of PCT

Official Implementation of PCT Prerequisites python == 3.8.5 Please make sure you have the following libraries installed: numpy torch=1.4.0 torchvisi

32 Nov 21, 2022
BookMyShowPC - Movie Ticket Reservation App made with Tkinter

Book My Show PC What is this? Movie Ticket Reservation App made with Tkinter. Tk

The Nithin Balaji 3 Dec 09, 2022
Match SafeGraph POIs with Data collected through a cultural resource survey in Washington DC.

Match SafeGraph POI data with Cultural Resource Places in Washington DC Match SafeGraph POIs with Data collected through a cultural resource survey in

Changjie Chen 1 Jan 05, 2022
A proof of concept ai-powered Recaptcha v2 solver

Recaptcha Fullauto I've decided to open source my old Recaptcha v2 solver. My latest version will be opened sourced this summer. I am hoping this proj

Nate 60 Dec 20, 2022
HDR Video Reconstruction: A Coarse-to-fine Network and A Real-world Benchmark Dataset (ICCV 2021)

Code for HDR Video Reconstruction HDR Video Reconstruction: A Coarse-to-fine Network and A Real-world Benchmark Dataset (ICCV 2021) Guanying Chen, Cha

Guanying Chen 64 Nov 19, 2022
Neuralnetwork - Basic Multilayer Perceptron Neural Network for deep learning

Neural Network Just a basic Neural Network module Usage Example Importing Module

andreecy 0 Nov 01, 2022
Code for our paper 'Generalized Category Discovery'

Generalized Category Discovery This repo is a placeholder for code for our paper: Generalized Category Discovery Abstract: In this paper, we consider

107 Dec 28, 2022
[NeurIPS 2021] Deceive D: Adaptive Pseudo Augmentation for GAN Training with Limited Data

Deceive D: Adaptive Pseudo Augmentation for GAN Training with Limited Data (NeurIPS 2021) This repository will provide the official PyTorch implementa

Liming Jiang 238 Nov 25, 2022
Oscar and VinVL

Oscar: Object-Semantics Aligned Pre-training for Vision-and-Language Tasks VinVL: Revisiting Visual Representations in Vision-Language Models Updates

Microsoft 938 Dec 26, 2022
MMDetection3D is an open source object detection toolbox based on PyTorch

MMDetection3D is an open source object detection toolbox based on PyTorch, towards the next-generation platform for general 3D detection. It is a part of the OpenMMLab project developed by MMLab.

OpenMMLab 3.2k Jan 05, 2023
Official implementation of "Synthetic Temporal Anomaly Guided End-to-End Video Anomaly Detection" (ICCV Workshops 2021: RSL-CV).

Official PyTorch implementation of "Synthetic Temporal Anomaly Guided End-to-End Video Anomaly Detection" This is the implementation of the paper "Syn

Marcella Astrid 11 Oct 07, 2022
Python script that takes an Impulse response .wav and a input .wav to demonstrate audio convolution.

convolver Python script that takes an Impulse response .wav and a input .wav to demonstrate audio convolution. Created by Sean Higley

Sean Higley 1 Feb 23, 2022
Safe Bayesian Optimization

SafeOpt - Safe Bayesian Optimization This code implements an adapted version of the safe, Bayesian optimization algorithm, SafeOpt [1], [2]. It also p

Felix Berkenkamp 111 Dec 11, 2022
YOLOv5 🚀 is a family of object detection architectures and models pretrained on the COCO dataset

YOLOv5 🚀 is a family of object detection architectures and models pretrained on the COCO dataset, and represents Ultralytics open-source research int

阿才 73 Dec 16, 2022