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.

You might also like...
Implementation of EMNLP 2017 Paper
Implementation of EMNLP 2017 Paper "Natural Language Does Not Emerge 'Naturally' in Multi-Agent Dialog" using PyTorch and ParlAI

Language Emergence in Multi Agent Dialog Code for the Paper Natural Language Does Not Emerge 'Naturally' in Multi-Agent Dialog Satwik Kottur, José M.

Technical experimentations to beat the stock market using deep learning :chart_with_upwards_trend:

DeepStock Technical experimentations to beat the stock market using deep learning. Experimentations Deep Learning Stock Prediction with Daily News Hea

This project provides a stock market environment using OpenGym with Deep Q-learning and Policy Gradient.
This project provides a stock market environment using OpenGym with Deep Q-learning and Policy Gradient.

Stock Trading Market OpenAI Gym Environment with Deep Reinforcement Learning using Keras Overview This project provides a general environment for stoc

Warning: This project does not have any current developer. See bellow.

Pylearn2: A machine learning research library Warning : This project does not have any current developer. We will continue to review pull requests and

code for paper
code for paper "Does Unsupervised Architecture Representation Learning Help Neural Architecture Search?"

Does Unsupervised Architecture Representation Learning Help Neural Architecture Search? Code for paper: Does Unsupervised Architecture Representation

 When Does Pretraining Help? Assessing Self-Supervised Learning for Law and the CaseHOLD Dataset of 53,000+ Legal Holdings
When Does Pretraining Help? Assessing Self-Supervised Learning for Law and the CaseHOLD Dataset of 53,000+ Legal Holdings

When Does Pretraining Help? Assessing Self-Supervised Learning for Law and the CaseHOLD Dataset of 53,000+ Legal Holdings This is the repository for t

Does Pretraining for Summarization Reuqire Knowledge Transfer?

Pretraining summarization models using a corpus of nonsense

Does MAML Only Work via Feature Re-use? A Data Set Centric Perspective

Does-MAML-Only-Work-via-Feature-Re-use-A-Data-Set-Centric-Perspective Does MAML Only Work via Feature Re-use? A Data Set Centric Perspective Installin

A human-readable PyTorch implementation of "Self-attention Does Not Need O(n^2) Memory"

memory_efficient_attention.pytorch A human-readable PyTorch implementation of "Self-attention Does Not Need O(n^2) Memory" (Rabe&Staats'21). def effic

Owner
Babu Kumaran Nalini
Researcher in energy optimization
Babu Kumaran Nalini
A Neural Net Training Interface on TensorFlow, with focus on speed + flexibility

Tensorpack is a neural network training interface based on TensorFlow. Features: It's Yet Another TF high-level API, with speed, and flexibility built

Tensorpack 6.2k Jan 1, 2023
Flax is a neural network ecosystem for JAX that is designed for flexibility.

Flax: A neural network library and ecosystem for JAX designed for flexibility Overview | Quick install | What does Flax look like? | Documentation See

Google 3.9k Jan 2, 2023
A Neural Net Training Interface on TensorFlow, with focus on speed + flexibility

Tensorpack is a neural network training interface based on TensorFlow. Features: It's Yet Another TF high-level API, with speed, and flexibility built

Tensorpack 6.2k Jan 9, 2023
Technical Indicators implemented in Python only using Numpy-Pandas as Magic - Very Very Fast! Very tiny! Stock Market Financial Technical Analysis Python library . Quant Trading automation or cryptocoin exchange

MyTT Technical Indicators implemented in Python only using Numpy-Pandas as Magic - Very Very Fast! to Stock Market Financial Technical Analysis Python

dev 34 Dec 27, 2022
E-Ink Magic Calendar that automatically syncs to Google Calendar and runs off a battery powered Raspberry Pi Zero

MagInkCal This repo contains the code needed to drive an E-Ink Magic Calendar that uses a battery powered (PiSugar2) Raspberry Pi Zero WH to retrieve

null 2.8k Dec 28, 2022
A lightweight Python-based 3D network multi-agent simulator. Uses a cell-based congestion model. Calculates risk, loudness and battery capacities of the agents. Suitable for 3D network optimization tasks.

AMAZ3DSim AMAZ3DSim is a lightweight python-based 3D network multi-agent simulator. It uses a cell-based congestion model. It calculates risk, battery

Daniel Hirsch 13 Nov 4, 2022
Matlab Python Heuristic Battery Opt - SMOP conversion and manual conversion

SMOP is Small Matlab and Octave to Python compiler. SMOP translates matlab to py

Tom Xu 1 Jan 12, 2022
Dynamic vae - Dynamic VAE algorithm is used for anomaly detection of battery data

Dynamic VAE frame Automatic feature extraction can be achieved by probability di

null 10 Oct 7, 2022
Use graph-based analysis to re-classify stocks and to improve Markowitz portfolio optimization

Dynamic Stock Industrial Classification Use graph-based analysis to re-classify stocks and experiment different re-classification methodologies to imp

Sheng Yang 10 Dec 5, 2022
Implementation of EMNLP 2017 Paper "Natural Language Does Not Emerge 'Naturally' in Multi-Agent Dialog" using PyTorch and ParlAI

Language Emergence in Multi Agent Dialog Code for the Paper Natural Language Does Not Emerge 'Naturally' in Multi-Agent Dialog Satwik Kottur, José M.

Karan Desai 105 Nov 25, 2022