How will electric vehicles affect traffic congestion and energy consumption: an integrated modelling approach

Overview

EV-charging-impact

This repository contains the code that has been used for the Queue modelling for the paper "How will electric vehicles affect traffic congestion and energy consumption: an integrated modelling approach" by Artur Grigorev, Tuo Mao, Adam Berry, Joachim Tan, Loki Purushothaman, Adriana-Simona Mihaita. The paper has been published and presented during the IEEE ITSC 2021 conference. The preprint is available: https://arxiv.org/abs/2110.14064 .

You can find a working queue model in "queue_model.py" file.

This EV charging station queue simulation program reads file "Northern_Sydney_EV_charger_list.csv" and outputs queue simulation results into file "q2080_2016_seq.csv". It relies on multiprocessing package to perform parallel simulation.

Input parameters of the model:

  1. Duration of modeling (day, week, month)
  2. Number of plugs on EV stations
  3. Distribution of time intervals between arrivals
  4. Distribution of charging time: normaly distributed between 20% and 80%.
  5. Max queue size
  6. Power supply at EV charger: KW/h

Model output:

  • (O1) Mean queue length of an EV station [n]'] = HOURQUEUE[i]
  • (O2) Mean waiting time in queue at an EV station [hours]
  • (O3) Mean service time to charge at an EV station [hours]
  • (O4) Total time spent overall at an EV station [hours]
  • (O5) Total energy consumption of an EV station [kWh]
  • (O6) Maximum recorded queue length of an EV station [n]
  • (O7) Maximum waiting time in queue at an EV station [hours]
  • (O8) Maximum time spent overall at an EV station [hours]
  • (O9) Maximal energy consumption of an EV station [kW]
  • Consumed electricity by hour [kWh]
  • Total waiting time (minutes) by hour
  • Overall Mean Service time/day'

queue model

To perform calculations for specific OD traffic flow (2016, OD15, OD30) change the line: DICT['StationFlow'] = float(dt[dt.Name==N]['2016 volume']) at the "Setup" section (to 2016, 15 or 30).

The structure of the framework: framework

The code to produce lineplots is in "lineplots.ipynb":

lineplot

lineplot2

The code to produce supplementary animation is in "anim.ipynb": anim

Code and data for "Broaden the Vision: Geo-Diverse Visual Commonsense Reasoning" (EMNLP 2021).

GD-VCR Code for Broaden the Vision: Geo-Diverse Visual Commonsense Reasoning (EMNLP 2021). Research Questions and Aims: How well can a model perform o

Da Yin 24 Oct 13, 2022
Adaptive Pyramid Context Network for Semantic Segmentation (APCNet CVPR'2019)

Adaptive Pyramid Context Network for Semantic Segmentation (APCNet CVPR'2019) Introduction Official implementation of Adaptive Pyramid Context Network

21 Nov 09, 2022
Genetic Programming in Python, with a scikit-learn inspired API

Welcome to gplearn! gplearn implements Genetic Programming in Python, with a scikit-learn inspired and compatible API. While Genetic Programming (GP)

Trevor Stephens 1.3k Jan 03, 2023
Author Disambiguation using Knowledge Graph Embeddings with Literals

Author Name Disambiguation with Knowledge Graph Embeddings using Literals This is the repository for the master thesis project on Knowledge Graph Embe

12 Oct 19, 2022
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
EMNLP 2021 - Frustratingly Simple Pretraining Alternatives to Masked Language Modeling

Frustratingly Simple Pretraining Alternatives to Masked Language Modeling This is the official implementation for "Frustratingly Simple Pretraining Al

Atsuki Yamaguchi 31 Nov 18, 2022
Traditional deepdream with VQGAN+CLIP and optical flow. Ready to use in Google Colab

VQGAN-CLIP-Video cat.mp4 policeman.mp4 schoolboy.mp4 forsenBOG.mp4

23 Oct 26, 2022
Crowd-Kit is a powerful Python library that implements commonly-used aggregation methods for crowdsourced annotation and offers the relevant metrics and datasets

Crowd-Kit: Computational Quality Control for Crowdsourcing Documentation Crowd-Kit is a powerful Python library that implements commonly-used aggregat

Toloka 125 Dec 30, 2022
Canonical Capsules: Unsupervised Capsules in Canonical Pose (NeurIPS 2021)

Canonical Capsules: Unsupervised Capsules in Canonical Pose (NeurIPS 2021) Introduction This is the official repository for the PyTorch implementation

165 Dec 07, 2022
Real Time Object Detection and Classification using Yolo Algorithm.

Real time Object detection & Classification using YOLO algorithm. Real Time Object Detection and Classification using Yolo Algorithm. What is Object D

Ketan Chawla 1 Apr 17, 2022
🔥 Real-time Super Resolution enhancement (4x) with content loss and relativistic adversarial optimization 🔥

🔥 Real-time Super Resolution enhancement (4x) with content loss and relativistic adversarial optimization 🔥

Rishik Mourya 48 Dec 20, 2022
SeqTR: A Simple yet Universal Network for Visual Grounding

SeqTR This is the official implementation of SeqTR: A Simple yet Universal Network for Visual Grounding, which simplifies and unifies the modelling fo

seanZhuh 76 Dec 24, 2022
[TPDS'21] COSCO: Container Orchestration using Co-Simulation and Gradient Based Optimization for Fog Computing Environments

COSCO Framework COSCO is an AI based coupled-simulation and container orchestration framework for integrated Edge, Fog and Cloud Computing Environment

imperial-qore 39 Dec 25, 2022
Official code for "InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization" (ICLR 2020, spotlight)

InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization Authors: Fan-yun Sun, Jordan Hoffm

Fan-Yun Sun 232 Dec 28, 2022
[SIGGRAPH 2021 Asia] DeepVecFont: Synthesizing High-quality Vector Fonts via Dual-modality Learning

DeepVecFont This is the official Pytorch implementation of the paper: Yizhi Wang and Zhouhui Lian. DeepVecFont: Synthesizing High-quality Vector Fonts

Yizhi Wang 146 Dec 18, 2022
Efficient Training of Audio Transformers with Patchout

PaSST: Efficient Training of Audio Transformers with Patchout This is the implementation for Efficient Training of Audio Transformers with Patchout Pa

165 Dec 26, 2022
A simple, unofficial implementation of MAE using pytorch-lightning

Masked Autoencoders in PyTorch A simple, unofficial implementation of MAE (Masked Autoencoders are Scalable Vision Learners) using pytorch-lightning.

Connor Anderson 20 Dec 03, 2022
Delta Conformity Sociopatterns Analysis - Delta Conformity Sociopatterns Analysis

Delta_Conformity_Sociopatterns_Analysis ∆-Conformity is a local homophily measur

2 Jan 09, 2022
Bayes-Newton—A Gaussian process library in JAX, with a unifying view of approximate Bayesian inference as variants of Newton's algorithm.

Bayes-Newton Bayes-Newton is a library for approximate inference in Gaussian processes (GPs) in JAX (with objax), built and actively maintained by Wil

AaltoML 165 Nov 27, 2022
Supporting code for "Autoregressive neural-network wavefunctions for ab initio quantum chemistry".

naqs-for-quantum-chemistry This repository contains the codebase developed for the paper Autoregressive neural-network wavefunctions for ab initio qua

Tom Barrett 24 Dec 23, 2022