From 69d9d3c59b3f3f3a64fefca48c0136546cb4cd11 Mon Sep 17 00:00:00 2001 From: Shayan Date: Mon, 10 Oct 2022 23:55:56 +1100 Subject: [PATCH] Minor modification before leaving paris --- Decarbonization.py | 2 +- WindSolar.py | 2 +- figures.py | 9 +++++++-- 3 files changed, 9 insertions(+), 4 deletions(-) diff --git a/Decarbonization.py b/Decarbonization.py index 6186a22..595f477 100644 --- a/Decarbonization.py +++ b/Decarbonization.py @@ -40,7 +40,7 @@ daq.Slider( min=0, max=100, - value=50, + value=0, handleLabel={"showCurrentValue": True,"label": "Wind"}, step=5, marks={'0': '100% PV','25': '75% PV', '50': '50-50','75': '75% Wind','100': '100% Wind'}, diff --git a/WindSolar.py b/WindSolar.py index c101c13..5630752 100644 --- a/WindSolar.py +++ b/WindSolar.py @@ -189,7 +189,7 @@ def generate_single_country_drpdwn(): style={"display": "none"}, ), dbc.Row([ - dbc.Col(html.Div(dcc.Graph(id="Pop-and-famil-size",figure=figures.rooftop_PV_plot(0.7,2.5)[0]), style=figure_border_style), md=6), + dbc.Col(html.Div(dcc.Graph(id="Pop-and-famil-size",figure=figures.rooftop_PV_plot(0.3,2.5)[0]), style=figure_border_style), md=6), dbc.Col(html.Div(dcc.Graph(id="number-of-buildings-rooftop",figure=figures.rooftop_PV_plot(0.7,2.5)[1]), style=figure_border_style), md=6), ]), html.Br(), diff --git a/figures.py b/figures.py index 6e413eb..21fcba9 100644 --- a/figures.py +++ b/figures.py @@ -1104,12 +1104,17 @@ def UNstats_plots(year): return [fig,fig2,fig3,fig4,fig5,fig6,fig7,fig8,fig9] def land_use_plot(): + summary_demand_df= pd.DataFrame() final_demand = functions.fetch_all_countries_demand(2019,Unit='GWh',Use='Analysis')[1] non_RE_demand = functions.fetch_all_countries_demand(2019,Unit='GWh',Use='Analysis')[9] countries = functions.fetch_all_countries_demand(2019,Unit='GWh',Use='Analysis')[0] non_RE_demand = non_RE_demand.round(0) final_demand=final_demand.round(0) + summary_demand_df['countries'] = countries + summary_demand_df['non-RE-GWh'] = non_RE_demand + summary_demand_df['final-GWh'] = final_demand + summary_demand_df.to_csv("demand_df_GWh.csv") df_pop = pd.read_csv('Data/Economic Indicators.csv') df = pd.read_excel('Data/Potentials.xlsx') @@ -1654,8 +1659,8 @@ def Solar_physical_resources(): pasture = df.iloc[6, 2:] forested = df.iloc[7, 2:] other = df.iloc[8, 2:] - - Technical_PV_area = (0.1 * pasture/100 + 0.1 * arable/100) * area + percentage_of_available_land = 0.01 + Technical_PV_area = (percentage_of_available_land * pasture/100 + percentage_of_available_land * arable/100) * area Theoretical_PV = PV_pot * area * 0.1 * 1000 * 0.8 #GWh