As sustainability is concerned, the goal here
is to study how to lower the overall
emission of greenhouse gases for the electricity grid and to encourage growth
of cleaner, renewable energy resources in Colorado. So, I looked for related
data on Colorado State Energy Profile and also in the U

As sustainability is concerned, the goal here is to study how to lower the overall emission of greenhouse gases for the electricity grid and to encourage growth of cleaner, renewable energy resources in Colorado. So, I looked for related data on Colorado State Energy Profile and also in the U.S. Energy Information Administration Portal and trying, still to model the overall Colorado pollution from the natural gas, coal and renewable energies such as solar and wind.

The current electricity portfolio of Colorado is still heavily reliant on high-emission sources of fossil fuel (i.e. Coal). In 2020, coal still generated the most electricity, followed by natural gas and renewable energy.

Colorado GHG emissions in 2015 were dominated by electricity generation, transportation, building energy use (especially space heating and water heating) and the oil and gas sector. Electricity generation emissions are predominantly attributed to coal combustion with a small portion from natural gas generators.

While Colorado has a range of energy options at its disposal and could make choices that grow renewables (e.g. solar and wind) while encouraging the production of less carbon-intensive fossil fuels (e.g. natural gas).

For example, Xcel Energy has set goals of increasing its use of renewable energy sources to 55% of its mix by 2026, reducing carbon emissions by 80% by 2030 across its eight-state territory and getting to zero emissions of the greenhouse gas by 2050.

 Some assumptions

Over the past decade, Colorado is becoming a major natural gas consumer; the electricity portfolio has been gradually changing. However, around 30% of electricity is still generated from burning coal, but a lot have been done for electricity is from renewables.

Colorado is betting better in adopting solar and wind energy, however generally speaking the state is still falling behind in renewable energy.

In 2019, renewable energy sources accounted for about 11% of total U.S. energy consumption and about 17% of electricity generation.

In FY 2019-20, the state budget totals about $32.5 billion. Of the $32.5 billion, $12.2 billion is from the General Fund, which supports basic state-funded services, such as K-12 education, prisons, courts, and public assistance. Most of the General Fund revenue comes from income and sales taxes.

Modeling

The two main goals are to lower the overall emission of greenhouse gases for the electricity grid and to encourage growth of cleaner, renewable energy resources.

 As boundaries to the problem, I used 35 years as our time frame and limited the model to the State of Colorado as the spatial extent.

The objectives of modeling include maximizing the economic benefits of exploring unconventional oil and natural gas resources, diversifying the energy portfolio of Colorado, encouraging the production and exportation of unconventional hydrocarbon resources, and reallocating the added revenue to the transition to renewables, like wind and solar.

 

 

 To provide a brief overview of the description of this model, here is a table of contents of sorts:  - The Program - Overview  - The Model Itself - Macro Scale  - Principal Inputs  - Principal Outputs  - Inputs & Outputs - Brief Explanation  - The Details - How This All Works  - Viewing Data Ou
To provide a brief overview of the description of this model, here is a table of contents of sorts:
- The Program - Overview
- The Model Itself - Macro Scale
- Principal Inputs
- Principal Outputs
- Inputs & Outputs - Brief Explanation
- The Details - How This All Works
- Viewing Data Outputs


The Program - Overview:

The model as seen revolves around the main variable components featuring "program" in their name and identified by their green color. The individual household starts at the "Building Envelope" program, which involves changes and modifications made to the actual building envelope of the house to make it more energy efficient, such as modifications to the insulation, windows, doors, etc. Then, the individual household will begin to progress through the behavioral component of the energy reduction program, starting with Climate Control. This portion concerns thermostat set points, the use of windows and fans to modulate temperature, and a behavioral adjustment in how to tolerate different levels of hot/cold temperature in the household. From here, the household moves through each room in the house, implementing energy reduction practices as appropriate. Because this program is designed to be modular and applicable to wide varieties of homes across the country, these rooms have been broken up into some standard categories that should apply to most households. These categories include the kitchen, the washroom, the main room/living room/"den", any bathrooms, and any bedrooms. Each category has its own set of energy reduction practices that can all be applied from a behavioral standpoint; clicking on each individual "program" will show a brief description of what these practices are in the notes section. Once the individual household has progressed through all of these areas, making the appropriate adjustments in each, they have more or less effectively "completed" the program. In reality, areas may continue to pop up where adjustments can be made to reduce energy consumption, so even though the program has been "completed" the members of the household will be continually working to maintain the new efficiency standard they have achieved with the end goal of cultivating a permanent, sustainable lifestyle. 


The Model Itself - Macro Scale:

The above is all essentially a description of how the household energy reduction program operates; the model is obviously tied to this, however it also includes an energy component that takes into account energy savings not only from a single house but all houses in a single community. How this all works will be discussed more in detail below, but first some basics will be gone over.

Principal inputs:

- energy capable of being saved in each portion of the program through behavioral changes (e.g. total possible energy reductions compared with initial baseline use prior to starting the program are X kWh/year and Y CCF/year)
- % of progress that needs to be made on meeting the reduction goal prior to moving onto the next program (e.g. for a total possible energy reduction of X compared to the initial energy use prior to starting the program, the participant must have reduced 90% of that total energy prior to moving on to the next program)
- time each program is projected to take (e.g. 4 weeks, 5 weeks, etc.)
- households in the community
- time (i.e. how long to run the model for, e.g. 52 weeks, 104 weeks, etc.)

Principal Outputs:

- amount of kWh of electricity saved by a household over the given period of time since starting the program (based on a kWh/yr basis)
- amount of CCF of gas saved by a household over the given period of time since starting the program (based on a CCF/yr basis)
- amount of gas and amount of electricity saved by the community the given period of time since starting the program (based on a per year basis)
- a plot of the progress made on each program for a specific period of time (e.g. which program is the household in, and what is their progress on the rest of the program they have already completed)

Inputs & Outputs - Brief Explanation:

For this model, the only inputs that could vary significantly from community to community are the specific number of households as well as the time the program has been in operation. Obviously the power that each household is capable of reducing can vary from household to household, however we are mainly concerned with the average energy reduction when looking at the community scale as there will always be outliers, which is why average numbers are used. Of the outputs produced, the kWh and CCF savings can be translated to lbs of CO2 saved, as well as other useful energy savings metrics that can better explain the impact of CE4A to the normal person than trying to explain the details behind what 1 kilo-watt hour is. Additionally, for a specific area's utility rate, the number of kWh/CCF saved overtime can yield data about how much money the specific household has saved since starting the program. This last statistic would be more helpful if the program were operating by strictly giving all the savings from energy reduction back to the homeowner; as this isn't exactly how CE4A handles this component, the model would have to be modified to more accurately depict the total savings going back to the homeowner/company revenue based on energy savings over time.


The Details - How This All Works:

Program Progression per Program:
The progress of the individual household through the home energy reduction program is essentially dictated by the progress through each individual program within. Progress through these individual programs is dictated by an inverse tangent curve that models behavioral change. The curve essentially outputs the % of progress the individual household has made, going from a value of 0 to 100. 
- Why an inverse tangent curve? - the shape of the curve includes an initial portion in which changes made are significantly large, followed by a portion in which the rate of change decreases as the easily made changes are completed over time. Compared with curves of similar shape, the important part about the inverse tangent curve is that it has a horizontal asymptote that the curve will only get close to, but never actually reach over time. This is representative of the concept that individuals will always have to work to maintain energy reduction practices until they become habit, as well as the reality that new challenges in the field of energy reduction can and will arise over time as people and technology changes.
***
Important to note: the inverse tangent function has been written to operate on a basis of weeks and % (in terms of a whole number XX.YY, not 0.XXYY). If the time scale is to be adjusted, say from weeks to months, then the entire tangent function must be rewritten to reflect this. Additionally, the function outputs values going from 0 to 100. This is a key reason why the function would need to be rewritten, as this would be drastically changed if different time units were used.
***
Inputs for each program include the progress % that the household needs to reach to advance on to the next program, as well as the time (in weeks) it should take them to reach this % threshold. Given the above explanation for how the inverse tangent curve works, the % progress and time threshold values should be chosen based on how much change is realistically possible within that time range (e.g. if it is realistic for an individual to complete 95% of possible changes within a 3 week period and form the habits to maintain those changes, then those values are well-suited for that program. However, if some programs have components that will take a long time to adapt to, then a longer period of time should be picked or a lower progress threshold, ideally the former.

Program Progression from Program to Program:
Each program following the first includes if-then statements related to the progress threshold of the previous program; once that program reaches that threshold, then the code the programs were written on will start the next program and reset its specific time scale to start at time=0 instead of time=current time in order to allow for flexibility in changing time thresholds without rewriting the entire inverse tangent function every time. In this way, changing progress thresholds not only affects the rate of progress of the current program but the start time of all others after it as well. 

Energy Reduction & Values:
The energy reduction numbers used in this model are all based on roughly what types of energy would be used in each room and how much is possible to be reduced. These numbers will all total up to the total projected energy reduction per household in terms of CCF/kWh, but the individual breakdown per room type as found in this model is entirely arbitrary and was chosen according to what made the most sense based on knowledge of what energy is used in which room and roughly how much with regards to the savings measures for the room type. These values are also on a per-week basis, so the small size is understandable in that context (originally on a yearly basis, then divided by 52 to get weeks to make this work with the model)

Original Use & Baseline Use:
Although this model does not utilize this and instead operates on a total savings possible basis, the initial energy usage of a particular household can be put into the "___.CCFOriginalUse" and "___.CCFBaseline" variables (note that CCF is interchangeable with KWH here) to get the total amount of possible savings based on real data. Currently, baseline use is set to 0 for each program with original use equivalent to the total amount of energy capable of being reduced per week for that room type. These numbers were derived from an estimate on the total energy reduction possible in terms of kWh and CCF, which was then broken down into each room and the type of energy capable of being reduced in each (see above section for more on this).

Note that "TotalKWH/CCFSavings" is for each individual household, whereas "NeighborhoodKWH/CCFSavings" is for the entire neighborhood composed of the amount of houses stored in the variable "#Households."


Viewing Data Outputs:

- Viewing current program progress at time X:
- use the plot option to while selecting "BuildingEnvelope.Program", "ClimateControl.Program", "Kitchen.Program," etc., to see the progress curves for each program over time.
- Viewing savings data:
- use the data table option to view the kWh/CCF savings over time for the household, the community, or both, changing the time column to display most recent time first; this will give the total savings in each of those areas for that entire time period.
Update 24 Feburary 2016 (v3.1): This version has biomass, hydro and nuclear continuing at pre-transition maxima, rather than increasing. The combined emplacement rate cap for wind and PV is set at a default value of 5000 GW/year.  Major update 12 December 2015 (v3.0): This new version of the model o
Update 24 Feburary 2016 (v3.1): This version has biomass, hydro and nuclear continuing at pre-transition maxima, rather than increasing. The combined emplacement rate cap for wind and PV is set at a default value of 5000 GW/year.

Major update 12 December 2015 (v3.0): This new version of the model overhauls the way that incumbent energy source (fossil sources plus biomass, hydro electricity and nuclear electricity) supply capacity is implemented. This is now based on direct (exogenous) input of historical data, with the future supply curve also set directly (but using a separate input array to the historical data). For coal and natural gas fired electricity, this also requires that the simple, direct-input EROI method be used (i.e. same as for coal and NG heating, and petroleum transport fuels).

Note that this new version of the model no longer provides a historical view of the emplacement rates for energy supply sources other than wind and PV, and therefore no longer allows comparison of required emplacement rates for wind and PV with incumbent energy sources. Output data relating to this is available in model version v2.5 (see link below), for the specific transition duration built into that version of the model.

The previous version of the model (version 2.5) is available here.

The original "standard run" version of the model (v1.0) is available here.
The model contains the key components of our Planet's energy balance, including an albedo parameter (setting the fraction of reflected solar radiation) and an emissivity parameter (setting the fraction of ideal blackbody radiation that is actually emitted from Earth) 
The model contains the key components of our Planet's energy balance, including an albedo parameter (setting the fraction of reflected solar radiation) and an emissivity parameter (setting the fraction of ideal blackbody radiation that is actually emitted from Earth) 
 This shall become an illustration of the Chapter 5 "Pathways to a Post-Capitalist World" of the book "Less is More" from Jason Hickel. There are 5 suggested steps to obtain this: 1. End planned obsolescence; 2. Cut advertising; 3. Shift from ownership to usership; 4. End food waste; 5. Scale down e
This shall become an illustration of the Chapter 5 "Pathways to a Post-Capitalist World" of the book "Less is More" from Jason Hickel. There are 5 suggested steps to obtain this: 1. End planned obsolescence; 2. Cut advertising; 3. Shift from ownership to usership; 4. End food waste; 5. Scale down ecologically destructive industries. You will find these aspects in the diagram. In the chapter are some other aspect not covered yet in this diagram. 

Degrowth is not about reducing GDP. It is about reducing the material and energy throughput of the economy to bring it back into balance with the living world, while distributing income and resources more fairly, liberating people from needless work, and investing in the public goods that people need to thrive.
  2015 Springer book  on systems science. See planned  contents from blog . Reframed to be similar to the Understanding Systems Science Insight  IM-9773
 2015 Springer book on systems science. See planned contents from blog. Reframed to be similar to the Understanding Systems Science Insight IM-9773
Simulating both the blanket (Greenhouse effect) & the cooling effect (PeTa) with the most simple model possible.  More PeTa radiation will lower the Temperature on Earth. PeTa radiation is released when water changes from water vapor to liquid.   Trees evapoTranspirate a lot of water. More trees
Simulating both the blanket (Greenhouse effect) & the cooling effect (PeTa) with the most simple model possible.

More PeTa radiation will lower the Temperature on Earth. PeTa radiation is released when water changes from water vapor to liquid. 

Trees evapoTranspirate a lot of water. More trees will lead to more energy that will be evaporated and will lead to less infrared radiation emitted by Earth.