The current electricity portfolio of Texas is heavily reliant on high-emission sources of fossil fuel (i.e. Coal). Texas has a range of energy options at its disposal and has the opportunity to make choices that grow renewables (e.g. solar and wind) while encouraging the production of less carbon-intensive fossil fuels (e.g. natural gas).

As boundaries to our problem, we will be using 35 years as our time frame. We will also limit our model to the State of Texas as our spatial extent. Over the past decade, Texas is becoming a major natural gas consumer; the electricity portfolio has been gradually changing. However, around 40% of electricity is still generated from burning coal, and only a very minor portion of electricity is from renewables. Texas is betting better in adopting solar and wind energy, however generally speaking the state is still falling behind in renewable energy.

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.

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

-​(2011). A Look at Green Energy Sources for the Home. Realitybiznews. Retrieved from http://realtybiznews.com/a-look-at-green-energy-sources-for-the-home/9877539/

Two households with PV systems and Electric Vehicles, sharing a battery and connected to the grid. What are the advantages?

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 simulates population growth, culture, energy, and land use. Parameters are somewhat arbitrary, and can be tailored to a specific urban system using real data.

Basic idea is to model demand with endogenous growth (but "satiation" becomes possible - eventually - at some notional "sufficiency" level); and supply then attempts to track demand with some time lag (~5-50 years - characteristic of commissioning/decommissioning large scale energy infrastructure). But supply also produces pollution, which accoumulates. We can specify a notional constraint/limit; approaching this should trumpdemand and forces supply to zero. In this version we'll only have one source. so no substitution is possible. We expect to see a fairly sudden supply crash. Of course, "demand" will still carry merrily on its way up anyway, but the interpretation of the consequently growing supply shortfall will be left to the eye of the beholder. NB: this version doesn't automatically succeed in limiting P to P_max. It forces dS/dt to zero as A*(P/ P_max) reaches 1; and then as that value exceeds 1, dS/dt is forced negative. But this dynamics has no way to "undo" any overshoot of P over P_max (which would require S itself to become negative: "negative emissions"). Need to manual find/choose a big enough value of A to limit P effectively.