The statement that there can be no economic activity without  energy and that fossil fuels are finite contrasts with the fact that money is not finite and can be created by governments via their central banks at zero marginal cost whenever needed.

An important fact about COAL, GAS and OIL (even when produced via fracking) is that their net energy ratios are falling rapidly. In other words the energy needed to extract a given quantity of fossil fuels is constantly increasing. This ratio (Energy Invested on Energy Returned - EIOER) provides yet another warning that we can no longer rely on fossil fuels to power our economies. We cannot wait until the ratio falls to 1/1 before we invest seriously in alternative sources of energy, because by then industrial society as we know it doday will have ceased to exist. 

PS: A link between growth in energy consumption and GDP growth is clearly illustrated on slide 13 of Gail Tverberg's presentaion entitled ''Ooop! The world economy depends on an energy-related bubble''. In fact, the slide shows that growth in energy consumption usually precedes GDP growth.

https://gailtheactuary.files.wordpress.com/2015/10/oops-debt-bubble-10_30_15.pdf

Análise comparativa e econômica de diferentes tipos de biomassa e óleos vegetais brasileiros para produção  de  alimento, ração animal e  de biocombustível e Agroenergia com o estudo de sua Rota Química. 

 

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

Attempt to clarify the differences in the energy balance and carbohydrate insulin obesity models described in Speakman and Hall's 2021 science article See also Nature Metabolism Obesity Causal Model Differences 2024 article and insight

Test

Trying to show the drop in Barrels of Oil per day as the number of Electric Vehicles on the road increases.

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

A simple simulation​ of a house losing heat at a rate based on indoor vs. outdoor temperature difference, and turning a heating system on and off to maintain indoor temperature.

This model represents the core (more connected) assumptions of the proposed energy bill HR 4286

Two households with PV systems and electric vehicles sharing a battery and connected to the grid. What are the advantages?

This model prototypes the working of an Smart Grid with Electric Vehicles

The objective is testing the theoretical advantages of batteries (also batteries in Electric Vehicles) in combination with renewable energies. The model considers two houses, that store energy both in Electric Vehicles (Vehicle to Grid), and in a communal battery.

Except when specified otherwise, the units of all variables are expressed in W/h.

Press "Story" in the lower bar for a guided tour over the model. Better seen at 50% zoom.

by Carlos Varela (cvarela@gmx.at)

Charging Electric Vehicles will have an impact in the electricity network infrastructure. What will be the influence at district level?

Test

Buying and storing electricity when it is cheap, and selling it when it is expensive. What are the benefits, both public and private?

A detailed description of all model input parameters is available here. These are discussed further here and here.

Update 14 December 2015 (v2.5): correction to net output basis LCOE calculation, to include actual self power demand for wind, PV and batteries in place of "2015 reference" values.

Update 20 November 2015 (v2.4): levelised O&M costs now added for wind & PV, so that complete (less transmission-related investments) LCOE for wind and PV is calculated, for both gross and net output.

Update 18 November 2015 (v2.3: development of capital cost estimates for wind, PV and battery buffering, adding levelised capital cost per unit net output, for comparison with levelised capital cost per unit gross output. Levelised capital cost estimate has been substantially refined, bringing this into line with standard practice for capital recovery calculation. Discount rate is user adjustable.

Default maximum autonomy periods reduced to 48 hours for wind and 72 hours for PV.

Update 22 October 2015 (v2.2): added ramped introduction of wind and PV buffering capacity. Wind and PV buffering ramps from zero to the maximum autonomy period as wind and PV generated electricity increases as a proportion of overall electricity supply. The threshold proportion for maximum autonomy period is user adjustable. Ramping uses interpolation based on an elliptical curve between zero and the threshold proportion, to avoid discontinuities that produce poor response shape in key variables.

Update 23 September 2015 (v2.1): added capital investment calculation and associated LCOE contribution for wind generation plant, PV generation plant and storage batteries.

**This version (v2.0) includes refined energy conversion efficiency estimates, increasing the global mean efficiency, but also reducing the aggressiveness of the self-demand learning curves for all sources. The basis for the conversion efficiencies, including all assumptions relating to specific types of work & heat used by the economy, is provided in this Excel spreadsheet.

Conversion of self power demand to energy services demand for each source is carried out via a reference global mean conversion efficiency, set as a user input using the global mean conversion efficiency calculated in the model at the time of transition commencement (taken to be the time for which all EROI parameter values are defined. A learning curve is applied to this value to account for future improvement in self power demand to services conversion efficiency.**

The original "standard run" version of the model is available here.

Charging Electric Vehicles will have an impact in the electricity network infrastructure. What will be the influence at district level?

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

This simulation examines carrying capacity, based on a given cropland input in acres, assuming a rate up to 14 people per acre per year (roughly that produced by corn or potatoes).

Using a hydrogen storage to remain energy-independent over the year