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

Clone of Smart Grid: Electricity storage and variable energy pricing
Insight diagram
This model represents the core (more connected) assumptions of the proposed energy bill HR 4286
Core of HR4286
Insight diagram
Clone of energy supply and losses for a house
Insight diagram
​Climate Sector Boundary Diagram By Guy Lakeman
 Climate, Weather, Ecology, Economics, Population, Welfare, Energy, Policy, CO2, Carbon Cycle, GHG (green house gasses, combined effects)

As general population is composed of 85% with an education level of a 12 grader or less (a 17 year old), a simple block of components concerning the health of the planet needs to be broken down into simple blocks.
Perhaps this picture will show the basics on which to vote for a sustained healthy future
Democracy is only as good as the ability of the voters to FULLY understand the implications of the policies on which they vote., both context and the various perspectives.   National voting of unqualified voters on specific policy issues is the sign of corrupt manipulation.

Clone of Climate Sector Boundary Diagram of Guy Lakeman
Insight diagram
Buying and storing electricity when it is cheap, and selling it when it is expensive. What are the benefits, both public and private?

Clone of Smart Grid: Electricity storage and variable energy pricing
Insight diagram
Two households with PV systems and Electric Vehicles, sharing a battery and connected to the grid. What are the advantages?


Vehicle to Grid Simulation
Insight diagram
Buying and storing electricity when it is cheap, and selling it when it is expensive. What are the benefits, both public and private?

Clone of Smart Grid: Electricity storage and variable energy pricing
Insight diagram
Working Model 11/24
Insight diagram
Buying and storing electricity when it is cheap, and selling it when it is expensive. What are the benefits, both public and private?

Clone of Smart Grid: Electricity storage and variable energy pricing
Insight diagram
This simulation examines the caloric well of a given settlement. Just add in a few pieces of information and run the insight simulation.
Simple Caloric Well Simulator
Insight diagram
Colombia has the opportunity to implement the Autoswitch, but there are no guarantees of its impact on the market, given its complexity. This model implements two policies: Price Control through Demand Response - RD and Autoswitch. In this model we explore de impact of the AMI cost.
Demand Response Model and Autoswitch - AMI costs - v4 - Imprimir
Insight diagram

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

Clone of Energy Transition Model - Team 1
Insight diagram
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)
Clone of [Reference] Vehicle to Smart Grid - Prototype
Insight diagram
Simulate an impact of an asteroid of any Diameter at any given Speed!
Clone of Asteroid impact simulator
Insight diagram
Afirmația că nu poate exista activitate economică fără energie și că combustibilii fosili sunt finiți contrastează cu faptul că banii nu sunt finiți și pot fi creați de guverne prin intermediul băncilor lor centrale la costuri marginale zero ori de câte ori este nevoie.
Un fapt important despre cărbunele, gazul și petrolul (mai ales atunci când sunt produse prin fracking) este că raporturile lor energetice nete scad rapid. Cu alte cuvinte, energia necesară pentru a extrage o anumită cantitate de combustibili fosili este în continuă creștere. Raportul în scădere „EROI” (Returul Energiei asupra Energiei Investite) oferă încă un avertisment că nu ne mai putem baza pe combustibilii fosili pentru a ne alimenta economiile. În 1940 a fost nevoie de energia unui singur baril de petrol pentru a extrage 100. Astăzi, energia unui baril de petrol va da doar 15. Nu putem aștepta până când raportul scade la 1/1 înainte de a investi serios în surse alternative de energie, pentru că până atunci societatea industrială așa cum o cunoaștem în prezent va fi încetat să mai existe. Un EROI de 1:1 înseamnă că este nevoie de energia unui baril de petrol pentru a extrage un baril de petrol - producția de petrol s-ar opri pur și simplu!

Clone of Energy and Economic Activity
Insight diagram
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

Clone of Energy and Economic Activity
Insight diagram
Eigg Grid
Insight diagram
Two households with PV systems and Electric Vehicles, sharing a battery and connected to the grid. What are the advantages?


Clone of Vehicle to Grid Simulation
Insight diagram
Combining electromobility and renewable energies since 2014.

http://www.amsterdamvehicle2grid.nl/

Clone of Amsterdam V2G simulation 2.0
Insight diagram
Buying and storing electricity when it is cheap, and selling it when it is expensive. What are the benefits, both public and private?

Clone of Smart Grid: Electricity storage and variable energy pricing
Insight diagram
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)
Clone of Vehicle to Grid Simulation
Insight diagram
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)
Clone of Vehicle + Smart Grid
Insight diagram
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 (especially 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. The falling ratio 'EROI' (Energy Return on Energy Invested ) provides yet another warning that we can no longer rely on fossil fuels to power our economies. In 1940 it took the energy of only one barrel of oil to extract 100. Today the energy of 1 barrel of oil will yield only 15. 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. An EROI of 1:1 means that it takes the energy of one barrel of oil to extract one barrel of oil - oil production would simply stop! 


Clone of Energy and Economic Activity
Insight diagram
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.
Clone of Energy transition to lower EROI sources (v2.5)