Energy balance

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Question

How to calculate energy balances?

Answer

Calculations are based on matrices, i.e. sets of equations. There must be as many equations as there are unknown variables. For details, see Energy balance in Kuopio.

Rationale

Rationale

Use a table where different fuel types are columns and different stocks, energy production processes, or consumption types are rows called Energy accounts (Ene.account for short). See also an example File:Energy supply in Europe.xls. All Ene.accounts and fuel types used are listed on Energy consumption classes.

A part of a full energy balance sheet (ktoe/a).

	Coal and peat	Crude oil	Petrochemical products	Electricity	Heat
Production and supply of primary energy
Production	129
Import		28	63
Export
Conversion of primary energy to use
Transfers
Electricity plants
CHP plants	-129	-28		61	96
Final energy consumption
Industry
Road transport			54
Heating				10	96
Other energy use			9	51

Energy balance can be considered as double-entry bookkeeping. The production and conversion are typically credit (i.e., where the energy comes from), while consumption is debit (i.e., where the energy is used). In a typical case, both credit and debit are marked positive on the energy balance sheet. However, there are activities that convert one fuel to another, so that the energy is moved from one column to another. In this case, credit (the source) is marked negative and debit (the target) is marked positive. This is because the production and conversion rows together should reflect how much energy is actually available for final consumption. In other words, the sum of production and conversion rows should equal the sum of the consumption rows in every column.

Because production + conversion = consumption, also production = consumption - conversion. These equations are used to derive the supply that is needed to fulfil the demand.

Formula

Default run key: qffJP3u5RpFw1GuL

Amount of renewable fuels compared with peat (may be over 1): Consumption of process heat produced by industry itself: Consumption of electricity by households: Consumption of electricity by industry: Consumption of electricity by commerce: Consumption of electricity by municipality: Consumption of district heat by households: Consumption of district heat by industry: Consumption of district heat by commerce: Consumption of district heat by municipality: + Show code- Hide code library(OpasnetUtils) library(xtable) # These three are city-specific: Matrix_page, Additions, Solutions. Matrix_page <- "Op_en5469" # This is the page with the matrix content. Additions <- data.frame( # These are additional contents to the matrix, in addition to Matrix_page. Equation = "Fraction CHP renewable", Col = "CHP peat", ETMResult = Frac_CHP_renew, ETMDescription = "Actual number given by user." ) Solutions <- c(rep(0, 18), # These are the solutions (right sides) of the equations. Ind_process_heat, Cons_Home_electricity, Cons_Ind_electricity, Cons_Commerce_electricity, Cons_Municip_electricity, Cons_Home_heat, Cons_Ind_heat, Cons_Commerce_heat, Cons_Municip_heat ) dependencies <- data.frame(Name = c( "Matrix_page", "Additions", "Solutions" ), Key = "") formula <- function(dependencies, intermediates = FALSE, ...) { ComputeDependencies(dependencies, ...) ## Define the energy transformation matrix ETM. # Get the data from Opasnet Base. ETM <- tidy(op_baseGetData("opasnet_base", Matrix_page), objname = "ETM", direction = "wide") # Add user-defined data to it. ETM <- rbind(ETM, Additions) # Reshape the table to make a matrix, and replace NA with 0. ETM <- reshape(ETM, timevar = "Col", idvar = "Equation", v.names = "ETMResult", direction = "wide") colnames(ETM) <- gsub("ETMResult.", "", colnames(ETM)) if(intermediates) {print(xtable(ETM), type = 'html')} # Show the matrix with explanations. ETM <- as.matrix(ETM[, !colnames(ETM) %in% c("Equation", "ETMDescription")]) for(i in 1:ncol(ETM)) { ETM[is.na(ETM[, i]), i] <- 0 } # Define the outputs for equations (for most equations, it is a zero sum game). out <- solve(ETM, Solutions) # Solve the matrix. out <- data.frame(Energy.class = colnames(ETM), Result = out) return(out) } energy.balance <- new("ovariable", name = "energy.balance", dependencies = dependencies, formula = formula ) temp <- EvalOutput(energy.balance) print(xtable(temp@output), type = 'html') objects.put(energy.balance) cat("Object energy.balance saved. Write down the key of the model run page for further use.\n")

←--#: . jkfhgkhfkghf --Matthew 10:18, 7 February 2013 (EET) (type: truth; paradigms: science: defence)

The model first creates the matrix (and shows it to the user if the user has defined intermediates = TRUE), and then it fills all empty cells with 0 and solves it by using the input values the user has given via the user interface. (The user interface can later be replaced by another model.) All the current input values are final consumptions. The example interface and values are based on the Kuopio data, but they are not stored as a part of the ovariable.

See also

• media:Health impacts of energy production.ppt (a lecture that also contains explanation of an energy balance using matrices)
• Energy balance in Kuopio Describes the production and consumption of energy in Kuopio.
• Energy balance in Stuttgart Describes the production and consumption of energy in Stuttgart.
• Energy balance in Suzhou Describes the production and consumption of energy in Suzhou.
• A previous method to calculate energy balances. Includes also other pages:
  • Energy transformations Describes the inputs and outputs of energy processes. Shows, which other things change when some input or output is changed.
  • Market allocation factor
• File:Energy supply in Europe.xls
• Climate change policies in Kuopio Indicates, which items change when a policy changes.
• Energiatase
• Kasvihuonekaasupäästöt/Kuopio
• Päätösanalyysia_ja_riskinhallintaa.ppt
• Urgenche
• http://www.energia.fi/sites/default/files/polttoaine-energian_maarittaminen_taselaskennan_avulla.pdf
• Uusiutuvan energian riskit selvitetään
• Urgenche: Mesap Planet energy model

Urgenche research project 2011 - 2014: city-level climate change mitigation

Urgenche pages Urgenche main page · Category:Urgenche · Urgenche project page (password-protected) Relevant data Building stock data in Urgenche‎ · Building regulations in Finland · Concentration-response to PM2.5 · Emission factors for burning processes · ERF of indoor dampness on respiratory health effects · ERF of several environmental pollutions · General criteria for land use · Indoor environment quality (IEQ) factors · Intake fractions of PM · Land use in Urgenche · Land use and boundary in Urgenche · Energy use of buildings Relevant methods Building model · Energy balance · Health impact assessment · Opasnet map · Help:Drawing graphs · OpasnetUtils‎ · Recommended R functions‎ · Using summary tables‎ City Kuopio Climate change policies and health in Kuopio (assessment) · Climate change policies in Kuopio (plausible city-level climate policies) · Health impacts of energy consumption in Kuopio · Building stock in Kuopio · Cost curves for energy (prioritization of options) · Energy balance in Kuopio (energy data) · Energy consumption and GHG emissions in Kuopio by sector · Energy consumption classes (categorisation) · Energy consumption of heating of buildings in Kuopio · Energy transformations (energy production and use processes) · Fuels used by Haapaniemi energy plant · Greenhouse gas emissions in Kuopio · Haapaniemi energy plant in Kuopio · Land use in Kuopio · Building data availability in Kuopio · Password-protected pages: File:Heat use in Kuopio.csv · Kuopio housing City Basel Buildings in Basel (password-protected) Energy balances Energy balance in Basel · Energy balance in Kuopio · Energy balance in Stuttgart · Energy balance in Suzhou

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