Added documentation on flexibility in the ETM and updated existing docs

general/documentation.md

@@ -5,17 +5,19 @@ Introduction
 
 The Energy Transition Model (ETM) allows the user to explore the future of the energy system in several different geographical regions. The model starts out with the current energy situation in the region, based on extensive research by Quintel and its partners. Select a region, a future year and a difficulty level to start the model. It will start without any changes to the present day energy system. The user can then use sliders to input assumptions about how the system will change in the future. The ETM immediately calculates the results of any measures taken and presents it to the user using graphs and a dashboard. In this way a user can create a scenario that showcases a possible future energy system.
 
-The model consists of 4 major areas:
+The model consists of 5 major areas:
 
 -   **[Targets](targets.md):** where users set their policy targets that they are later evaluated against
 -   **[Demand](demand.md):** where users set the future demand of energy in 6 economic sectors (households, non-residential buildings, transport, industry, agriculture and other)
--   **[Costs](costs.md):** where users specify their estimations of future energy costs
+-   **[Flexibility](flexibility.md):** where users set the technologies to deal with excess electricity
 -   **[Supply](supply.md):** where users set how and what energy is supplied in the future
+-   **[Costs](costs.md):** where users specify their estimations of future energy costs
+
 
 The model uses data on energy consumption and production and present day state-of-the-art technology data. The use of underlying assumptions has been minimized and assumptions about changes in the future are left to the user as much as possible. With the sliders in the interface a user can influence the future state of the model. If no slider is available to set a certain change in the future, no assumption is made by the ETM.
 **Note:** The user is responsible for the internal consistency of all assumptions, as no automatic correction of inconsistent assumptions takes place.
 
-The energy system is approached as an ‘energy flow’ or Sankey diagram based on a network of interconnected ‘energy convertors’. Energy converters convert energy carriers into other energy and losses, for example a gas heater converts gas into heat and loss. This network of converters is called a ‘graph’. The ETM uses two graphs, a static one for the present and a dynamic one for the future situation; the latter can be influenced using the sliders in the interface. The model does not calculate transition paths and does not take into account feedback loops (e.g. high costs do not depress demand).
+The energy system is approached as an ‘energy flow’ or Sankey diagram based on a network of interconnected ‘energy converters’. Energy converters convert energy carriers into other energy and losses, for example a gas heater converts gas into heat and loss. This network of converters is called a ‘graph’. The ETM uses two graphs, a static one for the present and a dynamic one for the future situation; the latter can be influenced using the sliders in the interface. The model does not calculate transition paths and does not take into account feedback loops (e.g. high costs do not depress demand).
 
 Interface
 ---------
@@ -24,7 +26,7 @@ Interface
 
 ### Layout
 
-The layout of the ETM is based on its four main topics (Targets, Demand, Costs and Supply), which are located in the tabs at the top of each page. Each main topic is divided into several sub-topics. These are are described further on the dedicated pages of each main topic.
+The layout of the ETM is based on its five main topics (Targets, Demand, Flexibility, Supply and Costs), which are located in the tabs at the left of each page. Each main topic is divided into several sub-topics. These are are described further on the dedicated pages of each main topic.
 
 #### Targets
 
@@ -38,18 +40,24 @@ Allows the user to set targets for sustainability, dependence on other countries
 
 Allows the user to change the way energy is used and what energy demand will be in the future in the sectors: Households, Non-residential buildings, Transport, Industry, Agriculture and Other.
 
-#### Cost
+#### Flexibility
 
-*Main article: [Costs](costs.md)*
+*Main article: [Flexibility](flexibility.md)*
 
-Allows the user to input his assumptions on how costs for fuels, electricity production technologies and CO<sub>2</sub> emission will change.
+Large amount of volatile electricity producertion will most likely result in times when supply exceeds demand. In order to deal with this excess electricity, the user can install several flexibility technologies like batteries and power to gas. 
 
 #### Supply
 
 *Main article: [Supply](supply.md)*
 
 Allows the user to determine which technologies are used for central electricity and heat production and also how green transport fuels will be.
 
+#### Cost
+
+*Main article: [Costs](costs.md)*
+
+Allows the user to input his assumptions on how costs for fuels, electricity production technologies and CO<sub>2</sub> emission will change.
+
 ### Charts
 
 The charts on the right hand side of the page directly show the result when a slider is changed. The charts provide insight in the energy system by showing figures of the current situation as well as of the scenario you are creating. The transition path in the charts is only an indication of the development, as the values between the current year and the scenario year are solely an interpolation between the figures of the two years.
@@ -64,14 +72,17 @@ The dashboard is the row of numbers at the bottom of each page. It shows the mos
 
 -   Energy use: Percentage difference in primary energy use between current situation and scenario
 -   CO<sub>2</sub> emissions: Percentage difference in energetic CO<sub>2</sub> emissions due to final energy consumption between 1990 and the scenario year
+-   Domestic CO<sub>2</sub> emissions: Percentage difference in energetic CO<sub>2</sub> emissions due to final energy consumption between 1990 and the scenario year, excluding the CO<sub>2</sub> emissions of imported electricity
 -   Energy imports: Share of primary energy that is imported
 -   Loss of load: Indicator showing the chance that production capacity is less than demand
 -   Cost: Total yearly cost of energy supply in current year's euros
--   Costs per household: The total yearly cost of energy divided by the number of households
--   Bio footprint: Land area necessary to grow all the biomass used compared to the arable land in your country
+-   Costs per home: The total yearly cost of energy divided by the number of households
+-   Employment: Percentage difference in local employment between the start year and the scenario
+-   Profitable plants: Percentage of plants installed in the scenario that make a profit as calculated by the merit order calculation
+-   Bio-footprint: Land area necessary to grow all the biomass used compared to the arable land in your country
 -   Renewables: Percentage of final energy consumption that is renewable
--   Renewable electricity: Percentage of final energy consumption that is renewably produced
--   Goals: Indicator showing how many of your own preset goals you have reached in the scenario
+-   Renewable el.: Percentage of final energy consumption that is renewably produced
+-   Targets: Indicator showing how many of your own preset targets you have reached in the scenario
 
 You can click on each of the indicators in the dashboard to get a pop-up with detailed information on each of the subjects. For more information on the dashboard items see the main article on the Dashboard.
 
@@ -235,9 +246,8 @@ Currently, the network costs are only calculated for the Netherlands. These cost
 
 *Main article: [Merit order](merit_order.md)*
 
-In future energy scenarios it is very likely that power plants will operate differently than they do now due to factors such as fuel price and market penetration of renewables. The merit order calculation determines the operating hours of power plants based on the power production park created by the user. The calculation shows that if for example the amount of wind electricity production increases the operating hours of conventional power plants decreases.
+In future energy scenarios it is very likely that power plants will operate differently than they do now due to factors such as fuel price and market penetration of renewables. The merit order calculation determines the operating hours of power plants based on the power production park created by the user. The calculation shows that if for example the amount of wind electricity production increases the operating hours of conventional power plants decreases. The merit order calculation also determines if hours occur when volatile and must-run electricity production exceeds demand. This user can decide what to do with this excess electricity, e.g. storing it in batteries for later use or converting it to gas with a power to gas unit.
 
-Currently the merit order calculation only works for the Netherlands.
 
 ### Loss of load calculations
 
@@ -249,6 +259,8 @@ The calculation shows the probability that available electricity production capa
 
 *Main article: [Storage and conversion of electricity](storage.md)*
 
+*These static electricity storage calculations have largely been replaced by a more dynamic excess electricity calculation that is part of the merit order calculation. The main results of the electricity storage calculation are, however, still available in the front-end of the ETM.*
+
 For large installed capacities of wind turbines and solar PV, it may become possible that production of wind and solar power exceeds the demand for electricity. The 'Electricity storage' module of the ETM displays cost trends of technologies that can absorb excess electricity as a function of installed wind and solar capacity. If very large installed volatile capacities are installed, it might become economically interesting to build first conversion units that reduce the amount of curtailment.
 
 Currently, the module "Electricity storage and conversion" is static and only works for The Netherlands. The cost trends are only 'indicative' because of high uncertainties in the calculation.

general/flexibility.md

@@ -0,0 +1,45 @@
+# Flexibility
+
+Wind turbines and solar panels are subject to volatile natural patterns. The electricity that they produce might therefore not always be used to match demand directly. This mismatch will lead to excess electricity, in particular in scenarios with large amounts of volatile production capacity. To prevent curtailment of this excess electricity, the ETM contains several flexibility technologies that can make good use of it.
+
+## Implementation in merit order module
+
+As described in [the merit order documentation](merit_order.md), the merit order module of the ETM calculates the hourly electricity mix based on the demand for electricity and the installed capacities and marginal costs of the electricity producing technologies. The merit order module distinguishes three types of electricity producers: volatile, must-run and dispatchable producers. The latter can be switched on or off depending on the demand for electricity. The first two, however, will produce electricity based on volatile natural patterns or based on heat demand and are therefore not coupled to the electricity demand. For scenario's with large installed capacities of volatile and must-run producers, electricity production might exceed demand. The merit order module keeps track of the amount of excess electricity at each hour and lets the user decide what to do with this electricity. The various flexibility options are described below.
+
+## Flexibility options
+
+### Order of flexibility options
+
+The ETM contains several technologies to deal with excess electricity. The user can decide which of these options to use first, second and so on, by changing the the order of the options in the flexibility options selector. Curtailment is always the last resort and hence locked in the last position. The flexibility options are modelled such that excess electricity is first used by the technology that is position 1. Once the full capacity of the technology is reached or its entire volume is filled (in case of batteries), any remaining excess electricity will be used by the technology in position 2 and so on.
+
+![Figure 1: Flexibility options selector](../images/20160809-screenshot-flex-options.png)
+
+### Storage in batteries
+A home battery that can be used to store excess electricity. The user can set the percentage of households that is equipped with such battery. The specs of these battery are documented in its [node source analysis](https://github.com/quintel/etdataset-public/blob/master/nodes_source_analyses/households/households_flexibility_p2p_electricity.converter.xlsx). The electricity that is stored in the home battery will be supplied back to the grid as soon as the excess electricity event has ended.
+
+### Storage in electric vehicles
+The user can set the percentage of his car battery storage volume that can be used to store excess electricity. In order for this to have any effect, the user first needs to include electric vehicles in his scenario. The specs of these electric vehicles are described in their [node source analysis](https://github.com/quintel/etdataset-public/blob/master/nodes_source_analyses/transport/transport_car_using_electricity.converter.xlsx). The electricity that is stored in the electric vehicles will be supplied back to the grid as soon as the excess electricity event has ended.
+
+### Conversion to heat
+Converting excess electricity into heat is easy. At times of excess electricity supply, a electric boiler can be used to (pre-)heat water for hot water consumption. If the volume of the boiler is selected appropriately, the boiler will on average be emptied once a day, leaving it ready to convert more excess electricity. The user can set the percentage of households that is equipped with a power-to-heat boiler. And the end of a merit order run, the heat generated by power-to-heat for the entire year will be subtracted from the heat demand that needs to be fulfilled by the other heating technologies. The specs of power-to-heat are described in a [node source analysis](https://github.com/quintel/etdataset-public/blob/master/nodes_source_analyses/households/households_flexibility_p2h_electricity.converter.xlsx).
+
+### Conversion to gas
+Excess electricity can be used to produce hydrogen in an electrolysis process. In the ETM, the hydrogen produced by power-to-gas will be used in the transport sector, provided that you have included hydrogen cars in your scenario. Any excess hydrogen will be exported. The user can set the percentage of hydrogen cars in the car technology slide and review the origin of the hydrogen used by these cars in the hydrogen production slide. The user can decide how many power-to-gas plants to built; their specs are documented in a [node source analysis](https://github.com/quintel/etdataset-public/blob/master/nodes_source_analyses/energy/energy_flexibility_p2g_electricity.converter.xlsx).
+
+### Export
+Excess electricity can be exported to neighbouring countries through the interconnectors between these countries. The capacity of these interconnectors is limited and can be adjusted by the user. Also, at times of excess electricity, the neighbouring countries will most likely also have to deal with this excess electricity. Hence the user can squeeze the available interconnector capacity to avoid overestimating the amount of electricity that can be exported.
+
+### Curtailment
+Any remaining excess electricity will be curtailed by switching off the wind turbines and solar panels. Curtailment is always the last resort.
+
+## Output
+
+To provide insight in the results of the merit order calculation regarding the flexibility options, two charts and a table are provided in the ETM. The first chart shows the hourly use of excess electricity. The second show the annual use of this excess electricity.
+
+![Figure 2: Merit Order hourly flexbility chart](../images/20160810-screenshot-hourly-flex.png)
+
+![Figure 3: Merit Order use of excess electricity chart](../images/20160810-screenshot-excess-el.png)
+
+Finally a table is available to provide insight in the available capacities and volumes of the flexibility technologies as well as, again, their annual usage.
+
+![Figure 4: Merit Order flexibility options table](../images/20160810-screenshot-flex-options.png)