Getting Started

Creating a Script

As an introduction to PSRIO, we will show you how to create PSRIO recipes from scratch using the output data from example cases inside the SDDP installation folder. The example case 20 will be used for the explanation. It consists, basically, of one system containing three thermal plants supplying energy to consumers. Twelve stages constitute the study horizon, and the execution is deterministic.

Example

The first example is about demand's marginal cost. We want to get an average value within the stages of the file cmgdem.csv. Therefore, since this output is a system-level variable, we can start loading the system collections with the following command:

system = System();

Then, we load the marginal cost data from the file cmgdem.csv:

cmgdem = system:load("cmgdem");

The data can be seen in the image below:

The processing is accomplished using the method aggregate_stages, with the parameter BY_AVERAGE():

cmgdem_avg = cmgdem:aggregate_stages(BY_AVERAGE());

We save the expression with the following method, and the PSRIO will output the cmgdem_avg.bin and cmgdem_avg.hdr.

cmgdem_avg:save("cmgdem_avg");

If we want to save a CSV file, we should use the additional parameter:

cmgdem_avg:save("cmgdem_avg", {csv=true});

Let's see what the final result looks like:

As we can see, the stages collapsed into one single value representing the average value of the demand marginal costs over the study horizon.

Example

Suppose we want to extract the total amount of energy generated by the plants based on the information received from SDDP about the generations in each stage of each plant, which we found in the file gerter.csv. The first step is to load the thermal collection with the following command:

thermal = Thermal();

Now, we have access to the attributes of each thermal plant in the system. As our interest lies in the generation, we will load the thermal generation data with the command:

gerter = thermal:load("gerter");

Check the data contained in the file:

Notice that we managed to load the generation data by informing the filename of the output. Now, we can make operations with the thermal generation data. We want to sum the values of each plant regarding one stage so that there is only one value per stage representing the total generation of the system.

total_gerter = gerter:aggregate_agents(BY_SUM(), "Total thermal");

total_gerter:save("total_gerter", {csv=true});

The first instruction is to aggregate agents, summing their respective generations for each stage. In the subsequent command, we are saving the data stored in the variable total_gerter to the file total_gerter.csv. The processed data looks like this:

The best way to visualize the output is by plotting the data, making one of them. First, let’s define an object for the chart.

chart = Chart("My first chart");

We indicate to the chart object that we want to plot the data in the file variable total_gerter, which we have just created.

chart:add_line(total_gerter);

After that, we will define a tab object to hold chart objects information and then add the chart and save it to the file thermal_report.html.

tab = Tab("My first tab");
tab:push(chart);
tab:save("thermal_report");

By clicking in the file thermal_report.html, that's what we get:

In short, the recipe for this work is as follows:

-- load thermal collections and thermal generation data
thermal = Thermal();
gerter = thermal:load("gerter");

-- aggregate agents generations by sum and save to output file
total_gerter = gerter:aggregate_agents(BY_SUM(), "Total thermal");
total_gerter:save("total_gerter", {csv=true});

-- create chart object
chart = Chart("My first chart");

-- add total generation info
chart:add_line(total_gerter);

-- create dashboad object
tab = Tab("My first tab");

-- add chart and save to html file
tab:push(chart);
tab:save("thermal_report");

There are two ways to run the script above. We are now going to explain each one of them in the next section of this tutorial.

Running a script

Graph 4.0

Graph 4.0 is a graphing tool that allows us to make PSRIO scripts inside an editor. After the execution of SDDP, open Graph 4.0:

Select the PSRIO editor option in the menu located on the left side of your screen:

You can create a new script, write down the code, save it, and then you will be ready to go.

SDDP

We can run a PSRIO script automatically after an SDDP execution. To do it, we need to save an sddp.lua file in the case folder. The SDDP model will run this script and produce the outputs and tab defined on it.

Attributes

Attributes are properties that characterize an object or, in the context of PSRIO, an expression. Expressions related to results of a PSR model, whose data can change over stages, scenarios, and blocks, for example, have a set of attributes in PSRIO that can be useful in some tasks. In the example below, we load the thermal generation:

thermal = Thermal();
gerter = thermal:load("gerter");

And the log shows some expression's attributes information:

[info] Loading gerter (stages: 12 [1:12] [monthly] [10/2016], blocks: hour, scenarios: 1200, unit: GWh, agents: 3 [thermal])

From the log, it is possible to see that gerter has:

• 12 stages in a month-level resolution
• initial stage in 10/2016
• blocks
• 1200 scenarios
• generation data given in GWh
• 3 agents

All attributes related to stages, block, scenarios, agents and units of an expression and their respective methods are presented in the tables below.

Stage

Method	Type	Syntax
Stages	number	attribute = exp:stages()
Stage	number	attribute = exp:stage(index)
Stage Type	number	attribute = exp:stage_type()
Initial Stage	number	attribute = exp:initial_stage()
Initial Year	number	attribute = exp:initial_year()
Final Year	number	attribute = exp:final_year()
Week	number	attribute = exp:week(stage)
Month	number	attribute = exp:month(stage)
Year	number	attribute = exp:year(stage)

Example

stages = gerter:stages() -- 12

stage1 = gerter:stage(1) -- 10
stage2 = gerter:stage(2) -- 11
stage3 = gerter:stage(3) -- 12
stage4 = gerter:stage(4) -- 13

stage_type = gerter:stage_type() -- 2 (monthly)

initial_stage = gerter:initial_stage() -- 10
initial_year = gerter:initial_year() -- 2016
final_year = gerter:final_year() -- 2017

month1 = gerter:month(1) -- 10
month2 = gerter:month(2) -- 11
month3 = gerter:month(3) -- 12
month4 = gerter:month(4) --  1

year1 = gerter:year(1) -- 2016
year4 = gerter:year(4) -- 2017

Blocks

Method	Type	Syntax
Blocks	number	attribute = exp:blocks(stage)
Has blocks	boolean	attribute = exp:has_blocks()
Is hourly	boolean	attribute = exp:is_hourly()

Example

blocks1 = gerter:blocks(1) -- 744
blocks2 = gerter:blocks(2) -- 720

has_blocks = gerter:has_blocks() -- true

is_hourly = gerter:is_hourly() -- true

Scenarios

Method	Type	Syntax
Scenarios	number	attribute = exp:scenarios()

Example

scenarios = gerter:scenarios() -- 1200

Agents

Method	Type	Syntax
Agents	vector of strings	attribute = exp:agents()
Agents Size	number	attribute = exp:agents_size()
Agent	string	attribute = exp:agent(index)

Example

[info] Thermal 1 at index 1
[info] Thermal 2 at index 2
[info] Thermal 3 at index 3

agents = gerter:agents() -- {"Thermal 1", "Thermal 2", "Thermal 3"}
for i, agent in ipairs(agents) do
    info(agent .. " at index " .. i);
end

size = gerter:agents_size() -- 3
for i = 1,size do
    agent = gerter:agent(i);
    info(agent .. " at index " .. i);
end

Unit

Method	Type	Syntax
Unit	string	attribute = exp:unit()

Example

unit = gerter:unit() -- "GWh"

Collections

Collection	Constructor	Enumerate
Area	Area()	Collection.AREA
Balancing Area	BalancingArea()	Collection.BALANCING_AREA
Balancing Area Hydro	BalancingAreaHydro()	Collection.BALANCING_AREA_HYDRO
Balancing Area Thermal	BalancingAreaThermal()	Collection.BALANCING_AREA_THERMAL
Battery	Battery()	Collection.BATTERY
Bus	Bus()	Collection.BUS
Circuit	Circuit()	Collection.CIRCUIT
Circuits Sum	CircuitsSum()	Collection.CIRCUITS_SUM
DC Link	DCLink()	Collection.DCLINK
Demand	Demand()	Collection.DEMAND
Demand Segment	DemandSegment()	Collection.DEMAND_SEGMENT
Expansion Capacity	ExpansionCapacity()	Collection.EXPANSION_CAPACITY
Expansion Project	ExpansionProject()	Collection.EXPANSION_PROJECT
Fuel	Fuel()	Collection.FUEL
Fuel Consumption	FuelConsumption()	Collection.FUEL_CONSUMPTION
Fuel Contract	FuelContract()	Collection.FUEL_CONTRACT
Fuel Reservoir	FuelReservoir()	Collection.FUEL_RESERVOIR
Generator	Generator()	Collection.GENERATOR
Generation Constraint	GenerationConstraint()	Collection.GENERATION_CONSTRAINT
Generic	Generic()	---
Hydro	Hydro()	Collection.HYDRO
Interconnection	Interconnection()	Collection.INTERCONNECTION
Interconnection Sum	InterconnectionSum()	---
Power Injection	PowerInjection()	Collection.POWERINJECTION
Renewable	Renewable()	Collection.RENEWABLE
Renewable Gauging Station	RenewableGaugingStation()	Collection.RENEWABLE_GAUGING_STATION
Reserve Generation Constraint	ReserveGenerationConstraint()	Collection.RESERVE_GENERATION_CONSTRAINT
Study	Study()	---
System	System()	Collection.SYSTEM
Thermal	Thermal()	Collection.THERMAL

Loading an Output

Operator	Syntax
Load method	output = collection:load("filename")

The generic collection can load any output with any agent type.

Example

The following example loads two outputs, `gerhid and fprodt, considering the agents as hydro plants collection:

hydro = Hydro();
gerhid = hydro:load("gerhid");
fprodt = hydro:load("fprodt");

Example

The following example loads two outputs, cmgdem and demand, considering the agents as system collection:

system = System();
cmgdem = system:load("cmgdem");
demand = system:load("demand");

Example 3

The following example loads two outputs, gerter and coster, considering the agents as thermal plants collection:

thermal = Thermal();
gerter = thermal:load("gerter");
coster = thermal:load("coster");

Example 4

The following example loads two outputs, objcop and outdfact, considering the agents as generic:

generic = Generic();
objcop = generic:load("objcop");
outdfact = generic:load("outdfact");

Loading a Generic CSV

Operator	Syntax
Load table method	table = study:load_table("filename.csv")

The following example loads a generic csv table and iterates through the rows:

Example

file.csv:

Name         , Node, Interval, Startup, Participation
H_1_1        , 1   , 1       , 1      , 0.79
R_1_3        , 1   , 1       , 1      , 0.20
CONTRATO_FLAT, 1   , 1       , 1      , 1

script:

study = Study();
table = study:load_table("file.csv");

info("Name,Node,Interval,Startup,Participation");
for i=1,#table do
    info(
        table[i]["Name"] .. "," .. 
        table[i]["Node"] .. "," .. 
        table[i]["Interval"] .. "," .. 
        table[i]["Startup"] .. "," .. 
        table[i]["Participation"]
    );
end

Loading an Input

• Area
• Battery
• Bus
• Circuit
• Demand
• Demand Segment
• Fuel
• Gauging Station
• Hydro
• Interconnection
• Power Injection
• Renewable
• Renewable Gauging Station
• System
• Thermal

Area

Data	Unit
area.code	---
area.imported	MW
area.exported	MW

Battery

Data	Unit
battery.code	---
battery.state	---
battery.capacity	MW

Bus

Data	Unit
bus.code	---
bus.voltage_level	kV

Circuit

Data	Unit
circuit.code	---
circuit.state	---
circuit.resistance	%
circuit.reactance	%
circuit.capacity	MW
circuit.emergency_capacity	MW
circuit.DLR_factor	pu
circuit.monitored	---
circuit.monitored_contingencies	---
circuit.is_dc	---
circuit.international_cost_right	$/MWh
circuit.international_cost_left	$/MWh

DC Link

Data	Unit
dclink.code	---
dclink.state	---
dclink.capacity_right	MW
dclink.capacity_left	MW

Demand

Data	Unit
demand.code	---
demand.is_elastic	---
demand.inelastic_hour	MW
demand.inelastic_block	GWh
demand.is_flexible	---
demand.max_increase	pu
demand.max_decrease	pu
demand.curtailment_cost	$/MWh
demand.max_curtailment	pu

Demand Segment

Data	Unit
demand_segment.hour	MW
demand_segment.block	GWh

Fuel

Data	Unit
fuel.code	---
fuel.cost	$/gal
fuel.emission_factor	tCO2/MWh

Gauging Station

Data	Unit
gauging_station.code	---
gauging_station.inflow	m3/s
gauging_station.forward	m3/s
gauging_station.backward	m3/s
gauging_station.hour_inflow_historical_scenarios_nodata	---
gauging_station.hour_inflow_historical_scenarios	m3/s
gauging_station.hour_inflow	m3/s

Hydro

Data	Unit
hydro.code	---
hydro.state	---
hydro.units	---
hydro.system	---
hydro.max_generation	MW
hydro.max_generation_available	MW
hydro.forced_outage_rate	%
hydro.historical_outage_factor	%
hydro.min_storage	hm3
hydro.max_storage	hm3
hydro.min_turbining_outflow	m3/s
hydro.max_turbining_outflow	m3/s
hydro.om_cost	$/MWh
hydro.irrigation	m3/s
hydro.min_total_outflow_modification	m3/s
hydro.target_storage_tolerance	%
hydro.disconsider_in_stored_and_inflow_energy	---
hydro.mean_production_coefficient	MW/(m3/s)
hydro.loss_factor	pu
hydro.min_total_outflow	m3/s
hydro.min_total_outflow_penalty	k$/m3/s
hydro.min_total_outflow_penalty_type	---
hydro.max_total_outflow	m3/s
hydro.max_total_outflow_penalty	k$/m3/s
hydro.max_total_outflow_penalty_type	---
hydro.min_operative_storage	hm3
hydro.min_operative_storage_penalty	k$/hm3
hydro.min_operative_storage_penalty_type	---
hydro.max_operative_storage	hm3
hydro.max_operative_storage_penalty	k$/hm3
hydro.max_operative_storage_penalty_type	---
hydro.flood_control	hm3
hydro.alert_storage	hm3
hydro.alert_storage_penalty	k$/hm3
hydro.alert_storage_penalty_type	---
hydro.min_spillage	m3/s
hydro.min_spillage_penalty	k$/m3/s
hydro.min_spillage_penalty_type	---
hydro.max_spillage	m3/s
hydro.max_spillage_penalty	k$/m3/s
hydro.max_spillage_penalty_type	---
hydro.min_bio_spillage	%
hydro.min_bio_spillage_penalty	k$/hm3
hydro.min_bio_spillage_penalty_type	---
hydro.target_storage	hm3
hydro.max_turbining	m3/s
hydro.max_turbining_penalty	k$/m3/s
hydro.max_turbining_penalty_type	---
hydro.min_turbining_penalty	k$/m3/s
hydro.min_turbining_penalty_type	---
hydro.spinning_reserve	%
hydro.max_reserve	MW

Interconnection

Data	Unit
interconnection.code	---
interconnection.state	---
interconnection.capacity_right	MW
interconnection.capacity_left	MW
interconnection.cost_right	$/MWh
interconnection.cost_left	$/MWh

Power Injection

Data	Unit
power_injection.code	---
power_injection.hour_capacity	MW
power_injection.hour_price	$/MWh

Renewable

Data	Unit
renewable.code	---
renewable.state	---
renewable.units	---
renewable.tech_type	---
renewable.capacity	MW
renewable.om_cost	$/MWh
renewable.hour_generation	pu
renewable.block_generation	pu
renewable.operation_factor	pu

Renewable Gauging Station

Data	Unit
renewable_gauging_station.code	---
renewable_gauging_station.hour_generation	pu
renewable_gauging_station.block_generation	pu
renewable_gauging_station.hour_historical_generation	pu

System

System

Data	Unit
system.code	---
system.load_level_length	---
system.hour_block_map	---
system.sensitivity	---

Thermal

Data	Unit
thermal.code	---
thermal.state	---
thermal.units	---
thermal.system	---
thermal.min_generation	MW
thermal.min_generation_available	MW
thermal.min_generation_constraint	MW
thermal.max_generation	MW
thermal.max_generation_available	MW
thermal.forced_outage_rate	%
thermal.historical_outage_factor	%
thermal.startup_cost	k$
thermal.om_cost	$/MWh
thermal.specific_consumption_segment_1	gal/MWh
thermal.specific_consumption_segment_2	gal/MWh
thermal.specific_consumption_segment_3	gal/MWh
thermal.fuel_transportation_cost	$/gal
thermal.operation_mode	---
thermal.forced_generation	MW
thermal.emission_coefficient	pu
thermal.ramp_up	MW/min
thermal.ramp_down	MW/min
thermal.min_uptime	hour
thermal.min_downtime	hour
thermal.max_startups	---
thermal.max_shutdowns	---
thermal.shutdown_cost	k$
thermal.alternative_fuel	---

Expressions

Unary Expressions

PSRIO provides four unary operators that only receive one expression and does not modify any dimension (stages, blocks, scenarios, or agents). The unary minus maps the data values to their additive inverses; the absolute value is the non-negative value of the data without regard to its sign; the round method rounds the data to the specified number of digits after the decimal separator; the convert method determines the unit of the data.

Operator	Syntax
Unary Minus	exp = -exp1
Absolute Value	exp = exp1:abs()
Round	exp = exp1:round(int)
Convert	exp = exp1:convert(string)
Fill	exp = exp1:fill(double)

Example

The example below takes the power flow in a circuit and calculates its absolute values.

circuit = Circuit();
cirflw = circuit:load("cirflw");

abs_cirflw = cirflw:abs();

Example

Here, we use the convert method to act over the generation data of a set of thermal plants given in GWh and convert it to MW.

thermal = Thermal();
thermal_gen = circuit:load("gerter");

converted_thermal_gen = thermal_gen:convert("MW");

Binary Expressions

PSRIO provides binary operators which can change attributes (stages, blocks, scenarios, and agents) depending on inputs. The first table presents the supported arithmetic operators.

Operator	Syntax
Addition	exp = exp1 + exp2
Subtraction	exp = exp1 - exp2
Multiplication	exp = exp1 * exp2
Right Division	exp = exp1 / exp2
Power	exp = exp1 ^ exp2

The second table defines the logical and comparison operators.

Operator	Syntax
Equal to	exp = exp1:eq(exp2)
Not Equal to	exp = exp1:ne(exp2)
Less-than	exp = exp1:lt(exp2)
Less-than-or-equals to	exp = exp1:le(exp2)
Greater-than	exp = exp1:gt(exp2)
Greater-than-or-equals to	exp = exp1:ge(exp2)
And	exp = exp1 & exp2
Or	exp = exp1 | exp2

The third table defines two element-wise max and min methods between the two data arguments.

Operator	Syntax
Maximum	exp = max(exp1, exp2)
Minimum	exp = min(exp1, exp2)

Here are some examples of binary expressions.

Example

Calculating the useful storage of a hydro plant:

hydro = Hydro();
useful_storage = hydro.max_storage - hydro.min_storage;

Example

Comparing the generation of a thermal plant with its maximum capacity:

thermal = Thermal();

thermal_gen = thermal:load("gerter");
thermal_cap = thermal:load("potter");

gen_gt_cap = thermal_gen:convert("MW"):gt(thermal_cap);

Note that, since the generation data is in GWh and the capacity in MW, a unit conversion is needed to compare them.

Example

Getting the highest total generated energy per type of plant:

thermal = Thermal();
hydro = Hydro();

gerter = thermal:load("gerter");
gerhid = hydro:load("gerhid");

total_gerter = gerter:aggregate_agents(BY_SUM(), "Total Thermal Gen");
total_gerhid = gerhid:aggregate_agents(BY_SUM(), "Total Hydro Gen");

max_generation =  max(total_gerter, total_gerhid);

Thermal and hydro generation are not directly compared. To compare them, we first need to aggregate the agents to obtain only one representative agent containing generation per block, scenario, and stage in each data set. Then, we can compare them.

All the above-mentioned binary expressions follow the same rules to define the resulting output's stages, scenarios, blocks, and agents.

Stages and Scenarios

If one expression has n stages, and the other has only 1, the result will have n stages. If the exp1 has n1 stages and exp2 has n2, the resulting expression will have n3 as the minimum number of stages between the two. In other words, n3 = min{n1, n2}. If both expressions have 1 stage, the result will naturally have also 1. The same rule is applied to the scenarios. The table below summarizes the explanation:

exp1	exp2	exp
1	1	1
n1	1	n1
1	n2	n2
n1	n2	min{n1,n2}

Block and Hours

The following table describes the blocks and hours rules. The only operation that is not allowed is mixing expressions that vary per block and hour.

exp1 or exp2	exp
none / none	none
block / none	block
block / block	block
hour / none	hour
hour / hour	hour
block / hour	❌

Ternary Expressions

The table below presents the ifelse. Likewise, the above-defined operators, the ifelse follow dataframe rules, doing element-wise operations. If the element of exp1 is true, exp2 is the result, otherwise, it is exp3.

Operator	Syntax
Conditional	exp = ifelse(exp1, exp2, exp3)

Example

In the example below, if the thermal generation is greater than zero, 1 is returned; otherwise, 0 is returned.

thermal = Thermal();

gerter = thermal:load("gerter");

gerter_gt_zero = ifelse(gerter:gt(0.0), 1, 0);

Unit Conversion

The units conversion follows the International System of Units (SI), based on the 2019 redefinition. The PSRIO will perform a multi-step process with all the expressions inputs, producing a conversion factor with the desired unit.

Operator	Syntax
Unit Conversion	exp = exp1:convert("unit")

Example

hydro = Hydro();
fprodt = hydro:load("fprodt");
    
pothid = min(hydro.max_turbining_outflow * fprodt, hydro.max_generation_available);

In this example we have two inputs with different units: hydro.max_turbining_outflow [m3/s] and fprodt [MW/(m3/s)]. The pothid output will be the multiplication: [m3/s] × [MW/(m3/s)] = 1.0 × [MW].

Example

renewable = Renewable();
gergnd = renewable:load("gergnd");
vergnd = renewable:load("vergnd");
    
captured_prices = (gergnd * vergnd) / (gergnd + vergnd);

The unit conversion output of Example 2 is ([GWh] × [GWh]) / ([GWh] + [GWh]) = 1.0 × [GWh]

Example

thermal = Thermal();
fuel = Fuel();
    
cinte1 = (thermal.specific_consumption_segment_1 * (thermal.transport_cost + fuel.cost) + thermal.om_cost);

The unit conversion output of Example 3 is [gal/MWh] × ([$/gal] + [$/gal]) + [$/MWh] = 1.0 × [$/MWh]

Example 4

hydro = Hydro();
volfin = hydro:load("volfin");
fprodtac = hydro:load("fprodtac");
    
eneemb = ((volfin - hydro.min_storage) * fprodtac):convert("GWh");

The unit conversion output of Example 4 is ([hm3] - [hm3]) × [MW/(m3/s)] = 0.27 × [GWh]

Dimensions

Aggregate Functions

When analyzing simulation outputs, we are often interested in finding one single value that represents a set. PSRIO provides a set of methods to accomplish this kind of task with a high level of abstraction, the [aggregate functions][aggregate-functions]. One can choose many forms of how the output values will be aggregated. The table below shows the options offered by PSRIO:

Aggregate Functions	Description
BY_SUM()	Sums the elements of a set
BY_AVERAGE()	Takes the average of the elements of a set
BY_MAX()	Selects the maximum value of a set
BY_MIN()	Selects the minimum value of a set
BY_CVAR_L(number)	Calculates the expected shortfall for the left-tail case with the specified probability in %
BY_CVAR_R(number)	Calculates the expected shortfall for the right-tail case with the specified probability in %
BY_PERCENTILE(number)	Returns the score associated with the specified percentile
BY_NTH_ELEMENT(number)	Takes the specified nth value of a set
BY_STDDEV()	Calculates standard deviation of a set
BY_FIRST_VALUE()	Takes the first value of a set
BY_LAST_VALUE()	Takes the last value of a set

The methods above are only specifying how the methods will execute the aggregations. The aggregation itself is carried out by other methods, which are described in the sections below.

Dimensions: Scenarios

Aggregate Scenarios

$$ \operatorname{exp}=\operatorname{exp1:aggregate\_scenarios}(\operatorname{f}); $$

Example

system = System();
cmgdem = system:load("cmgdem");
cmgdem_avg = cmgdem:aggregate_scenarios(BY_AVERAGE());
cmgdem_p90 = cmgdem:aggregate_scenarios(BY_PERCENTILE(90));

Aggregate Selected Scenarios

$$ \operatorname{exp}=\operatorname{exp1:aggregate\_scenarios}(\operatorname{f}, \{\operatorname{int}, \operatorname{int}, ...\}); $$

Example

system = System();
cmgdem = system:load("cmgdem");
cmgdem_max = cmgdem:aggregate_scenarios(BY_MAX(), {1, 2, 3, 4, 5});

Select One Scenario

$$ \operatorname{exp}=\operatorname{exp1:select\_scenario}(\operatorname{int}); $$

Example

system = System();
cmgdem = system:load("cmgdem");
cmgdem_scenario32 = cmgdem:select_scenario(32);

Select Multiple Scenarios

$$ \operatorname{exp}=\operatorname{exp1:select\_scenarios}(\{\operatorname{int}, \operatorname{int}, ...\}); $$

Remove Multiple Scenarios

$$ \operatorname{exp}=\operatorname{exp1:remove\_scenarios}(\{\operatorname{int}, \operatorname{int}, ...\}); $$

Dimensions: Blocks/Hours

Aggregate Blocks/Hours

$$ \operatorname{exp}=\operatorname{exp1:aggregate\_blocks}(\operatorname{f}); $$

Example

system = System();
cmgdem = system:load("cmgdem");
cmgdem_agg = cmgdem:aggregate_blocks(BY_AVERAGE());

renewable = Renewable();
gergnd = renewable:load("gergnd");
gergnd_agg = gergnd:aggregate_blocks(BY_SUM());

Select One Block/Hour

$$ \operatorname{exp}=\operatorname{exp1:select\_block}(\operatorname{int}); $$

Example

system = System();
cmgdem = system:load("cmgdem");
cmgdem_block21 = cmgdem:select_block(21);

Map Blocks into Hours

$$ \operatorname{exp}=\operatorname{exp1:to\_hour}(\operatorname{f}); $$

Where f is BY_AVERAGE() or BY_REPEATING().

Example

system = System();
cmgdem_block = thermal:load("cmgdem");
cmgdem_hourly = cmgdem_block:to_hour(BY_REPEATING());

Map Hours into Blocks

$$ \operatorname{exp}=\operatorname{exp1:to\_block}(\operatorname{f}); $$

Where f is BY_AVERAGE() or BY_SUM().

Example

thermal = Thermal();
gerter_hourly = thermal:load("gerter");
gerter_block = gerter_hourly:to_block(BY_SUM());

Dimensions: Stages

Aggregate Stages

$$ \operatorname{exp}=\operatorname{exp1:aggregate\_stages}(\operatorname{f}); $$

Aggregate Stages into a Profile

$$ \operatorname{exp}=\operatorname{exp1:aggregate\_stages}(\operatorname{f}, \operatorname{profile}); $$

Where profile is the following enumerate:

Profiles
Profile.STAGE
Profile.WEEK
Profile.MONTH
Profile.QUARTER
Profile.YEAR
Profile.PER_WEEK
Profile.PER_MONTH
Profile.PER_QUARTER
Profile.PER_YEAR

Profile.STAGE

The Profile.STAGE is the default value to characterize the aggregation if the user does not inform any profile. The data associated with each stage of the study horizon is aggregated.

exp1	exp (Profile.STAGE)
n (daily)	1 (daily)
n (weekly)	1 (weekly)
n (monthly)	1 (monthly)
n (yearly)	1 (yearly)

Profile.WEEK and Profile.PER_WEEK

When the data has a daily resolution and the aggregation profile is Profile.WEEK, PSRIO will aggregate the data for each day of the weeks in the study period, i.e., that data regarding all Mondays in the data set will be aggregated into one value and the same for Tuesday, Wednesday, and so on. With a daily resolution and the aggregation Profile.PER_WEEK, PSRIO will aggregate the data related to each week of the study.

When the data is weekly and we request is Profile.WEEK, the data associated with each week is aggregated in one week. If the request is the aggregation Profile.PER_WEEK, PSRIO will do nothing and the data will remains the same.

These aggregation profiles are not defined for monthly and yearly resolution data.

exp1	exp (Profile.WEEK)	exp (Profile.PER_WEEK)
n (daily)	7 (daily)	n/7 (weekly)
n (weekly)	1 (weekly)	n (weekly)
n (monthly)	❌	❌
n (yearly)	❌	❌

Example

system = System();
cmgdem = system:load("cmgdem");
cmgdem_agg = cmgdem:aggregate_blocks(BY_AVERAGE(), profile.WEEK);

Example

system = System();
cmgdem = system:load("cmgdem");
cmgdem_agg = cmgdem:aggregate_blocks(BY_AVERAGE(), profile.PER_WEEK);

Profile.MONTH and Profile.PER_MONTH

Similar to Profile.WEEK and Profile.PER_WEEK, when the data has daily discretization and we request Profile.MONTH, PSRIO will aggregate the data for each day of the months in the study period. For example, PSRIO will aggregate all 1^st days of each month and the same for the others months. If we request the Profile.PER_MONTH, PSRIO will aggregate the data related to each month.

When the data has month-level discretization and we request Profile.MONTH, PSRIO will aggregate the data associated with each month. If we request Profile.PER_MONTH, nothing is done to the data.

These aggregation profiles are not defined for weekly and yearly resolution data.

exp1	exp (Profile.MONTH)	exp (Profile.PER_MONTH)
n (daily)	31 (daily)	n/~30 (monthly)
n (weekly)	❌	❌
n (monthly)	1 (monthly)	n (monthly)
n (yearly)	❌	❌

Example

system = System();
cmgdem = system:load("cmgdem");
cmgdem_agg = cmgdem:aggregate_blocks(BY_AVERAGE(), profile.MONTH);

Example

system = System();
cmgdem = system:load("cmgdem");
cmgdem_agg = cmgdem:aggregate_blocks(BY_AVERAGE(), profile.PER_MONTH);

Profile.YEAR and Profile.PER_YEAR

When the data has a daily resolution and we request a Profile.YEAR, the data related to each day of years is aggregated. For example, PSRIO will aggregate all January 1^st days in the study period, which is done for the other days of the year. If we request a Profile.PER_YEAR, the data associated with each year is aggregated. The same happens when the data has week, month, or year-level resolution if Profile.PER_YEAR is selected.

If the data has a year resolution and profile.YEAR is selected. the data related to the same year is aggregated.

The profile.YEAR profile is not defined for weekly and monthly resolution data.

exp1	exp (Profile.YEAR)	exp (Profile.PER_YEAR)
n (daily)	365 (daily)	n/365 (yearly)
n (weekly)	52 (weekly)	n/52 (yearly)
n (monthly)	12 (monthly)	n/12 (yearly)
n (yearly)	1 (yearly)	1 (yearly)

Example

system = System();
defcit = system:load("defcit");
defcit_per_year = defcit:aggregate_stages(BY_SUM(), Profile.YEAR);

Example

system = System()
defcit = system:load("defcit")
defcit_per_year = defcit:aggregate_stages(BY_SUM(), Profile.PER_YEAR);

Select One Stage

$$ \operatorname{exp}=\operatorname{exp1:select\_stage}(\operatorname{int}); $$

generic = Generic();
objcop = generic:load("objcop");
objcop_1st_stage = objcop:select_stage(1);

Select the First Stage

$$ \operatorname{exp}=\operatorname{exp1:select\_first\_stage}(\operatorname{int}); $$

generic = Generic();
objcop = generic:load("objcop");
objcop_2nd_to_n_stage = objcop:select_first_stage(2);

Select the Last Stage

$$ \operatorname{exp}=\operatorname{exp1:select\_last\_stage}(\operatorname{int}); $$

generic = Generic();
objcop = generic:load("objcop");
objcop_1st_to_2nd_stage = objcop:select_last_stage(2);

Select the First and the Last Stages

$$ \operatorname{exp}=\operatorname{exp1:select\_stages}(\operatorname{int}, \operatorname{int}); $$

generic = Generic();
objcop = generic:load("objcop");
objcop_2nd_to_4th_stage = objcop:select_stages(2, 4);

Select Stages by a First and a Last Years

$$ \operatorname{exp}=\operatorname{exp1:select\_stages\_by\_year}(\operatorname{int}, \operatorname{int}); $$

generic = Generic();
objcop = generic:load("objcop");
objcop_2030_2040 = objcop:select_stages_by_year(2030, 2040);

Select Stages by a Year

$$ \operatorname{exp}=\operatorname{exp1:select\_stages\_by\_year}(\operatorname{int}); $$

generic = Generic();
objcop = generic:load("objcop");
objcop_2035 = objcop:select_stages_by_year(2035);

Reshape Stages

$$ \operatorname{exp}=\operatorname{exp1:reshape\_stages}(\operatorname{Profile.DAILY}); $$

For an hourly represented data, the stage resolution can changed from a week, month or year level to a daily one using that method

exp1	exp
n (daily-hourly)	n (daily-hourly)
n (weekly-hourly)	7n (daily-hourly)
n (monthly-hourly)	~30n (daily-hourly)
n (yearly-hourly)	365n (daily-hourly)

Example

thermal = Thermal();
gerter = thermal:load("gerter");
gerter_daily = gerter:reshape_stages(Profile.DAILY);

Dimensions: Agents

Aggregate All Agents

$$ \operatorname{exp}=\operatorname{exp1:aggregate\_agents}(\operatorname{f}, \operatorname{string}); $$

Example

hydro = Hydro();
gerhid = hydro:load("gerhid");
gerhid_sum = gerhid:aggregate_agents(BY_SUM(), "Total Hydro");

Aggregate Agents into Collection

$$ \operatorname{exp}=\operatorname{exp1:aggregate\_agents}(\operatorname{f}, \operatorname{collection}); $$

Where collection is Collection Enumerate.

Example

hydro = Hydro();
gerhid = hydro:load("gerhid");
gerhid_systems = gerhid:aggregate_agents(BY_SUM(), Collection.SYSTEM);
gerhid_buses = gerhid:aggregate_agents(BY_SUM(), Collection.BUSES);

Select One Agent by Name or Index

$$ \operatorname{exp}=\operatorname{exp1:select\_agent}(\text{string or int}); $$

Example

thermal = Thermal();
gerter = thermal:load("gerter");
gerter_t1 = gerter:select_agent("Thermal 1");
gerter_t2 = gerter:select_agent(2);

Select Mulitple Agents by Names or Indices

$$ \operatorname{exp}=\operatorname{exp1:select\_agents}(\{\text{string or int}, \text{string or int}, ...\}); $$

Example

thermal = Thermal();
gerter = thermal:load("gerter");
gerter_t1_and_t2 = gerter:select_agents({"Thermal 1", 2});

Select Agents within a Collection

$$ \operatorname{exp}=\operatorname{exp1:select\_agents}(\operatorname{collection}); $$

Where collection is Collection Enumerate.

Example

expansion_project = ExpansionProject()
outidec = expansion_project:load("outidec");
outidec_dclinks = outidec:select_agents(Collection.DCLINK);

Select Agents with a Query

$$ \operatorname{exp}=\operatorname{exp1:select\_agents}(\operatorname{string}); $$

Example

thermal = Thermal();
gerter = thermal:load("gerter");
non_zero_gerter = gerter:select_agents(gerter:ne(0));

Remove One Agent by Name or Index

$$ \operatorname{exp}=\operatorname{exp1:remove\_agent}(\text{string or int}); $$

Example

thermal = Thermal();
gerter = thermal:load("gerter");
gerter_t2_and_t3 = gerter:remove_agent("Thermal 1");
gerter_t1_and_t2 = gerter:remove_agent(3);

Remove Mulitple Agents by Names or Indices

$$ \operatorname{exp}=\operatorname{exp1:remove\_agents}(\{\text{string or int}, \text{string or int}, ...\}); $$

Example

thermal = Thermal();
gerter = thermal:load("gerter");
gerter_t1 = gerter:remove_agents({"Thermal 2", 3});

Rename One Agent

$$ \operatorname{exp}=\operatorname{exp1:rename\_agent}(\text{string}); $$

Rename Mulitple Agents with One Name

$$ \operatorname{exp}=\operatorname{exp1:rename\_agents}(\text{string}); $$

Rename Mulitple Agents with Mutiple Names

$$ \operatorname{exp}=\operatorname{exp1:rename\_agents}(\{\text{string}, \text{string}, ...\}); $$

Example

thermal = Thermal();
gerter = thermal:load("gerter");
gerter_renamed = gerter:rename_agents({"T1", "T2", "T3"});

Rename Mulitple Agents by Adding a Suffix

$$ \operatorname{exp}=\operatorname{exp1:add\_suffix}(\text{string}); $$

Rename Mulitple Agents by Adding a Prefix

$$ \operatorname{exp}=\operatorname{exp1:add\_prefix}(\text{string}); $$

Concatenate Agents

$$ \operatorname{exp}=\operatorname{concatenate}(\{\operatorname{exp1}, \operatorname{exp2}, ...\}); $$

Example 1

hydro = Hydro();
thermal = Thermal();
renewable = Renewable();

gerhid = hydro:load("gerhid");
gerter = thermal:load("gerter");
gergnd = renewable:load("gergnd");
generation = concatenate(gerhid, gerter, gergnd);

Dimensions: Others

Moving Function

$$ \operatorname{exp}=\operatorname{exp1:moving}(\operatorname{f}, \operatorname{int}); $$

Example

system = System();
cmgdem = system:load("cmgdem");
cmgdem_12months = cmgdem:moving(BY_AVERAGE(), 12);

Saving

Save Options

Description	Syntax	Default
Save output as BIN/HDR	bin	true
Save output as CSV	csv	false
Save output as DAT	dat	false

Save

$$ \operatorname{exp1:save}(\operatorname{string}); $$

Example

thermal = Thermal();
gerter = thermal:load("gerter");
gerter:save("example");

Save with Options

$$ \operatorname{exp1:save}(\operatorname{string}, \{\operatorname{options}\}); $$

Example

thermal = Thermal();
gerter = thermal:load("gerter");
gerter:save("example", { csv = true });

Save and Load into an Expression

$$ \operatorname{exp}=\operatorname{exp1:save\_and\_load}(\operatorname{string}); $$

Example

thermal = Thermal();
gerter = thermal:load("gerter");
example = gerter:save_and_load("example");

Save with Options and Load into an Expression

$$ \operatorname{exp}=\operatorname{exp1:save\_and\_load}(\operatorname{string}, \{\operatorname{options}\}); $$

Example

thermal = Thermal();
gerter = thermal:load("gerter");
example = gerter:save_and_load("example", { csv = true });

Save Cache

$$ \operatorname{exp}=\operatorname{exp1:save\_cache}(); $$

Example

thermal = Thermal();
gerter = thermal:load("gerter");
cache = gerter:save_cache();

Dashboard

PSRIO provides a set of methods that allow users to analyze their results simply and easily.

Create a Tab

$$ \operatorname{tab}=\operatorname{Tab}(\text{string}); $$

Example

tab = Tab("Tab title");

Set the Tab Icon

$$ \operatorname{tab:set\_icon}(\text{string}); $$

https://lucide.dev/

Example

tab = Tab("Tab title");
tab:set_icon("home");

Push a Chart to a Tab

$$ \operatorname{tab:push}(\text{chart}); $$

Example

tab = Tab("Tab title");
tab:push("home");

Push a Markdown to a Tab

$$ \operatorname{tab:push}(\text{string}); $$

Example

tab = Tab("Tab title");
tab:push("# Heading 1");

Push a Tab to a Tab

$$ \operatorname{tab:push}(\text{tab}); $$

Example

tab = Tab("Tab title");
subtab = Tab("Sub Tab title");
tab:push(subtab);

Save a Tab

$$ \operatorname{tab:save}(\text{string}); $$

Example

tab = Tab("Tab title");
tab:save("example");

Create a Dashboard

$$ \operatorname{dashboard}=\operatorname{Dashboard}(); $$

Example

dashboard = Dashboard();

Push a Tab to a Dashboard

$$ \operatorname{dashboard:push}(\operatorname{tab}); $$

Example

tab = Tab("Tab title");
dashboard = Dashboard();
dashboard:push(tab);

Save a Dashboard

$$ \operatorname{dashboard:save}(\text{string}); $$

Example

dashboard = Dashboard();
dashboard:save("example");

Charts

Charts are the essential elements of dashboards. They provide a visual way of analyzing the data generated by PSR models. To create a chart object, we should use one of the following methods:

Method	Syntax
Create a Chart	chart = Chart()
Create a Chart with a title	chart = Chart("title")
Create a Chart with a title and a subtitle	chart = Chart("title", "subtitle")

After creating the chart object, we can start to push the data in it. PSRIO gives multiple options for chart types, which can be seen below:

Method	Syntax
Line	chart:add_line(exp)
Spline	chart:add_spline(exp)
Column	chart:add_column(exp)
Column Stacking	chart:add_column_stacking(exp)
Column Percent	chart:add_column_percent(exp)
Categories	chart:add_categories(exp, "label")
Area	chart:add_area(exp)
Area Stacking	chart:add_area_stacking(exp)
Area Percent	chart:add_area_percent(exp)
Area Range	chart:add_area_range(exp1, exp2)
Area Spline	chart:add_area_spline(exp)
Area Spline Stacking	chart:add_area_spline_stacking(exp)
Area Spline Percent	chart:add_area_spline_percent(exp)
Area Spline Range	chart:add_area_spline_range(exp1, exp2)
Pie	chart:add_pie(exp)
Histogram	chart:add_histogram(exp)
Heatmap (Hourly)	chart:add_heatmap_hourly(exp)
Scatter	chart:add_scatter(exp1, exp2, "label")
Probability of Exceedance	chart:add_probability_of_exceedance(exp)

Examples

local thermal = Thermal();
local gerter = thermal:load("gerter");

local hydro = Hydro();
local gerhid = hydro:load("gerhid");

local renewable = Renewable();
local gergnd = renewable:load("gergnd");

local tab = Tab("Tutorial");

-- push charts to tab here --

tab:save("tutorial");

Example: Line

local chart = Chart("Line");
chart:add_line(gerter:aggregate_blocks(BY_SUM()):aggregate_scenarios(BY_AVERAGE()):select_largest_agents(5));
tab:push(chart);

Example: Spline

local chart = Chart("Spline");
chart:add_spline(gerter:aggregate_blocks(BY_SUM()):aggregate_scenarios(BY_AVERAGE()):select_largest_agents(5));
tab:push(chart);

Example: Column

local chart = Chart("Column");
chart:add_column(gerter:aggregate_blocks(BY_SUM()):aggregate_scenarios(BY_AVERAGE()):select_largest_agents(5));
tab:push(chart);

Example: Categories

local chart = Chart("Categories");
chart:add_categories(gerter:aggregate_blocks(BY_SUM()):aggregate_scenarios(BY_AVERAGE()):aggregate_agents(BY_SUM(), Collection.SYSTEM), "Thermal");
chart:add_categories(gerhid:aggregate_blocks(BY_SUM()):aggregate_scenarios(BY_AVERAGE()):aggregate_agents(BY_SUM(), Collection.SYSTEM), "Hydro");
chart:add_categories(gergnd:aggregate_blocks(BY_SUM()):aggregate_scenarios(BY_AVERAGE()):aggregate_agents(BY_SUM(), Collection.SYSTEM), "Renewable");
tab:push(chart);

Example: Column Stacking

local chart = Chart("Column Stacking");
chart:add_column(gerter:aggregate_blocks(BY_SUM()):aggregate_scenarios(BY_AVERAGE()):select_largest_agents(5));
tab:push(chart);

Example: Column Percent

local chart = Chart("Column Percent");
chart:add_column(gerter:aggregate_blocks(BY_SUM()):aggregate_scenarios(BY_AVERAGE()):select_largest_agents(5));
tab:push(chart);

Example: Area

local chart = Chart("Area");
chart:add_area(gerter:aggregate_blocks(BY_SUM()):aggregate_scenarios(BY_AVERAGE()):select_largest_agents(5));
tab:push(chart);

Example: Area Stacking

local chart = Chart("Area Stacking");
chart:add_area_stacking(gerter:aggregate_blocks(BY_SUM()):aggregate_scenarios(BY_AVERAGE()):select_largest_agents(5));
tab:push(chart);

Example: Area Percent

local chart = Chart("Area Percent");
chart:add_area_percent(gerter:aggregate_blocks(BY_SUM()):aggregate_scenarios(BY_AVERAGE()):select_largest_agents(5));
tab:push(chart);

Example: Area Range

local chart = Chart("Area Range");
chart:add_area_range(
    gerter:aggregate_blocks(BY_SUM()):aggregate_scenarios(BY_PERCENTILE(10)):aggregate_agents(BY_SUM(), "p10"),
    gerter:aggregate_blocks(BY_SUM()):aggregate_scenarios(BY_PERCENTILE(90)):aggregate_agents(BY_SUM(), "p90")
);
tab:push(chart);

Example: Area Spline

local chart = Chart("Area Spline");
chart:add_area_spline(gerter:aggregate_blocks(BY_SUM()):aggregate_scenarios(BY_AVERAGE()):select_largest_agents(5));
tab:push(chart);

Example: Area Spline Stacking

local chart = Chart("Area Spline Stacking");
chart:add_area_spline_stacking(gerter:aggregate_blocks(BY_SUM()):aggregate_scenarios(BY_AVERAGE()):select_largest_agents(5));
tab:push(chart);

Example: Area Spline Percent

local chart = Chart("Area Spline Percent");
chart:add_area_spline_percent(gerter:aggregate_blocks(BY_SUM()):aggregate_scenarios(BY_AVERAGE()):select_largest_agents(5));
tab:push(chart);

Example: Area Spline Range

local chart = Chart("Area Spline Range");
chart:add_area_spline_range(
    gerter:aggregate_blocks(BY_SUM()):aggregate_scenarios(BY_PERCENTILE(10)):aggregate_agents(BY_SUM(), "p10"),
    gerter:aggregate_blocks(BY_SUM()):aggregate_scenarios(BY_PERCENTILE(90)):aggregate_agents(BY_SUM(), "p90")
);
tab:push(chart);

Example: Pie

local chart = Chart("Pie");
chart:add_pie(gerter:aggregate_blocks(BY_SUM()):aggregate_scenarios(BY_AVERAGE()):aggregate_stages(BY_SUM()));
tab:push(chart);

Example: Histogram

local chart = Chart("Histogram");
chart:add_histogram(gerter:aggregate_blocks(BY_SUM()):aggregate_agents(BY_SUM(), "Total"));
tab:push(chart);

Example: Probability of Exceedance

local chart = Chart("Probability of Exceedance");
chart:add_probability_of_exceedance(gerter:aggregate_blocks(BY_SUM()));
tab:push(chart);

Example: Multiple (Line and Area Range)

local chart = Chart("Multiple (Line and Area Range)");
chart:add_area_range(
    gerter:aggregate_blocks(BY_SUM()):aggregate_scenarios(BY_PERCENTILE(10)):aggregate_agents(BY_SUM(), "p10"),
    gerter:aggregate_blocks(BY_SUM()):aggregate_scenarios(BY_PERCENTILE(90)):aggregate_agents(BY_SUM(), "p90")
);
chart:add_line(
    gerter:aggregate_blocks(BY_SUM()):aggregate_scenarios(BY_AVERAGE()):aggregate_agents(BY_SUM(), "avg")
);
tab:push(chart);

Example: Multiple (Line and Column)

local chart = Chart("Multiple (Line and Column)");
chart:add_column(gerter:aggregate_blocks(BY_SUM()):aggregate_scenarios(BY_AVERAGE()):aggregate_agents(BY_SUM(), "column"));
chart:add_line(gerter:aggregate_blocks(BY_SUM()):aggregate_scenarios(BY_AVERAGE()):aggregate_agents(BY_SUM(), "line"));
tab:push(chart);

Chart Attributes

Some methods accept arguments to customize your chart, i.e., change its color, define the limits on the y axis, etc.

The arguments are declared in tables inside the methods, as shown in the following example:
chart:add_line(exp, {lineWidth = 2}). The user can also define multiple arguments as follows chart:add_line(exp, {lineWidth = 2, color = "#8583ff"}). The following table describes the available chart arguments:

Argument	Description
color = ?	e.g. #ff0000 or red
lineWidth = ?	0, 1, 2, ...
marker = {enabled = ?}	true or false
marker = {symbol = ?}	circle, square, diamond, triangle or triangle-down
marker = {radius = ?}	0, 1, 2, ...
dataLabels = {enabled = ?}	true or false
dataLabels = {format = ?}	e.g. "{point.y:,.0f}"
xGridLineWidth = ?	0, 1, 2, ...
fillOpacity = ?	0.0 to 1.0
dashStyle = ?	solid, shortdash, shortdot, shortdashdot, shortdashdotdot, dot, dash, longdash, dashdot, longdashdot, and longdashdotdo
stops = { {?, ?}, ... }	e.g. stops = {{0.0, "#3060cf"}, {0.5, "#fffbbc"}, {0.9, '#c4463a"}}
showInLegend = ?	true or false

Examples

local system = System();
local cmgdem = system:load("cmgdem"):aggregate_scenarios(BY_AVERAGE());
local cmgdem_per_agent = cmgdem:aggregate_blocks(BY_AVERAGE());
local cmgdem_per_block = cmgdem:aggregate_agents(BY_SUM(), "Load Marginal Cost");
local cmgdem_aggregated = cmgdem:aggregate_blocks(BY_AVERAGE()):aggregate_agents(BY_SUM(), "Load Marginal Cost");

local tab = Tab("Tutorial");

-- push charts to tab here --

tab:save("tutorial");

Example: Single Color

local chart = Chart("Single Color");
chart:add_line(cmgdem_per_agent, {color = "#8583ff"});
tab:push(chart);

Example: Multiple Colors

local chart = Chart("Multiple Colors");
chart:add_line(cmgdem_per_agent, {color = {"#9b5de5", "#f15bb5", "#fee440", "#00bbf9", "#00f5d4"}});
tab:push(chart);

Example: Multiple Colors (interpolate)

local chart = Chart("Multiple Colors (interpolate)");
chart:add_line(cmgdem_per_agent, {color = PSR.interpolate_colors("#ff0000", "#00ff00", cmgdem_per_agent:agents_size())});
tab:push(chart);

Example: Line Width

local chart = Chart("Line Width");
chart:add_line(cmgdem_aggregated, {lineWidth = 8});
tab:push(chart);

Example: Marker

local chart = Chart("Marker");
chart:add_line(cmgdem_aggregated, {marker = {enabled = true, symbol = "circle", radius = 2}});
tab:push(chart);

Example: Data Labels

local chart = Chart("Data Labels");
chart:add_line(cmgdem_aggregated, {dataLabels = {enabled = true, format = "{point.y:,.0f}"} });
tab:push(chart);

Example: xGrid Line Width

local chart = Chart("xGrid Line Width");
chart:add_line(cmgdem_aggregated, {xGridLineWidth = 1});
tab:push(chart);

Example: Fill Opacity

local chart = Chart("Fill Opacity");
chart:add_area(cmgdem_aggregated, {fillOpacity = 1});
tab:push(chart);

Example: Dash Style

local chart = Chart("Dash Style");
chart:add_line(cmgdem_aggregated, {dashStyle = "dash"});
tab:push(chart);

Example: Show In Legend

local chart = Chart("Show In Legend");
chart:add_line(cmgdem_aggregated, {showInLegend = false});
tab:push(chart);

Markdown

https://docs.github.com/en/get-started/writing-on-github/getting-started-with-writing-and-formatting-on-github/basic-writing-and-formatting-syntax

Headers

# h1 Heading
## h2 Heading
### h3 Heading
#### h4 Heading
##### h5 Heading
###### h6 Heading

h1 Heading

h2 Heading

h3 Heading

h4 Heading

h5 Heading

h6 Heading

Horizontal Rules

___

---

***

---

---

---

Emphasis

*This text will be italic*
_This will also be italic_
**This text will be bold**
__This will also be bold__
*You **can** combine them*
~~This text will be strikethrough~~

This text will be italic
This will also be italic
This text will be bold
This will also be bold
You can combine them
This text will be strikethrough

Unordered List

+ Create a list by starting a line with `+`, `-`, or `*`
+ Sub-lists are made by indenting 2 spaces:
  - Marker character change forces new list start:
    * Ac tristique libero volutpat at
    + Facilisis in pretium nisl aliquet
    - Nulla volutpat aliquam velit
+ Very easy!

• Create a list by starting a line with +, -, or *
• Sub-lists are made by indenting 2 spaces:
  • Marker character change forces new list start:
    • Ac tristique libero volutpat at
    • Facilisis in pretium nisl aliquet
    • Nulla volutpat aliquam velit
• Very easy!

Ordered List

1. Item 1
2. Item 2
3. Item 3
    * Item 3a
    * Item 3b

1. Item 1
2. Item 2
3. Item 3
   • Item 3a
   • Item 3b

Links

[link text](http://psr-inc.com)

[link with tooltip](http://psr-inc.com/ "tooltip text!")

Autoconverted link http://psr-inc.com (enable linkify to see)

link text

link with tooltip

Autoconverted link http://psr-inc.com (enable linkify to see)

Blockquotes

> Blockquotes can also be nested...
>> ...by using additional greater-than signs right next to each other...
> > > ...or with spaces between arrows.

Blockquotes can also be nested...

...by using additional greater-than signs right next to each other...

...or with spaces between arrows.

Code

Inline `code`

    // Indented code
    line 1 of code
    line 2 of code
    line 3 of code

```
Block code
```

Inline code

// Indented code
line 1 of code
line 2 of code
line 3 of code

Block code

Tables

| Option | Description                                                               |
|--------|---------------------------------------------------------------------------|
| data   | path to data files to supply the data that will be passed into templates. |
| engine | engine to be used for processing templates. Handlebars is the default.    |
| ext    | extension to be used for dest files.                                      |

Option	Description
data	path to data files to supply the data that will be passed into templates.
engine	engine to be used for processing templates. Handlebars is the default.
ext	extension to be used for dest files.

Images

![Minion](https://octodex.github.com/images/minion.png)

![Stormtroopocat](https://octodex.github.com/images/stormtroopocat.jpg "The Stormtroopocat")

![Alt text][id]

[id]: https://octodex.github.com/images/dojocat.jpg  "The Dojocat"

Equations

https://katex.org/docs/supported.html

dashboard:push("$$ x^2 + y^2 = z^2 $$");

$$ x^2 + y^2 = z^2 $$

dashboard:push("$$ \sqrt{x^2+1} $$");

$$ \sqrt{x^2+1} $$

dashboard:push("$$ \int\limits_0^1 x^2 + y^2 dx $$");

$$ \int\limits_0^1 x^2 + y^2 dx $$

dashboard:push("$$ \int_0^1 x^2 + y^2 dx $$");

$$ \int_0^1 x^2 + y^2 dx $$

dashboard:push("$$ a_1^2 + a_2^2 = a_3^2 $$");

$$ a_1^2 + a_2^2 = a_3^2 $$

dashboard:push("$$ \sum_{i=1}^{\infty} \frac{1}{n^s} = \prod_p \frac{1}{1 - p^{-s}} $$");

$$ \sum_{i=1}^{\infty} \frac{1}{n^s} = \prod_p \frac{1}{1 - p^{-s}} $$

dashboard:push("$$ \begin{matrix} a & b \\\\ c & d \end{matrix} $$");

$$ \begin{matrix} a & b \\ c & d \end{matrix} $$

Base

PSRIO Base is a library embedded with PSRIO that provides implementations of PSR model outputs. Instead of rewriting recipes or searching for written similar scripts, we can use the functions provided by PSRIO Base. We use the function require to load the scripts defined in the PSRIO Base.

Example: Useful Storage

(https://github.com/psrenergy/psrio-base/blob/master/sddp/useful_storage.lua):set_icon

useful_storage = require("sddp/useful_storage");
useful_storage():save("useful_storage");

Example: Circuit Loading

sddp/usecir:

usecir = require("sddp/usecir");
usecir():save("usecir");

Example: Hydro Generation per Bus

sddp/gerhid_per_bus:

gerhid_per_bus = require("sddp/gerhid_per_bus");
gerhid_per_bus():save("gerhid_per_bus");

Example: Deficit Risk per Year

sddp/defcit_risk:

defcit_risk = require("sddp/defcit_risk");
defcit_risk():save("defcit_risk");

Example: Load Marginal Cost Report

sddp-reports/sddpcmgd:

sddpcmgd = require("sddp-reports/sddpcmgd");
sddpcmgd():save("sddpcmgd");

Example: Averaged Load Marginal Cost Report

sddp-reports/sddpcmga:

sddpcmga = require("sddp-reports/sddpcmga");
sddpcmga():save("sddpcmga");