diff --git a/dev/.documenter-siteinfo.json b/dev/.documenter-siteinfo.json index 049d32b..cc43db1 100644 --- a/dev/.documenter-siteinfo.json +++ b/dev/.documenter-siteinfo.json @@ -1 +1 @@ -{"documenter":{"julia_version":"1.6.7","generation_timestamp":"2024-03-12T00:47:00","documenter_version":"1.3.0"}} \ No newline at end of file +{"documenter":{"julia_version":"1.6.7","generation_timestamp":"2024-03-12T01:14:32","documenter_version":"1.3.0"}} \ No newline at end of file diff --git a/dev/GTEP/index.html b/dev/GTEP/index.html index e9d7460..061833d 100644 --- a/dev/GTEP/index.html +++ b/dev/GTEP/index.html @@ -17,4 +17,4 @@ \end{aligned}\]

(27) Cap & Trade - State carbon allowance cap:

\[\sum_{g \in (\bigcup_{i \in I_{w}} G_{i}) \cap G^{F}} a+{g,t} - em_{w}^{emis} \le ALW_{t,w}; w \in W, t \in T\]

(28) Cap & Trade - Balance between allowances and emissions:

\[N_{t} \sum_{h \in H_{t}} EF_{g} \times p_{g,t,h} = a_{g,t} + b_{g,t-1} = b_{g,t}; g \in (\bigcup_{i \in I_{w}} G_{i}) \cap G_{F}, w \in W, t \in T\]

(29) Cap & Trade - No cross-year banking:

\[b_{g,1} = b_{g,end} = 0; g \in G_{F}\]

(30) Binary variables:

\[x_{g} = \{0,1 \}; \forall g \in G_{+} y_{l} = \{0,1 \}; \forall l \in L_{+} z_{s} = \{0,1 \}; \forall s \in S_{+}\]

(31) Nonnegative variable:

\[a_{g,t}, b_{g,t}, p_{g,t,h}, p_{d,t,h}^{LS}, c_{s,t,h}, soc_{s,t,h}, pt^{rps}, pw_{g,w}, pwi_{g,w,w'}, em^{emis} \\ -\ge 0\]

+\ge 0\]

diff --git a/dev/GTEP_inputs/index.html b/dev/GTEP_inputs/index.html index d0b7b9d..aac49ee 100644 --- a/dev/GTEP_inputs/index.html +++ b/dev/GTEP_inputs/index.html @@ -1,2 +1,2 @@ -GTEP Inputs · HOPE.jl
GitHub

GTEP Inputs Explanation

The input files for the HOPE model could be one big .XLSX file or multiple .csv files. If you use the XLSX file, each spreadsheet in the file needs to be prepared based on the input instructions below and the spreadsheet names should be carefully checked. If you use the csv files, each csv file will represent one spreadsheet from the XLSX file. If both XLSX file and csv files are provided, the XLSX files will be used.

zonedata

This is the input dataset for zone-relevant information (e.g., demand, mapping with state, etc.).

Column NameDescription
Zone_idName of each zone (should be unique)
Demand (MW)Peak demand of the zone in MW
StateThe state that the zone is belonging to
AreaThe area that the zone is belonging to
Flag_MD1 if the zone belongs to a desired state (e.g., Maryland), and 0 otherwise

gendata

This is the input dataset for existing generators.

Column NameDescription
Pmax (MW)Maximum generation (nameplate) capacity of the generator in MW
Pmin (MW)Minimum generation (nameplate) capacity of the generator in MW
ZoneThe zone that the generator is belonging to
TypeThe technology type of the generator
Cost (/MWh)Operating cost of the generator in /MWh
EFThe CO2 emission factor for the generator in tons/MWh
CCThe capacity credit for the generator (it is the fraction of the installed/nameplate capacity of a generator that can be relied upon at a given time)

gendata_candidate

This is the input dataset for candidate generators (a set of all generators that can be selected for installation).

Column NameDescription
Pmax (MW)Maximum generation (nameplate) capacity of the generator in MW
Pmin (MW)Minimum generation (nameplate) capacity of the generator in MW
ZoneThe zone that the generator is belonging to
TypeThe technology type of the generator
Cost (M$)Investment cost for the generator in million dollars (M$)
Cost (/MWh)Operating cost of the generator in /MWh
EFThe CO2 emission factor for the generator in tons/MWh
CCThe capacity credit for the generator (it is the fraction of the installed/nameplate capacity of a generator that can be relied upon at a given time)

linedata

This is the input dataset for existing transmission lines (e.g., transmission capacity limit for each inter-zonal transmission line).

Column NameDescription
From_zoneStarting zone of the inter-zonal transmission line
From_zoneEnding zone of the inter-zonal transmission line
Capacity (MW)Transmission capacity limit for the transmission line

linedata_candidate

This is the input dataset for candidate transmission lines (a set of all inter-zonal lines that can be selected for installation).

Column NameDescription
From_zoneStarting zone of the inter-zonal transmission line
From_zoneEnding zone of the inter-zonal transmission line
Capacity (MW)Transmission capacity limit for the transmission line
Cost (M$)Investment cost for the generator in million dollars (M$)
XReactance of the line in P.U. (optional)

storagedata

This is the input dataset for existing energy storage units (e.g., battery storage and pumped storage hydropower).

Column NameDescription
ZoneThe zone that the generator is belonging to
TypeThe technology type of the generator
Capacity (MWh)Maximun energy capacity of the storage in MWh
Max Power (MW)Maximum energy rate (power capacity) of the storage in MW
Charging efficiencyRatio of how much energy is transferred from the charger to the storage unit
Discharging efficiencyRatio of how much energy is transferred from the storage unit to the charger
Cost (/MWh)Operating cost of the generator in /MWh
EFThe CO2 emission factor for the generator in tons/MWh
CCThe capacity credit for the generator (it is the fraction of the installed/nameplate capacity of a generator that can be relied upon at a given time)
Charging RateThe maximum rates of charging, unitless
Discharging RateThe maximum rates of discharging, unitless

storagedata_candidate

This is the input dataset for candidate energy storage units (a set of all storage units that can be selected for installation).

Column NameDescription
ZoneThe zone that the storage is belonging to
TypeThe technology type of the generator
Capacity (MWh)Maximun energy capacity of the storage in MWh
Max Power (MW)Maximum energy rate (power capacity) of the storage in MW
Charging efficiencyRatio of how much energy is transferred from the charger to the storage unit
Discharging efficiencyRatio of how much energy is transferred from the storage unit to the charger
Cost (M$)Investment cost for the new storage in million dollars (M$)
Cost (/MWh)Operating cost of the generator in /MWh
EFThe CO2 emission factor for the generator in tons/MWh
CCThe capacity credit for the generator (it is the fraction of the installed/nameplate capacity of a generator that can be relied upon at a given time)
Charging RateThe maximum rates of charging, unitless
Discharging RateThe maximum rates of discharging, unitless

solartimeseriesregional

This is the input dataset for the annual hourly solar PV generation profile in each zone. Each zone has 8760 data points and the values are per unit.

Column NameDescription
MonthMonths of the year, ranging from 1 to 12
DayDays of the month, ranging from 1 to 31
PeriodHours of the day, ranging from 1 to 24
Zone 1Solar power generation data in zone 1 on a specific period, day, and month
Zone 2Solar power generation data in zone 2 on a specific period, day, and month
......

windtimeseriesregional

This is the input dataset for the annual hourly wind generation profile in each zone. Each zone has 8760 data points and the values are per unit.

Column NameDescription
MonthMonths of the year, ranging from 1 to 12
DayDays of the month, ranging from 1 to 31
PeriodHours of the day, ranging from 1 to 24
Zone 1Wind power generation data in zone 1 on a specific period, day, and month
Zone 2Wind power generation data in zone 2 on a specific period, day, and month
......

loadtimeseriesregional

This is the input dataset for the annual hourly load profile in each zone. Each zone has 8760 data points and the values are per unit.

Column NameDescription
MonthMonths of the year, ranging from 1 to 12
DayDays of the month, ranging from 1 to 31
PeriodHours of the day, ranging from 1 to 24
Zone 1Load data in zone 1 on a specific period, day, and month
Zone 2Load data in zone 2 on a specific period, day, and month
......
NINet load import on a specific period, day, and month

carbonpolicies

This is the input dataset for carbon policies.

Column NameDescription
StateName of the state
Time PeriodTime periods for carbon allowance (can be yearly or quarterly, set by users)
Allowance (tons)Carbon emission allowance for each state in tons

rpspolicies

This is the input dataset for renewable portfolio standard (RPS) policies. It defines renewable credits trading relationship between different states (i.e., the states must be neighboring states) and the renewable credit requirement for each state.

Column NameDescription
From_stateState that trading the renewable credits from
To_stateState that trading the renewable credits to
RPSRPS requirement (renewable generation percentage) for the state in "From_state" column, range from 0-1, unitless
+GTEP Inputs · HOPE.jl
GitHub

GTEP Inputs Explanation

The input files for the HOPE model could be one big .XLSX file or multiple .csv files. If you use the XLSX file, each spreadsheet in the file needs to be prepared based on the input instructions below and the spreadsheet names should be carefully checked. If you use the csv files, each csv file will represent one spreadsheet from the XLSX file. If both XLSX file and csv files are provided, the XLSX files will be used.

zonedata

This is the input dataset for zone-relevant information (e.g., demand, mapping with state, etc.).

Column NameDescription
Zone_idName of each zone (should be unique)
Demand (MW)Peak demand of the zone in MW
StateThe state that the zone is belonging to
AreaThe area that the zone is belonging to
Flag_MD1 if the zone belongs to a desired state (e.g., Maryland), and 0 otherwise

gendata

This is the input dataset for existing generators.

Column NameDescription
Pmax (MW)Maximum generation (nameplate) capacity of the generator in MW
Pmin (MW)Minimum generation (nameplate) capacity of the generator in MW
ZoneThe zone that the generator is belonging to
TypeThe technology type of the generator
Cost (/MWh)Operating cost of the generator in /MWh
EFThe CO2 emission factor for the generator in tons/MWh
CCThe capacity credit for the generator (it is the fraction of the installed/nameplate capacity of a generator that can be relied upon at a given time)

gendata_candidate

This is the input dataset for candidate generators (a set of all generators that can be selected for installation).

Column NameDescription
Pmax (MW)Maximum generation (nameplate) capacity of the generator in MW
Pmin (MW)Minimum generation (nameplate) capacity of the generator in MW
ZoneThe zone that the generator is belonging to
TypeThe technology type of the generator
Cost (M$)Investment cost for the generator in million dollars (M$)
Cost (/MWh)Operating cost of the generator in /MWh
EFThe CO2 emission factor for the generator in tons/MWh
CCThe capacity credit for the generator (it is the fraction of the installed/nameplate capacity of a generator that can be relied upon at a given time)

linedata

This is the input dataset for existing transmission lines (e.g., transmission capacity limit for each inter-zonal transmission line).

Column NameDescription
From_zoneStarting zone of the inter-zonal transmission line
From_zoneEnding zone of the inter-zonal transmission line
Capacity (MW)Transmission capacity limit for the transmission line

linedata_candidate

This is the input dataset for candidate transmission lines (a set of all inter-zonal lines that can be selected for installation).

Column NameDescription
From_zoneStarting zone of the inter-zonal transmission line
From_zoneEnding zone of the inter-zonal transmission line
Capacity (MW)Transmission capacity limit for the transmission line
Cost (M$)Investment cost for the generator in million dollars (M$)
XReactance of the line in P.U. (optional)

storagedata

This is the input dataset for existing energy storage units (e.g., battery storage and pumped storage hydropower).

Column NameDescription
ZoneThe zone that the generator is belonging to
TypeThe technology type of the generator
Capacity (MWh)Maximun energy capacity of the storage in MWh
Max Power (MW)Maximum energy rate (power capacity) of the storage in MW
Charging efficiencyRatio of how much energy is transferred from the charger to the storage unit
Discharging efficiencyRatio of how much energy is transferred from the storage unit to the charger
Cost (/MWh)Operating cost of the generator in /MWh
EFThe CO2 emission factor for the generator in tons/MWh
CCThe capacity credit for the generator (it is the fraction of the installed/nameplate capacity of a generator that can be relied upon at a given time)
Charging RateThe maximum rates of charging, unitless
Discharging RateThe maximum rates of discharging, unitless

storagedata_candidate

This is the input dataset for candidate energy storage units (a set of all storage units that can be selected for installation).

Column NameDescription
ZoneThe zone that the storage is belonging to
TypeThe technology type of the generator
Capacity (MWh)Maximun energy capacity of the storage in MWh
Max Power (MW)Maximum energy rate (power capacity) of the storage in MW
Charging efficiencyRatio of how much energy is transferred from the charger to the storage unit
Discharging efficiencyRatio of how much energy is transferred from the storage unit to the charger
Cost (M$)Investment cost for the new storage in million dollars (M$)
Cost (/MWh)Operating cost of the generator in /MWh
EFThe CO2 emission factor for the generator in tons/MWh
CCThe capacity credit for the generator (it is the fraction of the installed/nameplate capacity of a generator that can be relied upon at a given time)
Charging RateThe maximum rates of charging, unitless
Discharging RateThe maximum rates of discharging, unitless

solartimeseriesregional

This is the input dataset for the annual hourly solar PV generation profile in each zone. Each zone has 8760 data points and the values are per unit.

Column NameDescription
MonthMonths of the year, ranging from 1 to 12
DayDays of the month, ranging from 1 to 31
PeriodHours of the day, ranging from 1 to 24
Zone 1Solar power generation data in zone 1 on a specific period, day, and month
Zone 2Solar power generation data in zone 2 on a specific period, day, and month
......

windtimeseriesregional

This is the input dataset for the annual hourly wind generation profile in each zone. Each zone has 8760 data points and the values are per unit.

Column NameDescription
MonthMonths of the year, ranging from 1 to 12
DayDays of the month, ranging from 1 to 31
PeriodHours of the day, ranging from 1 to 24
Zone 1Wind power generation data in zone 1 on a specific period, day, and month
Zone 2Wind power generation data in zone 2 on a specific period, day, and month
......

loadtimeseriesregional

This is the input dataset for the annual hourly load profile in each zone. Each zone has 8760 data points and the values are per unit.

Column NameDescription
MonthMonths of the year, ranging from 1 to 12
DayDays of the month, ranging from 1 to 31
PeriodHours of the day, ranging from 1 to 24
Zone 1Load data in zone 1 on a specific period, day, and month
Zone 2Load data in zone 2 on a specific period, day, and month
......
NINet load import on a specific period, day, and month

carbonpolicies

This is the input dataset for carbon policies.

Column NameDescription
StateName of the state
Time PeriodTime periods for carbon allowance (can be yearly or quarterly, set by users)
Allowance (tons)Carbon emission allowance for each state in tons

rpspolicies

This is the input dataset for renewable portfolio standard (RPS) policies. It defines renewable credits trading relationship between different states (i.e., the states must be neighboring states) and the renewable credit requirement for each state.

Column NameDescription
From_stateState that trading the renewable credits from
To_stateState that trading the renewable credits to
RPSRPS requirement (renewable generation percentage) for the state in "From_state" column, range from 0-1, unitless
diff --git a/dev/PCM/index.html b/dev/PCM/index.html index 48050fc..0452885 100644 --- a/dev/PCM/index.html +++ b/dev/PCM/index.html @@ -14,4 +14,4 @@ \ge \sum_{i \in I_{w},h \in H} \sum_{d \in D_{i}} p_{d,h} \times RPS_{w};\\ w \in W \end{aligned}\]

(18) Cap & Trade - State carbon allowance cap:

\[\sum_{g \in (\bigcup_{i \in I_{w}} G_{i}) \cap G^{F}} a+{g,t} - \sum_{t \in T} N_{t} em_{w,h}^{emis} \le ALW_{t,w}; w \in W\]

(19) Cap & Trade - Balance between allowances and emissions:

\[\sum_{h \in H} EF_{g} \times p_{g,h} = a_{g,t} + b_{g,t-1} = b_{g,t}; g \in (\bigcup_{i \in I_{w}} G_{i}) \cap G_{F}, w \in W, t \in T\]

(20) Cap & Trade - No cross-year banking:

\[b_{g,1} = b_{g,end} = 0; g \in G_{F}\]

(21) Nonnegative variable:

\[a_{g,t}, b_{g,t}, p_{g,h}, p_{d,h}^{LS}, c_{s,h}, soc_{s,h}, pt^{rps}, pw_{g,w}, pwi_{g,w,w'}, em^{emis} \\ -\ge 0\]

+\ge 0\]

diff --git a/dev/PCM_inputs/index.html b/dev/PCM_inputs/index.html index 8dfadaf..50a5c23 100644 --- a/dev/PCM_inputs/index.html +++ b/dev/PCM_inputs/index.html @@ -1,2 +1,2 @@ -PCM Inputs · HOPE.jl
GitHub

PCM Inputs Explanation

The input files for the HOPE model could be one big .XLSX file or multiple .csv files. If you use the XLSX file, each spreadsheet in the file needs to be prepared based on the input instructions below and the spreadsheet names should be carefully checked. If you use the csv files, each csv file will represent one spreadsheet from the XLSX file. If both XLSX file and csv files are provided, the XLSX files will be used.

zonedata

This is the input dataset for zone-relevant information (e.g., demand, mapping with state, etc.).

Column NameDescription
Zone_idName of each zone (should be unique)
Demand (MW)Peak demand of the zone in MW
StateThe state that the zone is belonging to
AreaThe area that the zone is belonging to
Flag_MD1 if the zone belongs to a desired state (e.g., Maryland), and 0 otherwise

gendata

This is the input dataset for existing generators.

Column NameDescription
Pmax (MW)Maximum generation (nameplate) capacity of the generator in MW
Pmin (MW)Minimum generation (nameplate) capacity of the generator in MW
ZoneThe zone that the generator is belonging to
TypeThe technology type of the generator
Cost (/MWh)Operating cost of the generator in /MWh
EFThe CO2 emission factor for the generator in tons/MWh
CCThe capacity credit for the generator (it is the fraction of the installed/nameplate capacity of a generator that can be relied upon at a given time)

linedata

This is the input dataset for existing transmission lines (e.g., transmission capacity limit for each inter-zonal transmission line).

Column NameDescription
From_zoneStarting zone of the inter-zonal transmission line
From_zoneEnding zone of the inter-zonal transmission line
Capacity (MW)Transmission capacity limit for the transmission line

storagedata

This is the input dataset for existing energy storage units (e.g., battery storage and pumped storage hydropower).

Column NameDescription
ZoneThe zone that the generator is belonging to
TypeThe technology type of the generator
Capacity (MWh)Maximun energy capacity of the storage in MWh
Max Power (MW)Maximum energy rate (power capacity) of the storage in MW
Charging efficiencyRatio of how much energy is transferred from the charger to the storage unit
Discharging efficiencyRatio of how much energy is transferred from the storage unit to the charger
Cost (/MWh)Operating cost of the generator in /MWh
EFThe CO2 emission factor for the generator in tons/MWh
CCThe capacity credit for the generator (it is the fraction of the installed/nameplate capacity of a generator that can be relied upon at a given time)
Charging RateThe maximum rates of charging, unitless
Discharging RateThe maximum rates of discharging, unitless

solartimeseriesregional

This is the input dataset for the annual hourly solar PV generation profile in each zone. Each zone has 8760 data points and the values are per unit.

Column NameDescription
MonthMonths of the year, ranging from 1 to 12
DayDays of the month, ranging from 1 to 31
PeriodHours of the day, ranging from 1 to 24
Zone 1Solar power generation data in zone 1 on a specific period, day, and month
Zone 2Solar power generation data in zone 2 on a specific period, day, and month
......

windtimeseriesregional

This is the input dataset for the annual hourly wind generation profile in each zone. Each zone has 8760 data points and the values are per unit.

Column NameDescription
MonthMonths of the year, ranging from 1 to 12
DayDays of the month, ranging from 1 to 31
PeriodHours of the day, ranging from 1 to 24
Zone 1Wind power generation data in zone 1 on a specific period, day, and month
Zone 2Wind power generation data in zone 2 on a specific period, day, and month
......

loadtimeseriesregional

This is the input dataset for the annual hourly load profile in each zone. Each zone has 8760 data points and the values are per unit.

Column NameDescription
MonthMonths of the year, ranging from 1 to 12
DayDays of the month, ranging from 1 to 31
PeriodHours of the day, ranging from 1 to 24
Zone 1Load data in zone 1 on a specific period, day, and month
Zone 2Load data in zone 2 on a specific period, day, and month
......
NINet load import on a specific period, day, and month

carbonpolicies

This is the input dataset for carbon policies.

Column NameDescription
StateName of the state
Time PeriodTime periods for carbon allowance (can be yearly or quarterly, set by users)
Allowance (tons)Carbon emission allowance for each state in tons

rpspolicies

This is the input dataset for renewable portfolio standard (RPS) policies. It defines renewable credits trading relationship between different states (i.e., the states must be neighboring states) and the renewable credit requirement for each state.

Column NameDescription
From_stateState that trading the renewable credits from
To_stateState that trading the renewable credits to
RPSRPS requirement (renewable generation percentage) for the state in "From_state" column, range from 0-1, unitless
+PCM Inputs · HOPE.jl
GitHub

PCM Inputs Explanation

The input files for the HOPE model could be one big .XLSX file or multiple .csv files. If you use the XLSX file, each spreadsheet in the file needs to be prepared based on the input instructions below and the spreadsheet names should be carefully checked. If you use the csv files, each csv file will represent one spreadsheet from the XLSX file. If both XLSX file and csv files are provided, the XLSX files will be used.

zonedata

This is the input dataset for zone-relevant information (e.g., demand, mapping with state, etc.).

Column NameDescription
Zone_idName of each zone (should be unique)
Demand (MW)Peak demand of the zone in MW
StateThe state that the zone is belonging to
AreaThe area that the zone is belonging to
Flag_MD1 if the zone belongs to a desired state (e.g., Maryland), and 0 otherwise

gendata

This is the input dataset for existing generators.

Column NameDescription
Pmax (MW)Maximum generation (nameplate) capacity of the generator in MW
Pmin (MW)Minimum generation (nameplate) capacity of the generator in MW
ZoneThe zone that the generator is belonging to
TypeThe technology type of the generator
Cost (/MWh)Operating cost of the generator in /MWh
EFThe CO2 emission factor for the generator in tons/MWh
CCThe capacity credit for the generator (it is the fraction of the installed/nameplate capacity of a generator that can be relied upon at a given time)

linedata

This is the input dataset for existing transmission lines (e.g., transmission capacity limit for each inter-zonal transmission line).

Column NameDescription
From_zoneStarting zone of the inter-zonal transmission line
From_zoneEnding zone of the inter-zonal transmission line
Capacity (MW)Transmission capacity limit for the transmission line

storagedata

This is the input dataset for existing energy storage units (e.g., battery storage and pumped storage hydropower).

Column NameDescription
ZoneThe zone that the generator is belonging to
TypeThe technology type of the generator
Capacity (MWh)Maximun energy capacity of the storage in MWh
Max Power (MW)Maximum energy rate (power capacity) of the storage in MW
Charging efficiencyRatio of how much energy is transferred from the charger to the storage unit
Discharging efficiencyRatio of how much energy is transferred from the storage unit to the charger
Cost (/MWh)Operating cost of the generator in /MWh
EFThe CO2 emission factor for the generator in tons/MWh
CCThe capacity credit for the generator (it is the fraction of the installed/nameplate capacity of a generator that can be relied upon at a given time)
Charging RateThe maximum rates of charging, unitless
Discharging RateThe maximum rates of discharging, unitless

solartimeseriesregional

This is the input dataset for the annual hourly solar PV generation profile in each zone. Each zone has 8760 data points and the values are per unit.

Column NameDescription
MonthMonths of the year, ranging from 1 to 12
DayDays of the month, ranging from 1 to 31
PeriodHours of the day, ranging from 1 to 24
Zone 1Solar power generation data in zone 1 on a specific period, day, and month
Zone 2Solar power generation data in zone 2 on a specific period, day, and month
......

windtimeseriesregional

This is the input dataset for the annual hourly wind generation profile in each zone. Each zone has 8760 data points and the values are per unit.

Column NameDescription
MonthMonths of the year, ranging from 1 to 12
DayDays of the month, ranging from 1 to 31
PeriodHours of the day, ranging from 1 to 24
Zone 1Wind power generation data in zone 1 on a specific period, day, and month
Zone 2Wind power generation data in zone 2 on a specific period, day, and month
......

loadtimeseriesregional

This is the input dataset for the annual hourly load profile in each zone. Each zone has 8760 data points and the values are per unit.

Column NameDescription
MonthMonths of the year, ranging from 1 to 12
DayDays of the month, ranging from 1 to 31
PeriodHours of the day, ranging from 1 to 24
Zone 1Load data in zone 1 on a specific period, day, and month
Zone 2Load data in zone 2 on a specific period, day, and month
......
NINet load import on a specific period, day, and month

carbonpolicies

This is the input dataset for carbon policies.

Column NameDescription
StateName of the state
Time PeriodTime periods for carbon allowance (can be yearly or quarterly, set by users)
Allowance (tons)Carbon emission allowance for each state in tons

rpspolicies

This is the input dataset for renewable portfolio standard (RPS) policies. It defines renewable credits trading relationship between different states (i.e., the states must be neighboring states) and the renewable credit requirement for each state.

Column NameDescription
From_stateState that trading the renewable credits from
To_stateState that trading the renewable credits to
RPSRPS requirement (renewable generation percentage) for the state in "From_state" column, range from 0-1, unitless
diff --git a/dev/hope_model_settings/index.html b/dev/hope_model_settings/index.html index f2d723b..6839e35 100644 --- a/dev/hope_model_settings/index.html +++ b/dev/hope_model_settings/index.html @@ -1,2 +1,2 @@ -HOPE Settings · HOPE.jl
GitHub

HOPE Model Settings Explanation

The Hope_model_settings.yml file configures system-level settings for running a HOPE case, including scenario settings (folder names), model mode settings, technology aggregation or not, using representative day or 8760 hourly time steps, integer or continuous for decision investment decisions, periods for setting representative days, planning reserve margin, value of loss of load, solver, debug flag, etc.

There are two columns: 1) the first column contains the names of setting parameters; 2) the second column contains the setting values. The explanation for setting parameters is also provided in the Hope_model_settings.yml file.

Parameter NameParameter Value (examples)Description
DataCase:Data_100RPS/#String, the folder name of data, default Data/ GTEP example: Data_100RPS/; PCM example: Data_PCM2035/
model_mode:GTEP#String, HOPE model mode: GTEP or PCM or ...
aggregated!:1#Binary, 1 aggregate technology resource; 0 Does Not
representative_day!:1#Binary, 1 use representative days (need to set time_periods); 0 Does Not
inv_dcs_bin:0#Binary, 1 use integer variable for investment decisions; 0 Does Not
time_periods:1 : (3, 20, 6, 20) <br> 2 : (6, 21, 9, 21) <br> 3 : (9, 22, 12, 20) <br> 4 : (12, 21, 3, 19)# 1: spring, March 20th to June 20th; <br> # 2: summer, June 21st to September 21st; <br> # 3: fall, September 22nd to December 20th; <br> # 4: winter, December 21st to March 19th.
planning_reserve_margin:0.02#Float, planningreservemargin
value_of_loss_of_load:100000#Float, value of loss of load d, /MWh
solver:cbc#String, solver: cbc, glpk, cplex, gurobi, etc.
debug:0#Binary, flag for turning on the Method of Debug, 0 = not active; 1 = active conflict method (works for gurobi and cplex); 2 = active penalty method
+HOPE Settings · HOPE.jl
GitHub

HOPE Model Settings Explanation

The Hope_model_settings.yml file configures system-level settings for running a HOPE case, including scenario settings (folder names), model mode settings, technology aggregation or not, using representative day or 8760 hourly time steps, integer or continuous for decision investment decisions, periods for setting representative days, planning reserve margin, value of loss of load, solver, debug flag, etc.

There are two columns: 1) the first column contains the names of setting parameters; 2) the second column contains the setting values. The explanation for setting parameters is also provided in the Hope_model_settings.yml file.

Parameter NameParameter Value (examples)Description
DataCase:Data_100RPS/#String, the folder name of data, default Data/ GTEP example: Data_100RPS/; PCM example: Data_PCM2035/
model_mode:GTEP#String, HOPE model mode: GTEP or PCM or ...
aggregated!:1#Binary, 1 aggregate technology resource; 0 Does Not
representative_day!:1#Binary, 1 use representative days (need to set time_periods); 0 Does Not
inv_dcs_bin:0#Binary, 1 use integer variable for investment decisions; 0 Does Not
time_periods:1 : (3, 20, 6, 20) <br> 2 : (6, 21, 9, 21) <br> 3 : (9, 22, 12, 20) <br> 4 : (12, 21, 3, 19)# 1: spring, March 20th to June 20th; <br> # 2: summer, June 21st to September 21st; <br> # 3: fall, September 22nd to December 20th; <br> # 4: winter, December 21st to March 19th.
planning_reserve_margin:0.02#Float, planningreservemargin
value_of_loss_of_load:100000#Float, value of loss of load d, /MWh
solver:cbc#String, solver: cbc, glpk, cplex, gurobi, etc.
debug:0#Binary, flag for turning on the Method of Debug, 0 = not active; 1 = active conflict method (works for gurobi and cplex); 2 = active penalty method
diff --git a/dev/index.html b/dev/index.html index 5775667..97e47b6 100644 --- a/dev/index.html +++ b/dev/index.html @@ -1,2 +1,2 @@ -Introduction · HOPE.jl
GitHub

HOPE Documentation

Overview

The Holistic Optimization Program for Electricity (HOPE) model is a transparent and open-source tool for evaluating electric sector transition pathways and policy scenarios regarding power system planning, system operation, optimal power flow, and market designs. It is a highly configurable and modulized tool coded in the Julia language and optimization package JuMP. The HOPE consists of multiple modes for modeling optimization problems of modern power systems and electricity markets, including:

  1. GTEP mode: a generation & transmission expansion planning model
  2. PCM mode: a production cost model
  3. OPF mode: (under development): an optimal power flow model
  4. DART mode: (under development): a bilevel market model for simulating day-head and real-time markets

Users can select the proper mode of HOPE based on their research needs. Each mode is modeled as linear or mixed-integer linear programming and can be solved with open-source (e.g., Cbc, GLPK, Clp, etc.) or commercial (e.g., Groubi and CPLEX) solver packages.

Contributors

The HOPE model was originally developed by a team of researchers in Prof. Benjamin F. Hobbs's group at Johns Hopkins University. The main developers of the current HOPE version include Dr. Shen Wang, Dr. Mahdi Mehrtash, and Zoe Song.

+Introduction · HOPE.jl
GitHub

HOPE Documentation

Overview

The Holistic Optimization Program for Electricity (HOPE) model is a transparent and open-source tool for evaluating electric sector transition pathways and policy scenarios regarding power system planning, system operation, optimal power flow, and market designs. It is a highly configurable and modulized tool coded in the Julia language and optimization package JuMP. The HOPE consists of multiple modes for modeling optimization problems of modern power systems and electricity markets, including:

  1. GTEP mode: a generation & transmission expansion planning model
  2. PCM mode: a production cost model
  3. OPF mode: (under development): an optimal power flow model
  4. DART mode: (under development): a bilevel market model for simulating day-head and real-time markets

Users can select the proper mode of HOPE based on their research needs. Each mode is modeled as linear or mixed-integer linear programming and can be solved with open-source (e.g., Cbc, GLPK, Clp, etc.) or commercial (e.g., Groubi and CPLEX) solver packages.

Contributors

The HOPE model was originally developed by a team of researchers in Prof. Benjamin F. Hobbs's group at Johns Hopkins University. The main developers of the current HOPE version include Dr. Shen Wang, Dr. Mahdi Mehrtash, and Zoe Song.

diff --git a/dev/installation/index.html b/dev/installation/index.html index afefbef..cad5cda 100644 --- a/dev/installation/index.html +++ b/dev/installation/index.html @@ -1,2 +1,2 @@ -Installation · HOPE.jl
GitHub

Installation

1. Install Julia

Install Julia language. A short video tutorial on how to download and install Julia is provided here.

2. Download HOPE repository

Clone or download the HOPE repository to your local directory - click the green "Code" button on the HOPE main page and choose "Download ZIP" (remember to change the folder name to HOPE after you decompress the zip file). You need to save the HOPE project in your home directory like: /yourpath/home/HOPE. image

3. Solver Packages

The open-source solver packages (e.g., Cbc, GLPK, Clp, etc.) will be automatically installed in step 2. While the commercial solver packages (e.g., Groubi and CPLEX) should be installed by users (if needed) by following their instructions. 

pkg> add https://github.com/swang22/HOPE.jl
+Installation · HOPE.jl
GitHub

Installation

1. Install Julia

Install Julia language. A short video tutorial on how to download and install Julia is provided here.

2. Download HOPE repository

Clone or download the HOPE repository to your local directory - click the green "Code" button on the HOPE main page and choose "Download ZIP" (remember to change the folder name to HOPE after you decompress the zip file). You need to save the HOPE project in your home directory like: /yourpath/home/HOPE. image

3. Solver Packages

The open-source solver packages (e.g., Cbc, GLPK, Clp, etc.) will be automatically installed in step 2. While the commercial solver packages (e.g., Groubi and CPLEX) should be installed by users (if needed) by following their instructions. 

pkg> add https://github.com/swang22/HOPE.jl
diff --git a/dev/model_introduction/index.html b/dev/model_introduction/index.html index d8942c6..b3a9a8a 100644 --- a/dev/model_introduction/index.html +++ b/dev/model_introduction/index.html @@ -1,2 +1,2 @@ -Model Introduction · HOPE.jl
GitHub

Model Overview

The HOPE consists of multiple modes for modeling optimization problems of modern power systems and electricity markets, including:

  1. GTEP mode: a generation & transmission expansion planning model
  2. PCM mode: a production cost model
  3. OPF mode: (under development): an optimal power flow model
  4. DART mode: (under development): a bilevel market model for simulating day-head and real-time markets
+Model Introduction · HOPE.jl
GitHub

Model Overview

The HOPE consists of multiple modes for modeling optimization problems of modern power systems and electricity markets, including:

  1. GTEP mode: a generation & transmission expansion planning model
  2. PCM mode: a production cost model
  3. OPF mode: (under development): an optimal power flow model
  4. DART mode: (under development): a bilevel market model for simulating day-head and real-time markets
diff --git a/dev/notation/index.html b/dev/notation/index.html index 6dc8376..4f7c041 100644 --- a/dev/notation/index.html +++ b/dev/notation/index.html @@ -1,2 +1,2 @@ -Notation · HOPE.jl
GitHub

Nomenclature

Sets and Indices

NotationDescription
$D$Set of demand, index $d$
$G$Set of all types of generating units, index $g$
$H$Set of hours, index $h$
$K$Set of technology types, index $k$
$T$Set of time periods (e.g., representative days of seasons), index $t$
$S$Set of storage units, index $s$
$I,J$Set of zones, index $i,j$
$L$Set of transmission corridors, index $l$
$W$Set of states, index $w/w’$

Subsets

NotationDescription
$D_{i}$Set of demand connected to zone $i$, a subset of $D$
$G^{PV}$, $G^{W}$, $G^{F}$Set of solar, wind, and dispatchable generators, respectively, subsets of $G$
$G^{RPS}$Set of generators could provide RPS credits, subsets of $G$
$G^{L}_{l}$Set of generators linked to line $i$, subset of $G$
$G_{i}$Set of generating units connected to zone $i$, subset of $G$
$G^{E}/G^{+}$Set of existing/candidate generation units, index $g$, subset of $G$
$H_{t}$Set of hours in time period (day) $t$, index $h$, subset of $H$
$S^{E}/S^{+}$Set of existing/candidate storage units, subset of $S$
$S_{i}$Set of storage units connected to zone $i$, subset of $S$
$L^{E}/L^{+}$Set of existing/candidate transmission corridors
$LS_{l}/LR_{l}$Set of sending/receiving corridors for zone $i$, subset of $L$
$WIR_{w}$Set of states that state w can import renewable credits from (includes $w$ itself), subset of $W$
$WER_{w}$Set of states that state w can export renewable credits to (excludes $w$ itself), subset of $W$

Parameters

NotationDescription
$ALW_{t,w}$Total carbon allowance in time period $t$ in state $w$, ton
$AFRE_{g,h,i}$Availability factor of renewable energy source $g$ in hour $h$ in zone $i$, $g \in G^{PV} \bigcup G^{W}$
$CC_{g/s}$Capacity credit of resource $g/s$, unitless
$CP_{g}$Carbon price of generation $g \in\ G^{F}$, M/t
$EF_{g}$Carbon emission factor of generator $g$, t/MWh
$ELMT_{w}$Carbon emission limits at state $w, t$
$F^{max}_{l}$Maximum capacity of transmission corridor/line $l$, MW
$\tilde{I}_{g}$Investment cost of candidate generator $g$, M$
$\tilde{I}_{l}$Investment cost of transmission line $l$, M$
$\tilde{I}_{s}$Investment cost of storage unit $s$, M$
$IBG$Total investment budget for generators
$IBL$Total investment budget for transmission lines
$IBS$Total investment budget for storages
$N_{t}$Number of time periods (days) represented by time period (day) $t$ per year, /sum{t /in T} N{t}
$NI_{i.h}$Net interchange in zone $i$ in hour $h, MWh
$P_{d,h}$Active power demand, MW
$PK$Peak power demand, MW
$PT^{rps}$RPS volitation penalty, /MWh
$PT^{emis}$Carbon emission volitation penalty, /t
$P_{g}^{min}/P_{g}^{max}$Minimum/Maximum power generation of unit $g$, MW
$RPS_{w}$Renewable portfolio standard in state $w$, %, unitless
$RM$Planning reserve margin, unitless
$SCAP_{s}$Maximum capacity of storage unit $s$, MW
$SECAP_{s}$Maximum energy capacity of storage unit $s$, MWh
$SC_{s}/SD_{s}$The maximum rates of charging/discharging, unitless
$VCG_{g}$Variable cost of generation unit $g$, / MWh
$VCS_{g}$Variable (degradation) cost of storage unit $s$, / MWh
$VOLL_{d}$Value of loss of load $d$, /MWh
$\epsilon_{ch}$Charging efficiency of storage unit $s$, unitless
$\epsilon_{dis}$Discharging efficiency of storage unit $s$, unitless

Variables

NotationDescription
$a_{g,t}$Bidding carbon allowance of unit $g$ in time period $t$, ton
$b_{g,t}$Banking of allowance of g in time period $t$, ton
$p_{g,t,h}$Active power generation of unit $g$ in time period $t$ hour $h$, MW
$pw_{g,w}$Total renewable generation of unit $g$ in state $w$, MWh
$p^{LS}_{d,t,h}$Load shedding of demand $d$ in time period $t$ in hour $h$, MW
$pt^{rps}_{w}$Amount of active power violated RPS policy in state $w$, MW
$pwi_{g,w,w'}$State $w$ imported renewable credits of from state $w'$ annually, MWh
$f_{l,t,h}$Active power of generator $g$ through transmission corridor/line $l$ in time period $t$ and hour $h$, MW
$em^{emis}_{w}$Carbon emission violated emission limit in state $w$, ton
$x_{g}$Decision variable for candidate generator $g$, binary
$y_{l}$Decision variable for candidate line $l$, binary
$z_{s}$Decision variable for candidate storage $s$, binary
$soc_{s,t,h}$State of charge level of storage $s$ in time period $t$ in hour $h$, MWh
$c_{s,t,h}$Charging power of storage $s$ from grid in time period $t$ in hour $h$, MW
$dc_{s,t,h}$Discharging power of storage $s$ from grid in time period $t$ in hour $h$, MW
+Notation · HOPE.jl
GitHub

Nomenclature

Sets and Indices

NotationDescription
$D$Set of demand, index $d$
$G$Set of all types of generating units, index $g$
$H$Set of hours, index $h$
$K$Set of technology types, index $k$
$T$Set of time periods (e.g., representative days of seasons), index $t$
$S$Set of storage units, index $s$
$I,J$Set of zones, index $i,j$
$L$Set of transmission corridors, index $l$
$W$Set of states, index $w/w’$

Subsets

NotationDescription
$D_{i}$Set of demand connected to zone $i$, a subset of $D$
$G^{PV}$, $G^{W}$, $G^{F}$Set of solar, wind, and dispatchable generators, respectively, subsets of $G$
$G^{RPS}$Set of generators could provide RPS credits, subsets of $G$
$G^{L}_{l}$Set of generators linked to line $i$, subset of $G$
$G_{i}$Set of generating units connected to zone $i$, subset of $G$
$G^{E}/G^{+}$Set of existing/candidate generation units, index $g$, subset of $G$
$H_{t}$Set of hours in time period (day) $t$, index $h$, subset of $H$
$S^{E}/S^{+}$Set of existing/candidate storage units, subset of $S$
$S_{i}$Set of storage units connected to zone $i$, subset of $S$
$L^{E}/L^{+}$Set of existing/candidate transmission corridors
$LS_{l}/LR_{l}$Set of sending/receiving corridors for zone $i$, subset of $L$
$WIR_{w}$Set of states that state w can import renewable credits from (includes $w$ itself), subset of $W$
$WER_{w}$Set of states that state w can export renewable credits to (excludes $w$ itself), subset of $W$

Parameters

NotationDescription
$ALW_{t,w}$Total carbon allowance in time period $t$ in state $w$, ton
$AFRE_{g,h,i}$Availability factor of renewable energy source $g$ in hour $h$ in zone $i$, $g \in G^{PV} \bigcup G^{W}$
$CC_{g/s}$Capacity credit of resource $g/s$, unitless
$CP_{g}$Carbon price of generation $g \in\ G^{F}$, M/t
$EF_{g}$Carbon emission factor of generator $g$, t/MWh
$ELMT_{w}$Carbon emission limits at state $w, t$
$F^{max}_{l}$Maximum capacity of transmission corridor/line $l$, MW
$\tilde{I}_{g}$Investment cost of candidate generator $g$, M$
$\tilde{I}_{l}$Investment cost of transmission line $l$, M$
$\tilde{I}_{s}$Investment cost of storage unit $s$, M$
$IBG$Total investment budget for generators
$IBL$Total investment budget for transmission lines
$IBS$Total investment budget for storages
$N_{t}$Number of time periods (days) represented by time period (day) $t$ per year, /sum{t /in T} N{t}
$NI_{i.h}$Net interchange in zone $i$ in hour $h, MWh
$P_{d,h}$Active power demand, MW
$PK$Peak power demand, MW
$PT^{rps}$RPS volitation penalty, /MWh
$PT^{emis}$Carbon emission volitation penalty, /t
$P_{g}^{min}/P_{g}^{max}$Minimum/Maximum power generation of unit $g$, MW
$RPS_{w}$Renewable portfolio standard in state $w$, %, unitless
$RM$Planning reserve margin, unitless
$SCAP_{s}$Maximum capacity of storage unit $s$, MW
$SECAP_{s}$Maximum energy capacity of storage unit $s$, MWh
$SC_{s}/SD_{s}$The maximum rates of charging/discharging, unitless
$VCG_{g}$Variable cost of generation unit $g$, / MWh
$VCS_{g}$Variable (degradation) cost of storage unit $s$, / MWh
$VOLL_{d}$Value of loss of load $d$, /MWh
$\epsilon_{ch}$Charging efficiency of storage unit $s$, unitless
$\epsilon_{dis}$Discharging efficiency of storage unit $s$, unitless

Variables

NotationDescription
$a_{g,t}$Bidding carbon allowance of unit $g$ in time period $t$, ton
$b_{g,t}$Banking of allowance of g in time period $t$, ton
$p_{g,t,h}$Active power generation of unit $g$ in time period $t$ hour $h$, MW
$pw_{g,w}$Total renewable generation of unit $g$ in state $w$, MWh
$p^{LS}_{d,t,h}$Load shedding of demand $d$ in time period $t$ in hour $h$, MW
$pt^{rps}_{w}$Amount of active power violated RPS policy in state $w$, MW
$pwi_{g,w,w'}$State $w$ imported renewable credits of from state $w'$ annually, MWh
$f_{l,t,h}$Active power of generator $g$ through transmission corridor/line $l$ in time period $t$ and hour $h$, MW
$em^{emis}_{w}$Carbon emission violated emission limit in state $w$, ton
$x_{g}$Decision variable for candidate generator $g$, binary
$y_{l}$Decision variable for candidate line $l$, binary
$z_{s}$Decision variable for candidate storage $s$, binary
$soc_{s,t,h}$State of charge level of storage $s$ in time period $t$ in hour $h$, MWh
$c_{s,t,h}$Charging power of storage $s$ from grid in time period $t$ in hour $h$, MW
$dc_{s,t,h}$Discharging power of storage $s$ from grid in time period $t$ in hour $h$, MW
diff --git a/dev/reference/index.html b/dev/reference/index.html index 272aa75..7bc8896 100644 --- a/dev/reference/index.html +++ b/dev/reference/index.html @@ -1,2 +1,2 @@ -- · HOPE.jl
GitHub
    +- · HOPE.jl
    GitHub
      diff --git a/dev/run_case/index.html b/dev/run_case/index.html index 2026693..080aa60 100644 --- a/dev/run_case/index.html +++ b/dev/run_case/index.html @@ -1,2 +1,2 @@ -Run a case · HOPE.jl
      GitHub

      Run a Case in HOPE

      Using VScode to Run a Case (Recommended)

      Install Visual Studio Code: Download VScode and install it. A short video tutorial on how to install VScode and add Julia to it can be found here.

      (1) Open the VScode, click the 'File' tab, select 'Open Folder...', and navigate to your home working directory:/yourpath/home (The home directory in the examples below is named Maryland-Electric-Sector-Transition).

      (2) In the VScode TERMINAL, type Julia and press the "Enter" button. Julia will be opened as below:

      image

      (3) Type ] into the Julia package mode, and type activate HOPE (if you are in your home directory) or activate yourpath/home/HOPE (if you are not in your home directory), you will see prompt (@v1.8) pkg> changing to (HOPE) pkg>, which means the HOPE project is activated successfully.

      image

      (4) Type instantiate in the (HOPE) pkg prompt (make sure you are in your home directory, not the home/HOPE directory!).

      (5) Type st to check that the dependencies (packages that HOPE needs) have been installed. Type up to update the version of dependencies (packages). (This step may take some time when you install HOPE for the first time. After the HOPE is successfully installed, you can skip this step)

      image

      (6) If there is no error in the above processes, the HOPE model has been successfully installed! Then, press Backspace button to return to the Juila prompt. To run an example case (e.g., default Maryland 2035 case in PCM mode), type using HOPE, and type HOPE.run_hope("HOPE/ModelCases/MD_Excel_case/"), you will see the HOPE is running:

      image

      The results will be saved in yourpath/home/HOPE/ModelCases/MD_Excel_case/output.

      image

      (7) For your future new runs, you can skip steps 4 and 5, and just follow steps 1, 2, 3, 6.

      Using System Terminal to Run a Case

      You can use a system terminal either with a "Windows system" or a "Mac system" to run a test case. See details below.

      Windows users

      (1) Open Command Prompt from Windows Start and navigate to your home path:/yourpath/home.

      (2) Type julia. Julia will be opened as below:

      image

      (3) Type ] into the Julia package mode, and type activate HOPE (if you are in your home directory), you will see prompt (@v1.8) pkg> changing to (HOPE) pkg>, which means the HOPE project is activated successfully.

      (4) Type instantiate in the (HOPE) pkg prompt. ( After the HOPE is successfully installed, you can skip this step)

      (5) Type st to check that the dependencies (packages that HOPE needs) have been installed. Type up to update the version of dependencies (packages). (This step may take some time when you install HOPE for the first time. After the HOPE is successfully installed, you can skip this step)

      image

      (6) If there is no error in the above processes, the HOPE model has been successfully installed. Then, click Backspace to return to the Juila prompt. To run an example case (e.g., default Maryland 2035 case in PCM mode), type using HOPE, and type HOPE.run_hope("HOPE/ModelCases/MD_Excel_case/"), you will see the HOPE is running:

      image

      The results will be saved in yourpath/home/HOPE/ModelCases/MD_Excel_case/output.

      image

      (7) For your future new runs, you can skip steps 4 and 5, and just follow steps 1, 2, 3, 6.

      +Run a case · HOPE.jl
      GitHub

      Run a Case in HOPE

      Using VScode to Run a Case (Recommended)

      Install Visual Studio Code: Download VScode and install it. A short video tutorial on how to install VScode and add Julia to it can be found here.

      (1) Open the VScode, click the 'File' tab, select 'Open Folder...', and navigate to your home working directory:/yourpath/home (The home directory in the examples below is named Maryland-Electric-Sector-Transition).

      (2) In the VScode TERMINAL, type Julia and press the "Enter" button. Julia will be opened as below:

      image

      (3) Type ] into the Julia package mode, and type activate HOPE (if you are in your home directory) or activate yourpath/home/HOPE (if you are not in your home directory), you will see prompt (@v1.8) pkg> changing to (HOPE) pkg>, which means the HOPE project is activated successfully.

      image

      (4) Type instantiate in the (HOPE) pkg prompt (make sure you are in your home directory, not the home/HOPE directory!).

      (5) Type st to check that the dependencies (packages that HOPE needs) have been installed. Type up to update the version of dependencies (packages). (This step may take some time when you install HOPE for the first time. After the HOPE is successfully installed, you can skip this step)

      image

      (6) If there is no error in the above processes, the HOPE model has been successfully installed! Then, press Backspace button to return to the Juila prompt. To run an example case (e.g., default Maryland 2035 case in PCM mode), type using HOPE, and type HOPE.run_hope("HOPE/ModelCases/MD_Excel_case/"), you will see the HOPE is running:

      image

      The results will be saved in yourpath/home/HOPE/ModelCases/MD_Excel_case/output.

      image

      (7) For your future new runs, you can skip steps 4 and 5, and just follow steps 1, 2, 3, 6.

      Using System Terminal to Run a Case

      You can use a system terminal either with a "Windows system" or a "Mac system" to run a test case. See details below.

      Windows users

      (1) Open Command Prompt from Windows Start and navigate to your home path:/yourpath/home.

      (2) Type julia. Julia will be opened as below:

      image

      (3) Type ] into the Julia package mode, and type activate HOPE (if you are in your home directory), you will see prompt (@v1.8) pkg> changing to (HOPE) pkg>, which means the HOPE project is activated successfully.

      (4) Type instantiate in the (HOPE) pkg prompt. ( After the HOPE is successfully installed, you can skip this step)

      (5) Type st to check that the dependencies (packages that HOPE needs) have been installed. Type up to update the version of dependencies (packages). (This step may take some time when you install HOPE for the first time. After the HOPE is successfully installed, you can skip this step)

      image

      (6) If there is no error in the above processes, the HOPE model has been successfully installed. Then, click Backspace to return to the Juila prompt. To run an example case (e.g., default Maryland 2035 case in PCM mode), type using HOPE, and type HOPE.run_hope("HOPE/ModelCases/MD_Excel_case/"), you will see the HOPE is running:

      image

      The results will be saved in yourpath/home/HOPE/ModelCases/MD_Excel_case/output.

      image

      (7) For your future new runs, you can skip steps 4 and 5, and just follow steps 1, 2, 3, 6.

      diff --git a/dev/solver_settings/index.html b/dev/solver_settings/index.html index 22dca21..b71505f 100644 --- a/dev/solver_settings/index.html +++ b/dev/solver_settings/index.html @@ -1,2 +1,2 @@ -Solver Settings · HOPE.jl
      GitHub

      Solver Settings Explanation

      The HOPE model can use multiple solvers to solve optimization problems. The solver parameters are saved in the following yml files: cbc_settings.yml, clp_settings.yml, cplex_settings.yml, gurobi_settings.yml, highs_settings.yml, scip_settings.yml, etc. In general, users do not need to modify these files. Each solver may have its own different settings parameters, if one wants to modify these parameters, it would be better to check the corresponding solver's documentation.

      +Solver Settings · HOPE.jl
      GitHub

      Solver Settings Explanation

      The HOPE model can use multiple solvers to solve optimization problems. The solver parameters are saved in the following yml files: cbc_settings.yml, clp_settings.yml, cplex_settings.yml, gurobi_settings.yml, highs_settings.yml, scip_settings.yml, etc. In general, users do not need to modify these files. Each solver may have its own different settings parameters, if one wants to modify these parameters, it would be better to check the corresponding solver's documentation.