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Models and results of transactive energy-based control to stabilize oscillations in integrated wholesale-retail energy markets

The resources under this data set represent models and results of work done under Control of Complex Systems Initiative (CCSI) to demonstrate the transactive energy-based control capabilities to stabilize and reduce oscillations that might occur when other control mechanisms are used.

Power system transmission (wholesale energy market) and distribution (retail energy market) components, and their simulators (MATPOWER and GridLAB-D) are integrated in the Framework for Network Co-Simulation (FNCS) in order to study.

Data and Resources

FieldValue
Modified
2018-07-18
Release Date
2018-03-29
Identifier
c8dbb977-c86d-4d92-b838-7d004ff94c99
License
License Not Specified
Author
Jacob Hansen
Data Dictionary

Each resource archive has a certain folder hierarchy explained below.

inputFiles folder contains the input files necessary for the GridLAB-D simulations of the feeders

models folder contains the transmission and distribution networks models, in MATPOWER (.m) and GridLAB-D (.glm) formats, respectively.

The transmission system model used for this study is a modified version of a 240-node Western Electricity Coordination Council (WECC) Interconnect model originally produced by CAISO (case_WECC240_line_limits_updated_v3.m). The model aggregates hourly load into twenty-two zones and provides constant distribution factors that segments that load to each of the nodes in that zone. Generators are also aggregated to each bus with a single generator for a given fuel type representing all those being aggregated. This results in some buses having multiple generators, one for each fuel type. Hydro generation was scaled back to 20\% of the installed capacity and treated as low-cost dispatchable generation. The model is described in MATPOWER format under models/transmission folder, together with 2 text files containing typical load profiles.

A set of 24 typical North American distribution circuit models has been defined for GridLAB-D. These circuits are generalized from models supplied by utilities around the country and have region-based customization in terms of circuit scale and topology, load composition, and environment. Nine circuits were selected that span the three regions of interest when simulating the Western Interconnect:
- climateRegion1 - West Coast of the United States; characterized by a temperate climate,
- climateRegion2 - North Central and North Eastern portions of the United States; characterized by a cold climate,
- climateRegion3 - non-coastal South West of the United States; characterized by a hot and arid climate.

For each climate region there are 3 types of feeders, differentiated by the served area, population, types of consumers, etc.

To identify a specific feeder in the model and result data, this naming convention should be considered:
R<region number>12_47<feeder type number>feeder<feeder number>

results folder contains the results files specific to each scenario.
Transmission-side results. <\results\transmission>
For all 3 scenarios the following are collected in JSON-format files:
- generator data <generator_data.json>:
- GEN_BUS - generator bus number
- GEN_STATUS - generator status, that is, either "in-service" (value > 0) or "out-of-service" (value <= 0)
- LMP_P - active power/real location marginal price (LMP) [$/MW]
- LMP_Q - reactive power LMP [$/MVar]
- PG - currently generated active power [MW]
- QG - currently generated reactive power [MVar]
- load data <load_data.json>:
- LMP_P - active power LMP [$/MW]
- LMP_Q - reactive power LMP [$/MVar]
- PD - real power demand [MW]
- PQ - reactive power demand [MVar]
- Vang - voltage angle [degrees]
- Vmag - voltage magnitude [p.u.]
- Vmax - maximum voltage magnitude [p.u.]
- Vmin - minimum voltage magnitude [p.u.]
- dispatchable load data <dispatchableLoad.json>: treated as negative generation, and hence, having the same fields as in generator data.

Distribution-side results. <\results\distribution\climateRegion#\feederType#>
Structured based on region climate location and type, the feeders' results are saved as:
- for all 3 cases:
- individual consumption of residential HVACs over time, per feeder per climate region [KW]<\residentialHVACloads\R#12_47#feeder#resHVACloads.csv>
- currents [A], voltages [V] and power [W] at the head of each feeder per climate region <R#_12_47
#feeder#headData.csv>
- extra data for case with no feedback:
- individual HVAC bid price [$/MW] over time <\residentialHVACCtrlBidPrice\R#_12_47
#feeder#ctrlBidPrice.csv>
- individual HVAC bid quantity [W] over time <\residentialHVACCtrlBidQuantity\R#_12_47
#feeder#ctrlBidQuantity.csv>
- retail market data statistics over time <\retailMarketData\R#_12_47
#feeder#_retailMarket.csv>
- extra data for the case with feedback - distribution coordinator results <\results\distributionCoordinator>:
- individual HVAC consumption for all feeders under the same coordinator (at the substation/bus level) at fixed time intervals <\actualLoadData\bus#_actualLoadData.csv>
- for each coordinator (at substation/bus level), second order fit coefficients of the demand curve, maximum flexibile demand [KW], and the currently active controllable load [KW] at fixed time intervals<\demandCurveData\bus#_demandCurveData.csv>
- individual HVAC price bid for all feeders under the same coordinator (at the substation/bus level) at fixed time intervals <bus#_priceData.csv>
- individual HVAC quantity bid for all feeders under the same coordinator (at the substation/bus level) at fixed time intervals <bus#_quantityData.csv>

weather folder contains the weather-related files for each region, and reports the outside temperature and humidity.

Contact Name
Laurentiu Marinovici
Contact Email
Public Access Level
Public