Predictive Congestion and Distributed Energy Resources Management
Kuovi, Janne Petteri (2015)
2015
Sähkötekniikan koulutusohjelma
Tieto- ja sähkötekniikan tiedekunta - Faculty of Computing and Electrical Engineering
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Hyväksymispäivämäärä
2015-12-09
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:tty-201511231739
https://urn.fi/URN:NBN:fi:tty-201511231739
Tiivistelmä
More and more distributed generation is connected to distribution network. Despite its many benefits, distributed generation can also cause problems, especially at times of large production and low consumption. The significance of energy storages is growing as well. Therefore the software used by distribution system operators must support the energy storages.
In this master’s thesis, bottlenecks caused by distributed generation, and energy storages were introduced, requirement specifications and functional specifications were pro-duced, and congestion management and energy storage component were implemented in distribution management system MicroSCADA Pro DMS600. Congestion manage-ment solution is based on outline created earlier.
The congestion management implementation can be used to find bottlenecks like over-voltage and overload at present time and 72 hours in advance. The main solution offered to mitigate violations is to curtail real power produced by distributed generation. This solution was pre-selected. Also Volt-VAr Control integration is included. Volt-VAr Control offers possibility to control voltage by means of stepping on-load tap changers on primary transformers and switching of capacitors. The program calculates the amount of curtailment needed and finds possible curtailment locations with sensitivities but does not decide where the curtailments shall actually take place. Grouping the violations by the violation type, location, and relation to other violations was selected for present-ing the analysis results better. The information can be saved in a text file. Executing the curtailments requires a separate software.
The congestion management is based on unreliable and inaccurate consumption and production forecasts. This means the results are inaccurate as well. The solution still pro-vides an enhancement when compared to earlier situation without such feature.
The energy storage component may be used for asset management and for calculation purposes including simulation. There are multiple different energy storage types availa-ble. The most important common properties of the energy storages include capacity, state of charge, charge and discharge rate, and efficiencies. The battery energy storages are modeled with two models: Peukert’s law and kinetic battery model which were adopted to meet the requirements. They can take into account the nonlinear properties of the batteries. Other energy storages are modeled linearly. As the energy storage systems provide possibilities for reactive power control, it is modeled as well.
In this master’s thesis, bottlenecks caused by distributed generation, and energy storages were introduced, requirement specifications and functional specifications were pro-duced, and congestion management and energy storage component were implemented in distribution management system MicroSCADA Pro DMS600. Congestion manage-ment solution is based on outline created earlier.
The congestion management implementation can be used to find bottlenecks like over-voltage and overload at present time and 72 hours in advance. The main solution offered to mitigate violations is to curtail real power produced by distributed generation. This solution was pre-selected. Also Volt-VAr Control integration is included. Volt-VAr Control offers possibility to control voltage by means of stepping on-load tap changers on primary transformers and switching of capacitors. The program calculates the amount of curtailment needed and finds possible curtailment locations with sensitivities but does not decide where the curtailments shall actually take place. Grouping the violations by the violation type, location, and relation to other violations was selected for present-ing the analysis results better. The information can be saved in a text file. Executing the curtailments requires a separate software.
The congestion management is based on unreliable and inaccurate consumption and production forecasts. This means the results are inaccurate as well. The solution still pro-vides an enhancement when compared to earlier situation without such feature.
The energy storage component may be used for asset management and for calculation purposes including simulation. There are multiple different energy storage types availa-ble. The most important common properties of the energy storages include capacity, state of charge, charge and discharge rate, and efficiencies. The battery energy storages are modeled with two models: Peukert’s law and kinetic battery model which were adopted to meet the requirements. They can take into account the nonlinear properties of the batteries. Other energy storages are modeled linearly. As the energy storage systems provide possibilities for reactive power control, it is modeled as well.