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Jorge Mario Velasquez De la Ossa

Methodology for Controller Conflict Assessment in Distribution Networks with High Penetration of Decentralized Energy Resources

PhD by Jorge Mario Velasquez De la Ossa, Colombia (PPRE 2013/15)
at OFFIS - R&D Division Energy – Simulation and Automation of Complex Energy Systems in Oldenburg (since
March 2015)

Decentralized Energy Resources (DER) are taking a significant role in the power supply in Germany. The aim is to provide energy in a secure, reliable and sustainable manner while phasing out nuclear and fossil fueled power plants. In order to address these requirements it is necessary to introduce modern control strategies, and consequently the use of Automation and Information and Communication Technologies (ICT). However, the use of multiple control schemes in a complex grid may result in a conflicting behavior of two or more control devices which ultimately lead to an undesired behavior of the controlled power plants. For example, there is an increase in the use of renewable energies to provide ancillary services to address grid stability issues. This means that these power plants are able to supply active and reactive power to meet the frequency and voltage levels respectively. One particular conflict occurs when the Transmission System Operator (TSO) requires the provision of reactive power to control the voltage levels in the MV grid resulting in an imbalance of the voltage levels in the LV grid.

Nowadays, there are several efforts toward the early identification and mitigation of controller conflicts within complex energy systems. However, a comprehensive methodology to address these issues is still not fully established. This research is divided into three different stages. First is the identification of possible conflicts that may emerge from the interaction of two or more control schemes with the identification of several Use Cases and its mapping onto the SGAM architecture. Second it is necessary to confirm the existence of the conflict and to determine its impact on a given electrical power system via the employment of software and hardware co-simulation. The final step is to give the recommendations towards the mitigation of the source of conflict among intelligent devices.

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