Electric power systems are becoming increasingly complex to operate; a trend driven by an increased demand for electricity, large-scale integration of renewable energy resources, and new system components with power electronic interfaces. In this thesis, a new real-time monitoring and control tool that can support system operators to allow more efficient utilization of the transmission grid has been developed. The developed tool is comprised of four methods aimed to handle the following complementary tasks in power system operation: 1) preventive monitoring, 2) preventive control, 3) emergency monitoring, and 4) emergency control. The methods are based on recent advances in machine learning and deep reinforcement learning to allow real-time...
In the smart grid paradigm, growing integration of large-scale intermittent renewable energies has i...
The integration of renewable energy into the power system requires rethinking the operating paradigm...
The continuous increase in the demand of active and reactive power in the power system network has l...
Voltage instability is a phenomenon that limits the operation and the transmission capacity of a pow...
This paper develops a real-time control method based on deep reinforcement learning (DRL) aimed to d...
Deep reinforcement learning (DRL) is a machine learning-based method suited for complex and high-dim...
With the increasing integration of variational renewable energy and the more active demand side resp...
With the increasing requirements for power system transient stability assessment, the research on po...
This study develops a machine learning-based method for a fast estimation of the dynamic voltage sec...
Research Doctorate - Doctor of Philosophy (PhD)Security is a basic yet essential requirement for ope...
In recent years, with the expansion of power system size, the increase of interconnection and the us...
Research Doctorate - Doctor of Philosophy (PhD)The fundamental role of an electrical power system is...
Modern power systems are very complex due to constant variations of the load. These systems are cons...
peer reviewedThis paper reviews existing works on (deep) reinforcement learning considerations in e...
In power system operation, steady state security control is employed to provide continuous supply to...
In the smart grid paradigm, growing integration of large-scale intermittent renewable energies has i...
The integration of renewable energy into the power system requires rethinking the operating paradigm...
The continuous increase in the demand of active and reactive power in the power system network has l...
Voltage instability is a phenomenon that limits the operation and the transmission capacity of a pow...
This paper develops a real-time control method based on deep reinforcement learning (DRL) aimed to d...
Deep reinforcement learning (DRL) is a machine learning-based method suited for complex and high-dim...
With the increasing integration of variational renewable energy and the more active demand side resp...
With the increasing requirements for power system transient stability assessment, the research on po...
This study develops a machine learning-based method for a fast estimation of the dynamic voltage sec...
Research Doctorate - Doctor of Philosophy (PhD)Security is a basic yet essential requirement for ope...
In recent years, with the expansion of power system size, the increase of interconnection and the us...
Research Doctorate - Doctor of Philosophy (PhD)The fundamental role of an electrical power system is...
Modern power systems are very complex due to constant variations of the load. These systems are cons...
peer reviewedThis paper reviews existing works on (deep) reinforcement learning considerations in e...
In power system operation, steady state security control is employed to provide continuous supply to...
In the smart grid paradigm, growing integration of large-scale intermittent renewable energies has i...
The integration of renewable energy into the power system requires rethinking the operating paradigm...
The continuous increase in the demand of active and reactive power in the power system network has l...