Optimization is an essential part of power grid operation and lately, Online Optimization methods have gained traction. One such method is Online Feedback Optimization (OFO) which uses measurements from the grid as feedback to iteratively change the control inputs until they converge to the solution of the optimization problem. Such algorithms have been applied to many power system problems and experimentally validated in lab setups. This paper implements an OFO controller in a real distribution grid for 24/7 operation using off-the-shelf hardware and software. The proposed control strategy optimizes the reactive power flow at the substation while satisfying voltage constraints. As part of an existing coordination scheme between (sub)transmission grid operator (TSO) and distribution grid operator (DSO), this comes with a financial reward and simultaneously it virtually reinforces the grid by regulating the voltage on the feeder and therefore allowing higher levels of distributed generation/consumption. We present how a distribution grid is retrofitted such that we can use existing inverters, we analyze the controller's interaction with legacy infrastructure, and investigate its overall control behavior. Finally, we demonstrate the successful deployment of an OFO controller in an operational environment which corresponds to Technology Readiness Level (TRL) 7.
Der Einsatzbereich von Gasmotoren ist heute äußerst vielfältig. Off-Highway-betriebene Gasmotoren – also Motoren, die nicht für Straßenfahrzeuge vorgesehen sind – werden zunehmend auch für Anwendungen vorgesehen, die noch vor wenigen Jahren fast ausschließlich mit Dieselmotoren bedient wurden.
For corporate security officers (CSOs), investment decisions about IT security are more challenging than microeconomic models would suggest. Large budgets are not necessarily associated with effective corporate protection, whereas cybersecurity breaches negatively affect individual career prospects irrespective of prior investments. In this chapter we build on the Gordon-Loeb model to develop a recursive model which simulates investment dynamics, CSO reputation and inter-firm migration as well as cyberdefense effectiveness. We argue that a positive (negative) dynamic should exist between high (low) CSO reputation and effective corporate protection, and we simulate this hypothesized relationship by a Monte Carlo process which uses data from real cybersecurity breaches.
