The increasing penetration of Distributed Energy Resources (DER) expands the cyberattack surface of power systems. This paper analyses, using PowerFactory, the impact and success of MaDIoT 3.0 attacks in the PST-16 model, a simplified model of the European system. MaDIoT 3.0 attacks are a novel type of attack that manage to compromise both high-wattage IoT demand devices and DER devices at the same time. The results indicate that the inclusion of distributed solar PV generation in the PST-16 system reduces the success ratio and impact of load-altering MaDIoT attacks when compared to the same system without DER, mainly due to an increment of the initial voltages. For MaDIoT 3.0 attacks, the demand had a more significant influence on the attack’s success than DER in the PST-16 system. Distributing the attacked demand across more buses or targeting the demand from other areas would decrease the success ratio of the attack. Therefore, the local scalability and replicability of vulnerable high-wattage demand devices in the analysed system become more critical than their distributed deployment in larger areas.

The increasing penetration of Internet of Things (IoT) devices at the consumer level of power systems also increases the surface of attack for the so-called Manipulation of Demand through IoT (MaDIoT) attacks. This paper provides a comparison of the impact that MaDIoT attacks could have on power systems with different characteristics, such as the IEEE 39-Bus (New England) and the PST-16 system (simplified European model), by assuming that the attacker does not have advanced knowledge of the grid. The results for the IEEE 39-Bus system expand and complement the results obtained by previous work. The simulation results show that these systems present significant differences between them with respect to the success probability of an attack, being in general much higher for the IEEE 39-Bus system. In the PST-16 system, the required number of bots to obtain a certain success probability varies depending on the area attacked. However, a high probability of success does not necessarily mean a high impact on the system. This paper shows that the response to the high-impact MaDIoT attacks of the two models considered is very different as the initial impact of the attack on the system also differs, mainly affecting rotor angles in the PST-16 system, and the frequency in the IEEE 39-Bus.