The proliferation of Distributed Energy Resources (DERs) is decentralizing the power system, with more and more capacity installed in the distribution grids. Concurrently, the energy sector is embracing the Internet of Things (IoT) paradigm, resulting in the emergence of the Internet of Energy. However, this transformation introduces new concerns regarding cyber security. As the number of interconnected devices increases, the possible attack surface for malicious actors expands. Recognizing this challenge, researchers are investigating the potential cyber security benefits of applying blockchain in power systems. Blockchain offers some secure-by-design features, such as the immutability of the stored data, that can be leveraged to improve the cyber security of smart grids.
In this work, a blockchain-based application for the monitoring and control of a feeder in the Low-Voltage (LV) distribution grid is designed and tested. A smart contract is created and deployed in a private Ethereum blockchain utilizing the Proof of Authority (PoA) consensus mechanism. The blockchain application enhances the cyber security of the LV distribution system in three ways. First, it detects cyber attacks targeting DERs by comparing the setpoints received by prosumers with smart meter measurements. Second, it prevents cyber attacks by enabling the exchange of measurements and setpoints on-chain and by preventing unreliable prosumers from participating in the voltage regulation market. Third, it mitigates the effects of cyber attacks on the steady-state voltage magnitudes by enforcing a novel voltage regulation mechanism, in which a new metric is proposed to quantify the power-to-voltage relationship while considering the location of the power exchange.
The efficacy of the blockchain application is tested in a co-simulation environment together with a modeled LV distribution network, simulated in DigSILENT PowerFactory. The distribution network model is first used to assess the impact of cyber attacks manipulating the setpoints of Battery Energy Storage Systems (BESSs), which have been identified as the most critical DERs. The simulation results demonstrate that the considered cyber attacks can force the disconnection of inverters by causing violations of the acceptable steady-state voltage magnitudes. One of the scenarios demonstrates that a cyber attack targeting half of the BESSs in a feeder can lead to the collapse of the voltage, causing a local outage. Finally, the results of the co-simulation of the blockchain-based monitoring and control system, achieved by the Open Platform Communications Unified Architecture (OPC UA) communication protocol and by a series of clients managing the data streams, demonstrate its efficacy in detecting cyber attacks and mitigating their impact on the voltage magnitude across the feeder, thus reducing the number of disconnected DERs.

Power grids rely on Operational Technology (OT) networks, for real-time monitoring and control. These traditionally segregated systems are now being integrated with general-purpose Information and Communication Technologies (ICTs). The coupling of the physical power system and its communications infrastructure forms a complex, interdependent structure referred to as a Cyber-Physical System (CPS). As cyber attacks on critical infrastructures become more frequent, power systems are especially vulnerable, as their OT systems were not designed with cyber security considerations. Hence, identifying and quantifying the risk of cyber attacks on power grids is of utmost importance.
In this dissertation, a method for quantitative risk assessment is proposed. The impact of cyber attacks is examined on a holistic model of a cyber-physical power system and their likelihood is assessed through attack graphs. Firstly, the physical power system is modelled to analyze the impact of cyber attacks on power system operation. The dynamic model of the IEEE 39-bus is used to validate the proposed risk assessment method. Various protection schemes are implemented and coordinated to analyze how cyber attacks can lead to cascading failures and a blackout. The communication networks of digital substations are modelled and integrated with the power system model. They emulate the communication network traffic between the control center and digital substations. The physical and cyber system models are integrated via co-simulation.
Secondly, attack graphs for digital substations are designed and used for cyber attack analysis. The attack graph model is based on the topology of a digital substation, specified by industry and academia. A novel method is proposed for defining the probability distributions of the time-to-compromise for each attack step, which is used in the attack simulations to extract the global time-to-compromise of the targeted asset.
Furthermore, an impact assessment method is proposed, which correlates the impact on both layers of the cyber-physical system. Key performance indicators for the power system operation as well as the operation of its communication system are defined and implemented. The overall risk of a specific cyber attack scenario is assessed based on the impact indices, likelihood of the cyber attack to commence, and a proposed metric regarding power system restoration. The proposed methods are validated by examining various cyber attack scenarios on the developed cyber-physical system model. The examined scenarios are based on real-world cyber attacks. Additionally, a study regarding the effect of different attack sequences is conducted. The impact is assessed on both layers of the cyber-physical power system by running dynamic simulations.
On overall, the CPS simulation results show the effectiveness of the proposed methods to assess risks and identify the most critical systems per cyber attack scenario. The proposed methods correlate the vulnerability assessment of the modelled security infrastructure with the corresponding impact on the cyber-physical system. The risk assessment is validated by a comprehensive analysis of selected study cases, examining the cascading failure chains of the power system. These studies show the importance of examining various attack scenarios in order to identify the weak points and bottlenecks in the integrated cyber-physical power system.