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.

The modern power grid is becoming more susceptible to cyber-attacks due to an increase in digitalization, leading to a larger attack surface for malicious actors to attack. Such attacks on critical infrastructure could lead to partial power outages, minor societal disruption, or in the worst-case scenario, a rolling black-out in which the entire country has no access to electricity. Electrical utility companies can decrease the likelihood of a successful cyber-attack on the Cyber Physical Power System (CPPS) – consisting of the physical power grid, and vulnerable Information Technology (IT) and Operational Technology (OT)- by implementing cyber security interventions. Investing in these cyber security mechanisms is not cheap, which is why it is expected to have a certain return on investment. However, it is hard to quantify the effects of prospective cyber security investments. The main research question of this study is: “To what extent can cyber security measures decrease the risk of cyber attacks on CPPS substations?” This research question is answered by means of an implicitly mixed research approach that uses computer-assisted attack tree modelling and Monte Carlo simulation. The model is based on the publicly available technical system information of known suppliers of relevant substation components and other documentation acquired by means of multiple literature studies and document analyses. The change in likelihood and subsequent risk has been studied by extensively modelling the possible attack paths of a digital substation. This has been combined with financial analysis in the form of a societal cost-benefit analysis. As a result, potential cyber security investments can be evaluated on their merits in the form of risk reduction and their required costs as expressed in dollars. The contribution of the performed research to science is the elaboration of existing models to more accurately represent reality, and simultaneously provide the cyber security decision-making process with a tool that provides guiding Key Performance Indicators (KPIs). This study has shown that suggested measures from the quantified model are able to increase the TTCavg needed by malicious actors to reach their intended target, and therefore cause a decrease in likelihood and subsequent risk of the studied scenarios. An important finding of this study emphasizes the need for extensive attack path modelling. This finding was the fact that the application of some well-intended countermeasure (such as remote-attestation), might have no significant effect on the likelihood and risk of a certain scenario at all, but only changes the dominant attack path. While the constructed quantified model, as proposed in this study, is able to provide quantified insights into the effects of proposed cyber security investments, it is merely a simplified tool that should be expanded upon to generate more accurate insights. Besides the aforementioned there have been additional findings from this study. Such as a list of weaknesses in the current state of digital substation cyber security. This list has been created by an extensive document analysis of over 40 sources. Also, an overview of 23 different possible cyber security interventions has been compiled by a systemic literature review of over 16 sources. According to the quantified model, a reduction (between 21.8% and 93%) in the total risk of certain attack scenarios against digital substation by malicious actors can be achieved. The costs for these possible risk reductions range between $28 thousand for a honeypot deception system and $413 thousand for a combination of all the simulated countermeasures. These countermeasures could, in comparison to a base case with no protection, potentially reduce the total risk by an amount between $3.7 billion and $15.9 billion. According to the general societal cost-benefit analyses, the best Retun-on- Investment (ROI)/cost-effectiveness of investment is the investment in a honeypot (scenario 5) which has an ROI of 247,390, and the least cost-effective is the investment in remote attestation (scenario 4), which has an ROI of -2,066. Altogether, this study has shown that there is added value in using a simplified quantified model to aid in decision-making for digital substation cyber security investments aimed at risk reduction.