Biblio
The concept of a microgrid has emerged as a promising solution for the management of local groups of electricity consumers and producers. The use of end-users' energy usage data can help in increasing efficient operation of a microgrid. However, existing data-aggregation schemes for a microgrid suffer different cyber attacks and do not provide high level of accuracy. This work aims at designing a privacy-preserving data-aggregation scheme for a microgrid of prosumers that achieves high level of accuracy, thereby benefiting to the management and control of a microgrid. First, a novel smart meter readings data protection mechanism is proposed to ensure privacy of prosumers by hiding the real energy usage data from other parties. Secondly, a blockchain-based data-aggregation scheme is proposed to ensure privacy of the end-users, while achieving high level of accuracy in terms of the aggregated data. The proposed data-aggregation scheme is evaluated using real smart meter readings data from 100 prosumers. The results show that the proposed scheme ensures prosumers' privacy and achieves high level of accuracy, while it is secure against eavesdropping and man-in-the-middle cyber attacks.
The expression of cyber-attacks on communication links in smart grids has emerged recently. In microgrids, cooperation between agents through communication links is required, thus, microgrids can be considered as cyber-physical-systems and they are vulnerable to cyber-attack threats. Cyber-attacks can cause damages in control systems, therefore, the resilient control methods are necessary. In this paper, a resilient control approach against false data injection attack is proposed for secondary control of DC microgrids. In the proposed framework, a PI controller with an adjustable gain is utilized to eliminate the injected false data. The proposed control method is employed for both sensor and link attacks. Convergence analysis of the measurement sensors and the secondary control objectives under the studied control method is performed. Finally, a DC microgrid with four units is built in Matlab/Simulink environment to verify the proposed approach.
This paper presents a user-friendly design method for accurately sizing the distributed energy resources of a stand-alone microgrid to meet the critical load demands of a military, commercial, industrial, or residential facility when the utility power is not available. The microgrid combines renewable resources such as photovoltaics (PV) with an energy storage system to increase energy security for facilities with critical loads. The design tool's novelty includes compliance with IEEE standards 1562 and 1013 and addresses resilience, which is not taken into account in existing design methods. Several case studies, simulated with a physics-based model, validate the proposed design method. Additionally, the design and the simulations were validated by 24-hour laboratory experiments conducted on a microgrid assembled using commercial off the shelf components.
The ability to advance the state of the art in automated cybersecurity protections for industrial control systems (ICS) has as a prerequisite of understanding the trade-off space. That is, to enable a cyber feedback loop in a control system environment you must first consider both the security mitigation available, the benefits and the impacts to the control system functionality when the mitigation is used. More damaging impacts could be precipitated that the mitigation was intended to rectify. This paper details networked ICS that controls a simulation of the frequency response represented with the swing equation. The microgrid loads and base generation can be balanced through the control of an emulated battery and power inverter. The simulated plant, which is implemented in Raspberry Pi computers, provides an inexpensive platform to realize the physical effects of cyber attacks to show the trade-offs of available mitigating actions. This network design can include a commercial ICS controller and simple plant or emulated plant to introduce real world implementation of feedback controls, and provides a scalable, physical effects measurable microgrid for cyber resilience analysis (SPEMMCRA).