• Energy Research

The smart grid merges cyber-physical systems (CPS) infrastructure with information and communication technologies (ICT) to ensure efficient power generation, smart energy distribution in real-time, and optimisation, and it is rapidly becoming the current standard for energy generation and distribution. However, the use of ICT has increased the attack surface against the electricity grid, which is vulnerable to a wider range of cyberattacks. In particular, Denial-of-Service (DoS) attacks might impact both the communication network and the cyber-physical layer. DoS attacks have become critical threats against the smart grid due to their ability to impact the normal operation of legitimate smart-grid devices and their ability to target different smart grid systems and applications. This paper presents a comprehensive and methodical discussion of DoS attacks in the smart grid, analysing the most common attack vectors and their effect on the smart grid. The paper also presents a survey of detection and mitigation techniques against DoS attacks in the smart grid using reinforcement learning (RL) algorithms, analysing the strengths and limitations of the current approaches and identifying the prospects for future research.

This paper deals with the load shifting problem in a household equipped with smart appliances and an energy storage unit with conversion losses. The problem is faced by establishing an event driven Model Predictive Control framework aiming to meet the real life dynamics of a household and to keep low the impact of the control system on the total electric energy consumption. The proposed approach allows the consumer to minimize the daily energy cost in scenarios characterized by Time of Use tariffs and Demand Side Management, by dynamically evaluating the best time to run of the appliances and the optimal evolution of the battery level of charge. A proper set of realistic simulations validates the proposed approach, showing the relevance of the energy storage unit in the domestic load shifting architecture.

The new challenge in power systems design and operation is to organize and control smart micro grids supplying aggregation of users and special loads as electric vehicles charging stations. The presence of renewable and storage can help the optimal operation only if a good control manages all the elements of the grid. New models of green buildings and energy communities are proposed. For a real application they need an appropriate and advanced power system equipped with a building automation control system. This article presents an economic model predictive control approach to the problem of managing the electric and heating resources in a smart building in a coordinated way, for the purpose of achieving in real time nearly zero energy consumption and automated participation to demand response programs. The proposed control, leveraging a mixed integer quadratic programming problem, allows to meet manifold thermal and electric users’ requirements and react to inbound demand response signals, while still guaranteeing stable operation of the building's electric and thermal storage equipment. The simulation results, performed for a real case study in Italy, highlight the peculiarities of the proposed approach in the joint handling of electric and thermal building flexibility.

This paper presents a review of technical works in the field of cyber-physical attacks on the smart grid. The paper starts by discussing two reference mathematical frameworks proposed in the literature to model a smart grid under attack. Then, a review of cyber-physical attacks on the smart grid is presented, starting from works on false data injection attacks against state estimation. The aim is to present a systematic and quantitative discussion of the basic working principles of the attacks, also in terms of the inner smart grid vulnerabilities and dynamical properties exploited by the attack. The main contribution of the paper is the attempt to provide a unifying view, highlighting the fundamental aspects and the common working principles shared by the attack models, even when targeting different subsystems of the smart grid.

This paper presents a novel control system for the participation of plug-in electric vehicles (PEVs) in the provisioning of ancillary services for frequency regulation, in a way that is transparent to the driver and harmonized with the smart charging service requirements. Given a power-frequency droop curve, which specifies how the set of PEVs collectively participate to the provisioning of the frequency regulation service (we call this curve a “global” droop curve), we propose an algorithm to compute “local” droop curves (one for each PEV), which are optimized according to the current status of the PEV and the current progress of the smart recharging session. Once aggregated, the local droop curves match the global one (so that the PEVs contribute as expected to the provisioning of the ancillary service). One innovative aspect of the proposed algorithm is that it is specifically designed to be interoperable with the algorithms that control the PEV recharging process; hence, it is transparent to the PEV drivers. Simulation results are presented to validate the proposed solution.

This paper presents an optimal procedure for controlled electricity black start for electricity distribution grids in reaction to adverse events or malicious cyber attacks resulting in the interruption of the main power supply from transmission network. The islanded operation is supposed to be guaranteed by an electric energy storage system, which covers the network imbalance between demand and supply from distributed generation during the sequential reconnection of medium voltage branches. The objective is to restore the service to the consumers while avoiding violation of technical constraints in terms of storage power flow and battery capacity. The discussion of simulation results assesses the effectiveness of the proposed approach in the context of a simplified network model and gives rise to relevant remarks and requirements for further developments.

This paper presents an optimisation problem to determine the optimal reclosure order of remotely operable switches deployed in a smart grid consisting in a distribution network equipped with one or more Energy Storage Systems (ESS). The proposed solution integrates nonlinear real and reactive power flow equations, by reconducting them to a set of conic constraints, together with several network operator requirements, such as network radiality and ampacity limits. A numerical simulation validates the approach and concludes the work.