This paper provides a comprehensive review of the applications of smart meters in the control and optimisation of power grids to support a smooth energy transition towards the renewable energy future. The smart grids become more complicated due to the presence of small-scale low inertia generators and the implementation of electric vehicles (EVs), which are mainly based on intermittent and variable renewable energy resources. Optimal and reliable operation of this environment using conventional model-based approaches is very difficult. Advancements in measurement and communication technologies have brought the opportunity of collecting temporal or real-time data from prosumers through Advanced Metering Infrastructure (AMI). Smart metering brings the potential of applying data-driven algorithms for different power system operations and planning services, such as infrastructure sizing and upgrade and generation forecasting. It can also be used for demand-side management, especially in the presence of new technologies such as EVs, 5G/6G networks and cloud computing. These algorithms face privacy-preserving and cybersecurity challenges that need to be well addressed. This article surveys the state-of-the-art of each of these topics, reviewing applications, challenges and opportunities of using smart meters to address them. It also stipulates the challenges that smart grids present to smart meters and the benefits that smart meters can bring to smart grids. Furthermore, the paper is concluded with some expected future directions and potential research questions for smart meters, smart grids and their interplay.

This paper proposes a distributed hierarchical control framework for energy storage systems (ESSs) in DC microgrid clusters, which achieves voltage regulation and current sharing for ESSs in each microgrid as well as the whole microgrid cluster. The primary control stage adopts a droop controller which only requires local information while the secondary control stage provides correction terms for ESSs within microgrids. The tertiary control stage samples the pinned ESSs in different microgrids with low sampling rate to provide the voltage setpoint, which ensures global current sharing among microgrid cluster. The corresponding multilayered event-triggered consensus algorithm for clusters is proposed to reduce the communication cost generated by operation of the distributed controller. Both the control framework and the consensus algorithm can be extended for satisfying higher dimensional regulation needs. The controller is validated in a DC microgrid cluster through simulation under different scenarios, and the results illustrate the effectiveness of the proposed controller.

This paper investigates distributed finite-time secondary control of islanded AC microgrids with prescribed performance subject to time-varying disturbances. By specifying the desired performance function, the transient and steady-state performances (including the convergence rate, the maximum overshoot, and the maximum steady-state error) of both the voltage and frequency restoration processes are considered in the design phase. Given the microgrid modeling inaccuracies and load-switching effects, the time-varying disturbances lump unmodeled dynamics, parameter perturbations, and exogenous load disturbances. A novel control scheme, which consists of two main parts, is established. In the first part, reference signal generators are constructed to produce the restoration references in a finite time for each power unit. In the second part, with the observer-based disturbance rejection technique and the prescribed performance control philosophy, performance-guaranteed finite-time secondary controllers are designed such that the finite-time restoration task with the prescribed performance is fulfilled, and the time-varying disturbance rejection is achieved. Rigorous stability analysis and case studies are conducted to verify the correctness and effectiveness of the proposed control scheme.

This study investigates the distributed secondary control of a network of interconnected battery energy storage systems (BESSs) in an islanded AC microgrid (MG) where an upper-bounded number of BESS units are subject to cyberattacks. Byzantine model of misbehaviour is considered, where the compromised BESSs can communicate contradicting and unbounded information to their neighbours in order to destabilise MG's operation. A new resilient distributed secondary control algorithm is proposed, whereby the data transmitted by a predetermined number of extreme neighbours is ignored by the normal BESSs. It is proved that the proposed algorithm guarantees resilient frequency regulation, active power sharing, and state of charge balancing, provided specific conditions regarding control parameters and the robustness of communication network topology are met. The theoretical results are supported by experimental results obtained using an OPAL-RT real-time simulator.