Progress in Microgrid (MG) research has evolved the MG concept from classical, purely MG power networks to more advanced power and communications networks. The communications infrastructure helps control and manage the unreliable power outputs that most standard power generation elements of the MG (e.g., wind turbines and photo-voltaic panels) deliver. Although communication technologies do offer certain advantages for sensing and control, they generate other complications due to packet loss and packet latency, among other transmission impairments. In this work, we discuss the impact of communications on MG performance, establishing the requirements of data exchanges and system response in the three levels of a hierarchical control approach: primary, secondary, and tertiary. With a focus on the secondary level — responsible for ensuring the restoration of electrical parameters — we identify standards, networking protocols, and communication technologies relevant for the interoperability of MGs and clusters of MGs, including both modes of operation: isolated and grid-connected. We review theoretical approaches and practical implementations that consider the effects of the communications network on the general performance of the MG. Moreover, we undertake an experimental analysis of the influence of wired and wireless communication networks on MG performance, revealing the importance of designing future smart control solutions more robust to communication degradation, especially if wireless technologies are integrated to provide scalable deployments. Aspects such as resilience, security, and interoperability are also shown to require continuing efforts in research and practical applications.

Distributed control schemes have transformed frequency and voltage regulation into a local task in distributed generators (DGs) rather than by a central secondary controller. A distributed scheme is based on information shared among neighboring units; thus, the microgrid performance is affected by issues induced by the communication network. This paper presents a distributed predictive control applied to the secondary level of microgrids. The model used for prediction purposes is based on droop and power transfer equations; however, communication features, such as connectivity and latency, are also included, thus making the controller tolerant to electrical and communication failures. The proposed controller considers the frequency and voltage regulation control objectives and consensus over the real and reactive power contributions from each power unit in the microgrid. The experimental and simulation results show that the proposed scheme (i) responds properly to load variations, working within operating constraints, such as generation capacity and voltage range; (ii) maintains the control objectives when a power unit is disconnected and reconnected without any user updating in the controllers; and (iii) compensates for the effects of communication issues over the microgrid dynamics.

Microgrids are the cornerstone for a new model of electrical generation based on renewable resources. Commonly microgrids are controlled with a centralised hierarchical structure, which is inherited from power systems. However, a time-scale separation between traditional fast frequency restoration and slow economic dispatch may be counterproductive in the long run because the slow long-term economic dispatch increases the prediction uncertainty. In an effort to improve the economical operation of microgrids, this work proposes a distributed model predictive control strategy for the operation of isolated microgrids based on a consensus strategy that tackles both the economic dispatch and frequency restoration over the same time-scale. The proposed controller can operate without knowledge of the microgrid's topology: instead, typical local measurements and other information from neighboring generation units are required. Experimental results demonstrate that the controller is robust to load variations and communication issues, but the plug-and-play nature of the system is preserved.

This paper proposes a distributed predictive secondary control strategy to share imbalance in three-phase, three-wire isolated AC Microgrids. The control is based on a novel approach where the imbalance sharing among distributed generators is controlled through the control of single-phase reactive power. The main characteristic of the proposed methodology is the inclusion of an objective function and dynamic models as constraints in the formulation. The controller relies on local measurements and information from neighboring distributed generators, and it performs the desired control action based on a constrained cost function minimization. The proposed distributed model predictive control scheme has several advantages over solutions based on virtual impedance loops or based on the inclusion of extra power converters for managing single-phase reactive power among distributed generators. In fact, with the proposed technique the sharing of imbalance is performed directly in terms of single-phase reactive power and without the need for adding extra power converters into the microgrid. Contrary to almost all reported works in this area, the proposed approach enables the control of various microgrid parameters within predefined bands, providing a more flexible control system. Extensive simulation and Hardware in the Loop studies verify the performance of the proposed control scheme. Moreover, the controller’s scalability and a comparison study, in terms of performance, with the virtual impedance approach were carried out.

The transition from fossil fuels to renewable energies as power sources in the heavy industries is one of the main climate change mitigation strategies. The carbon footprint in mining is related to its inherent extraction process, its high demand of electric power and water, and the use of diesel. However, considering its particular power requirements, the integration of microgrids throughout the whole control hierarchy of mining industry is an emergent topic. This paper provides an overview of the opportunities and challenges derived from the synergy between microgrids and the mining industry. Bidirectional and optimal power flow, as well as the integration of power quality have been identified as microgrid features that could potentially enhance mining processes. Recommendations pertaining to the technological transition and the improvement of energy issues in mining environments are also highlighted in this work.

Hybrid AC/DC microgrids (H-MGs) are a prominent solution for integrating distributed generation and modern AC and DC loads. However, controlling these systems is challenging as multiple electrical variables need to be controlled and coordinated. To provide flexibility to the control system, these variables can be regulated to specific values or within secure bands. This paper proposes a set of distributed model predictive control schemes for the secondary control level to control certain variables to specific values and other variables within secure pre-defined bands into H-MGs. Specifically, optimal dispatch of active and reactive power is achieved while frequency and voltages are regulated within secure bands in H-MGs. Dynamic models of AC generators, DC generators and interlinking converters along with their novel multi-objective cost functions are developed in constrained distributed predictive optimisation problems to simultaneously achieve the aforementioned objectives via information sharing. Extensive simulation work validates the performance of this proposal.