Regarding microgrids (MGs), several definitions can be found in the literature ^{[1][2][3][4][5][6]}[21,139,140,141,142,143]. The U.S. Department of Energy ^[1][21] defines a MG as “a group of interconnected loads and distributed energy resources within clearly defined electrical boundaries that acts as a single controllable entity with respect to the main grid. A microgrid can connect and disconnect from the grid and, as a result, can operate in grid-connected or islanded mode. A remote microgrid is a variation of a microgrid that operates in islanded conditions”. The International Council on Large Electrical Systems (CIGRE) and the Consortium for Electric Reliability Technology Solution (CERTS) define MGs as “electricity distribution systems containing loads and distributed energy resources, (such as distributed generators, storage devices, or controllable loads) that can be operated in a controlled, coordinated way either while connected to the main power network or while islanded”. The French Energy Regulation Commission (CRE) ^[6][7][23,143] defines MGs as “small-scale power grids designed to provide a reliable power supply to a small number of consumers. Microgrids combine multiple local and diffuse production facilities, consumption facilities, storage facilities and supervision and monitoring tools for demand management. Microgrids can be directly connected to the power distribution grid (i.e., the main grid) or operate disconnected from the grid (islanding mode). The microgrid concept, likely to concern different system scales (i.e., a building, a district, an industrial or a craft zone, a village, etc.) is being extended to heat and natural gas networks, and can thus be thought out in a multifaceted manner”.

In recent years, interconnected (networked) microgrids have emerged as one of the best successors to the current power distribution system. In networked (interconnected) microgrids (NMGs), local resources are shared between MGs and cooperative power exchange management is carried out ^[8][82]. According to Alam et al. ^[9][28], “networked MGs is referred to the interconnection of two or more MGs with an ability to connect distribution system to exchange power among the microgrids and/or the distribution system at the point of common coupling (PCC)”. The deployment of NMGs is an interesting way to improve security, efficiency, durability, robustness, reliability, economic profitability and carbon footprint aspects ^[9][10][11][28,134,146]. In networked MGs, a MG can be islanded for independent operation, along (or not) with other MGs. In this case, energy management systems (EMSs) seek to maximize energy self-sufficiency ^[2][9][28,139].

A MG (or a NMG) is composed of the following components (Figure 14) ^[12][13][32,147]:

• Distributed generators. Sources of distributed generation include on-site renewables, such as wind and solar, waste-to-energy and combined heat and power (CHP). Conventional generation sources (diesel generator for example) may be used for emergency situations or in case MGs are isolated.
• Loads. As highlighted by Gavilema et al. ^[14][30], loads, which are critical or not, can be classified into different categories: non-controllable loads, shiftable loads, controllable comfort-based loads and controllable energy-based loads.
• Energy storage systems (ESSs). ESSs—correct sizing of these systems is crucial ^[15][148]—are needed to store renewable energy, to perform load shifting or to assist during black starts ^[16][149]. In MGs, energy storage systems can either be mechanical, electrochemical or electrical ^[17][18][34,150].
• Electric vehicles (EVs). Because of an acceleration in the adoption of EVs, EV integration in a MG (or in a NMG) environment is critical. There is a need for efficient vehicle-to-grid technologies and optimization techniques.
• An energy management system (EMS). The EMS coordinates energy demand and supply between the dispatchable generators and the different loads, while aiming at the fulfilment of technical, economical, and environmental objectives. Supervisory control and data acquisition (SCADA) systems, which can help improving microgrids’ reliability, safety and economic benefits ^[19],Section 2.3). The EMS coordinare closely linked to EMStes energy demand and supply between the dispatchable generators and the different loads, while aiming at the fulfilment of technical, economical, and environmental objectives. Supervisory control and data acquisition (SCADA) systems, which can help improving microgrids’ reliability, safety and economic benefits ^[20]. If the EMS is a predictive one—i.e.[151], a predictive energy management system (PEMS)—a forecast module is involved to predict loads, power generation and energy prices, among the quantities of interest. Accurate forecasts are needed to achieve efficient flux management in MGs and NMGs ^[21]e closely linked to EMSs [13]. If the EMS is a predictive one—i.e., a predictive energy management system (PEMS)—a forecast module is involved to predict loads, power generation and energy prices, among the quantities of interest. Accurate forecasts are needed to achieve efficient flux management in MGs and NMGs [152].

According to the International Electrotechnical Commission (IEC), an energy management system is “a computer system comprising a software platform providing basic support services and a set of applications providing the functionality needed for the effective operation of electrical generation and transmission facilities so as to assure adequate security of energy supply at minimum cost” ^[12][32]. According to the International Organization for Standardization (ISO), “an energy management system involves developing and implementing an energy policy, setting achievable targets for energy use, and designing action plans to reach them and measure progress. This might include implementing new energy-efficient technologies, reducing energy waste or improving current processes to cut energy costs” ^[22][153].

EMSs have several functions among which data monitoring, data analytics, and real-time control. EMSs can also account for data uncertainties: for example, Carli et al. ^[23][154] propose an EMS based on a robust MPC approach, allowing the consideration of data uncertainties, to minimize the total economical cost, while satisfying comfort and energy constraints; Karimi and Jadid ^[24][155] propose a cooperative multi-objective optimization approach for energy management in NMGs, where the renewable generation uncertainty is modeled as a stochastic component. Benefits of EMSs are: power generation dispatch, reactive power support, detecting power quality problems, frequency regulation, energy savings, and reduction of carbon dioxide emissions, to name a few ^[12][25][32,156]. EMSs play a key role in the management of distributed generators and energy storage systems during grid-connected and islanded operation modes. Islanding is an interesting option in case of emergency, for example when an extreme climatic event occurs or if a cyber attack happens, or when power demand is too high and, as a result, consumers can be asked to disconnect from the main grid. In the first case, voltage or frequency is greatly affected ^[26][157]. When a fault is detected, smooth transition and synchronization between grid-connected and islanded operation modes has to be achieved ^{[27][28][29][30]}[1,119,158,159].

SCADA systems, which consist of both software and hardware components, first enable remote and on-site gathering of data. SCADA systems play also a key role in data visualization, storage, monitoring, and control ^[31][32][36,160]. In addition, SCADA systems can contribute to solving protection and communication issues ^[33][55]. A special attention is paid in ^[34][161] to security. A possible evolution path towards dynamic MGs is highlighted in ^[35][162], in the light of SCADA systems. In this context, new-generation peer-to-peer communication systems are needed. In addition, due to the cyber vulnerabilities introduced by digitalization and an increasing dependency on ICT systems, looking into MG security becomes crucial. One of the newest ways to solve security-related issues is through blockchain. Blockchain is a powerful trustworthy platform for peer-to-peer transaction based on distributed data storage, enabling to keep track of the exchanged data. A review of challenges and opportunities in the energy sector for blockchain is conducted in ^[36][163]. As highlighted in the literature, the decentralized structure of blockchain is particularly suitable for implementing control and business processes in MGs, using smart contracts and decentralized applications. In ^[37][164], an overview of projects and concepts in relation with blockchain applications in MGs is given. The authors conclude that the most promising use case from the MG perspective is peer-to-peer trading, where energy is locally exchanged and traded between consumers and prosumers. In ^[38][165], Canaan et al. address the existing approaches attending to cyber-physical security in MGs, including blockchain. In ^[39][166], the possibility of customizing blockchain technologies to satisfy socio-economic requirements of transactive energy management in NMGs is evaluated. In ^[40][167], an enhanced blockchain-based data management scheme for MGs is proposed. The aim is to counteract possible false data injection (FDI) attacks. In ^[41][168], a hierarchical bidding and transaction structure based on blockchain (HBTS) for MGs is proposed. The bidding strategy effectiveness is verified through experiments. In ^[42][169], a blockchain-based energy trading platform for smart homes in a MG is proposed.

In MGs, EMSs can be centralized, decentralized, distributed or hierarchical ^[43][29]. Hierarchical control ^{[44][45][46][47][48]}[120,170,171,172,173] is commonly used to manage MGs. It consists of different layers to ensure voltage/frequency stability, power sharing and optimal operation. Hierarchical control is defined as having the following four levels, from the fastest to the slowest level ^{[43][45][49][50][51][52][53][54][55]}[11,29,38,52,56,170,174,175,176]:

• Level 0, i.e., the inner loop control. This level, which consists of voltage and current loops, deals with managing the output power of renewable energy sources (operation time is in milliseconds).
• Level 1, i.e., the primary control. This level consists of an independent local control for increasing power reliability. It aims at stabilizing frequency and voltage using droop controllers ^[55][176] (operation time is in milliseconds to seconds).
• Level 2, i.e., the secondary control. This level deals with monitoring and supervising the MG in order to collect the necessary information from distributed generators and regulating these generators. It compensates the voltage and frequency steady state deviations caused by the primary control ^[55][56][176,177] (operation time is in seconds, minutes, even hours).
• Level 3, i.e., the tertiary control. This level, which deals with managing power fluxes, consists of an interface between the MG and the main grid. It takes into consideration economic factors and determines power flow between the MG and the main grid in order to achieve optimal operation or to minimize power losses when the MG is islanded ^[55][176] (operation time is in minutes, hours, even days).

For NMGs, in a centralized structure, all MGs are controlled thanks to a single energy management system, which optimize the operating costs of each MG through preventing load shedding of critical loads ^[12][27][1,32]. Although such an EMS has an uncomplicated implementation with acceptable reliability in islanded mode, it can lead to heavy costs as the structure requires communication infrastructures, and has low flexibility. In a decentralized structure, each MG is equipped with a local control center and operated independently of the other MGs ^[57][178]. A MG fulfills its generation and load balance through sharing energy with the main grid or other MGs in its vicinity. In islanded mode, the main objective of each MG is to maintain a reliable power supply to its customers ^[57][58][178,179]. A local generator may export electricity and will enter either in the competitive or collaborative mode with other local generators ^[12][27][1,32]. In comparison with the centralized structure, a decentralized EMS is well-suited to MGs. This kind of EMS, however, is highly dependent on the main grid in interconnected mode, which results in high operating costs. Moreover, such a structure is not beneficial and flexible in islanded mode. The centralized and decentralized approaches have different drawbacks. Centralized EMSs are easier to implement but are cost expensive (due to the communication structure) and difficult to manage ^[17][34]. In a decentralized approach, the MGs are more dependent on the main grid as local controllers do not communicate and the quantity of electricity bought from the grid is generally higher ^[17][59][34,180].

In order to tackle these drawbacks, distributed energy management systems have emerged ^{[8][59][60][61]}[82,180,181,182]. Distributed EMSs are defined as a combination of a number of local EMSs and a central EMS. Local EMSs optimize their own resources and inform the central EMS of their needs or if a surplus of energy is available ^[8][59][82,180]. Distributed EMSs have the ability to make mitigating operating cost savings. A central EMS along with local energy management systems perform scheduling, monitoring and rescheduling, and benefits distribution processes. In ^[8][82], a hybrid EMS based on canonical coalition games is proposed for cooperative power exchange management of NMGs.