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Power networks, especially distribution networks, have been undergoing substantial changes since the application of new technologies. Technology development in the early part of the 21st century has opened up new horizons for automated, efficient and reliable power grids. New technologies, while enhancing the capability of the electrical networks and providing opportunities and innovative solutions to the challenges of future networks, can also cause drawbacks that should be investigated and taken into account. Distributed generation (DG) is one of the new technologies that improves the operation of power grids. Despite tangible benefits that integration of DG units brings to electrical grids, their notable impacts on protection systems of power networks raise many challenges and concerns on how a fault should be detected and isolated in active distribution networks. Many attempts have been made to investigate the downside of the interconnection of DG units and methods to mitigate their impacts have been proposed. This study reviews the impact of DG integration on protection systems addressed in other research works and recapitulates suggested methods provided by scholars. [ABSTRACT FROM AUTHOR]

Increasing the penetration level of distributed generation (DG) units requires overcoming the technical challenges associated with their integration into the distribution systems, especially protection problems. Change in the current profile of the distribution system due to the presence of DG units disrupts the operation of the conventional fuse saving coordination (FSC) scheme. The first objective of this paper is to provide an overview of the state‐of‐the‐art of FSC schemes in distribution systems with distributed generators that has not been systematically presented yet. In addition to comparing the features of reliability, cost, speed, implementation, calculation burden, and requirements, the impact of presence of distributed generations on the performance of the conventional FSC scheme is investigated in details. The second objective of this paper is to propose an FSC restoration scheme for minimizing the challenges of previous works. Using a quasi‐voltage current term, the proposed scheme modifies the adjustable time coefficient of the recloser in two ways of pro and plus. The former scheme provides an approximate FSC with a simple setting while the latter scheme provides complete coordination at the expense of a more complex setting. No need for voltage measurement makes its implementation practical in available distribution systems. The effective performance of the proposed FSC scheme is verified through extensive simulation studies in the ETAP environment. [ABSTRACT FROM AUTHOR]

With the increasing integration of distributed energy resources (DERs) into distribution systems, the optimization of system operation has become complex, facing challenges such as inadequate consideration of market participants' benefits, poor computational efficiency, and data privacy concerns. This paper introduces the concept of a virtual power plant (VPP) as a solution for energy integration and management. To strike a balance between operational safety and the interests of market participants, a dual‐layer model is proposed. This model considers the benefits of both Distribution System Operators (DSO) and VPP, while also enhancing the consideration of distribution network constraints. The DSO considers AC optimal power flow and utilizes penalty functions to ensure network security in case of violations. To enhance computational efficiency and privacy, the paper presents the parameter‐sharing twin delayed deep deterministic policy gradient approach. This approach allows multiple intelligent agents to share a neural network model, effectively reducing the computational load. During the training process, only essential data is exchanged among the agents, ensuring the privacy of sensitive information. The effectiveness of the proposed model and the algorithm is validated through a case study on an IEEE 33‐node system. [ABSTRACT FROM AUTHOR]

This paper proposes a new multistage AC model for transmission expansion planning that finds an optimal combination of transmission lines, fault current‐limiting high‐temperature superconducting cables, and multiple distributed generations (DGs). On this basis, the proposed model, from a new perspective, allows for simultaneous improvement of the short‐circuit level and grid‐scale flexibility (GFLX) under both normal and fault conditions. The objective function to be minimized includes not only the net present worth of the total investment and operation costs but also the congestion‐induced GFLX degradation measure. This model also takes the AC power balance and flow relationships, equipment capacity limits, nodal voltage bounds, DG penetration level limit, as well as discrete logical and financial restrictions together into account with the short‐circuit level constraint. To overcome the complexity of solving the resultant non‐convex mixed‐integer non‐linear optimization problem, a multi‐objective integer‐coded melody search algorithm is employed, followed by a fuzzy satisfying decision‐making mechanism to obtain the final optimal solution. The exhaustive case studies conducted on the IEEE 24‐ and 118‐bus test systems verify the efficacy of the newly developed model in terms of cost‐effectiveness, flexibility, and short‐circuit level suppression when facing different normal and fault conditions. [ABSTRACT FROM AUTHOR]

Contemporary distribution networks can be seen with diverse dispatchable and non‐dispatchable energy resources. The coordinated scheduling of these dispatchable resources with non‐dispatchable resources can provide several techno‐economic and social benefits. Since battery energy storage systems (BESSs) and microturbine units are capital intensive. A thorough investigation of their coordinated scheduling on a purely economic basis will be an interesting and challenging task while considering dynamic electricity price and uncertainty of renewable power generation and load demand. This paper proposes a new methodology for optimal coordinated scheduling of BESSs and microturbine units considering existing renewable energy resources and dynamic electricity price to maximize daily profit function of the utility. In this study, a recently explored modified African buffalo optimization algorithm is employed. The key attributes of the proposed methodology are comprised of mean price‐based adaptive scheduling embedded within a decision mechanism system to maximize arbitrage benefits. Decision mechanism system keeps a track of system states as a‐priori thus guides the artificial intelligence‐based solution technique for sequential optimization. This may also reduce the computational burden of complex real‐life engineering optimization problems. Further, a novel concept of fictitious charges in coordination with BESS management algorithm is proposed to restrict the counterproductive operational management of BESSs. The application results investigated and compared on a benchmark 33‐bus test distribution system highlights the importance of the proposed methodology. [ABSTRACT FROM AUTHOR]

This paper presents an analysis of the fault current contributions of small‐scale single‐phase photovoltaic inverters under grid‐connected operation and their potential impact on the protection of distribution systems. To conduct this analysis, an autotransformer‐based voltage dip generator is proposed as a means to test the photovoltaic inverters' contribution to short‐circuit currents. Laboratory tests are then performed to obtain the short‐circuit current contribution of eight single‐phase photovoltaic inverters. Using the short‐circuit current data obtained, a behaviour model is developed and simulated on Matlab‐Simulink. The model is then applied to a real distribution system and case studies are conducted to simulate the potential impacts on the protection system. Results indicate that while the massive penetration of small‐scale single‐phase photovoltaic inverters can alter the protection system's operating time, the impacts are not significant. Only in very specific scenarios, such as events related to high impedance faults, some impact can be observed. In these situations, the presence of photovoltaic inverters further complicates the already difficult task of identifying high impedance faults through conventional overcurrent protections. This study provides valuable insights into the integration of photovoltaic inverters into distribution systems, and can aid in the development of effective protection measures for future grid designs. [ABSTRACT FROM AUTHOR]

Electric vehicles (EVs) charging swapping stations (CSSs), as well as multi‐functional integrated charging and swapping facilities (CSFs), have become important to reduce the impact of e‐mobility on the electric power distribution system. This paper presents a coordinated planning optimization strategy for CSSs/CSFs and active distribution networks (AND) that includes distributed generation. The approach is based on the application of a specifically developed spatial‐temporal load forecasting method of both plug‐in EVs (PEVs) and swapping EVs (SEVs). The approach is formulated as a mathematical programming optimization model that provides the location and sizing of new CSSs, the best active distribution network topology, the required distributed generation, and substation capacities. The developed model is solved using CPLEX, and its characteristics and performances are evaluated through a realistic case study. [ABSTRACT FROM AUTHOR]

This paper proposes three‐phase steady‐state models for distributed generators (DGs) with different negative control strategies. An augmented rectangular load flow method is used for three‐phase distribution systems. For two types of DGs with power electronic devices: photovoltaic power generators and doubly fed induction generators, the nodal voltage equations and output power equations are derived. Moreover, under unbalanced conditions, the strategies for mitigating the effects caused by negative sequence components are formulated as functions of the nodal voltage and the injected current. Furthermore, the models are incorporated into an augmented rectangular load flow method with nodal voltage and injected current as state variables in three‐phase systems. Case studies are conducted to verify the correctness and accuracy of the proposed models by comparing the results obtained from MATLAB and PSCAD. [ABSTRACT FROM AUTHOR]

The high penetration of distributed generation systems poses challenges in effectively managing both DC bus voltage and power‐sharing in DC microgrids (MGs). To ensure precise voltage regulation across various distributed generation systems and maintain overall system stability, this paper studies the modelling and control of an islanded DC MG described by a set of nonlinear‐nonaffine differential equations. In the proposed DC MG, a battery storage, a photovoltaic (PV) power plant, and a back‐end power converter with DC loads have been connected to a common DC bus. First, a dynamic model of a DC MG was developed. Then, to find the maximum power point of solar PV, a straightforward method based on an artificial neural net is employed. Afterward, a nonlinear local state feedback controller through output regulation theory is applied to achieve voltage stability, overcoming the drawbacks of droop‐based techniques. Moreover, partial state feedback capability simplifies controller design. To verify the effectiveness of the proposed approach, various scenarios, including sudden load variation, illumination change, and changes in the MG configuration, have been examined. Finally, numerical studies were carried out in a simulation environment to demonstrate the superiority of the proposed nonlinear control scheme over constant feedback control. [ABSTRACT FROM AUTHOR]

Driven by the demand for carbon emission reduction and environmental protection, battery swapping stations (BSS) with battery energy storage stations (BESS) and distributed generation (DG) have become one of the key technologies to achieve the goal of emission peaking and carbon neutrality. Therefore, this paper proposes a strategy to optimize the operation of BSS with photovoltaics (PV) and BESS supplied by transformer spare capacity. Firstly, it introduces the operation mechanism of BSS and uses the spare capacity of building special transformers and the roof PV to supply power to BSS to avoid the investment of transformers. Secondly, this paper establishes the load model of BSS and proposes the charging rules of battery swapping. Thirdly, a segmented pricing mechanism for the rental price of special transformers is formulated to guide BSS operators to preferentially rent spare capacity during low load rate periods. Aiming at the maximum daily profit of BSS, an optimization model is established to optimize the number of batteries to be charged and the charging status of BESS in each period; on this basis, the demand response model is further proposed. Simulation results show that the proposed strategy can improve the daily profit of BSS through shifting load. And the configuration of BESS can improve the battery swapping capacity and peak‐shaving ability. Moreover, the exponential segmented pricing mechanism can greatly reduce the number of high load periods and reduce the burden on the power supply. [ABSTRACT FROM AUTHOR]

The upcoming network investment decisions and regulatory framework adopted by distribution system operators (DSOs) are most likely to be impacted by the integration of fluctuating distributed generation. The economical hosting capacity (HC) improvement method is investigated in this paper as a trade‐off between curtailment and upgrade using a Monte Carlo simulation procedure. The associated costs of both methods are vital indicators for network operators that are trying to maximize the HC and minimize cost. In addition, the breakeven point where curtailment and upgrade costs intersect is the decisive point at which network upgrade becomes sensible as marginal curtailment cost exceeds upgrade cost. A shift in global climate conditions can impact the photovoltaic (PV) levels that motivate network operators to investigate PV penetration, especially in colder climate regions. Thus, the primary objective of this paper is to investigate the shift of the breakeven point to guide DSOs to either adopt PV curtailment as a temporary measure or grid upgrade as a risk aversion strategy considering Finnish climate and load patterns. The real‐time load and PV generation data are utilized for the simulations to consider the dynamic performance indication of three Finnish distribution networks. Curtailment remains a low‐cost option to obtain a percentage HC rise of 13%, 7%, and 8% for rural, suburban, and urban regions, respectively, beyond which curtailment compensation cost surpasses upgrade cost. In essence, PV curtailment serves as an immediate and least‐cost solution to relieve network violations and defer network investment until the HC level (118%, 106%, 97%) making the upgrade a practical option afterwards. [ABSTRACT FROM AUTHOR]

As an important form of renewable energy utilization, microgrid (MG) is considered to be the main bearing form of distributed generation in the future. One of the most concerning issues in the operation of MG is how to realize its economic dispatch (ED). Nowadays, distributed algorithms have been increasingly used to solve the economic dispatch problem of MG. However, the MG based on the distributed optimization architecture must bear higher cyber‐attack risks. To address this issue, this paper investigates the distributed robust ED problem of MG. Firstly, a multi‐objective dispatch model of MG using a linear weighted sum (LWS) algorithm is developed, which considers the environmental and economic costs. On this basis, an event‐triggered fully distributed algorithm is proposed, which can effectively reduce communication times. Furthermore, an attack resilient strategy against false data injection (FDI) attacks is implemented in the proposed fully distributed algorithm, which has strong robustness against various colluding attacks and non‐colluding attacks, and can eliminate incorrect measurement of incremental cost and power generation data. Finally, the effectiveness of the proposed distributed control strategy is demonstrated through case studies in this paper. [ABSTRACT FROM AUTHOR]

With the development of the energy structure of the power system, the characterization of the observed oscillation in the power system has steadily evolved. With the increasingly high penetration of distributed energy sources and power electronic devices, such as the photovoltaic, wind power and charging pile, the basic mechanism, frequency ranges and propagation of oscillation would become more dynamic and complex. Therefore, the traditional parameter estimation, as well as the suppression methods would also suffer from dynamic oscillations. To this end, this paper first investigates the oscillation propagation and typical events caused by the oscillations. Next, the oscillation model estimation method including the model‐based and data‐driven based methods is discussed. The benefits and difficulties of various parameter estimate techniques are highlighted. Under this context, the validity and limitations of the current power system stability are summarized. Furthermore, the different oscillation damping and mitigation measures are compared, and the major adaptability and limitations are listed for the specific application scenarios. Conclusions are drawn, and the wideband oscillation becomes the future research objective where the future work is presented at the end of the paper. [ABSTRACT FROM AUTHOR]

Microgrids are a new concept resulting from decentralized power sources, which have changed energy utility grid topography. As this promising field is penetrated, control must be streamlined immediately. This paper analyses key control mechanisms in energy utility networks, including centralized, decentralized, and distributed setups. The focus is on the auxiliary category as the various benefits and drawbacks of each approach is investigated. Information interchange architectures that enable multiple control techniques in the auxiliary control domain are examined using distributed energy networks. The research emphasizes the necessity of auxiliary control in ensuring reliable and effective utility infrastructure operation but notes the lack of a comprehensive scholarly reference. Additionally, the study explores key concerns in utility grids' auxiliary control mechanisms, emphasizing information‐sharing system limits. The goal is to demonstrate the importance of auxiliary control and evaluate its challenges, such as latency, which require new solutions for a seamless transition to a sustainable energy future through rigorous academic assessment. At the auxiliary level, complex, decentralized regulatory mechanisms are recommended to handle transmission channel bandwidth and operational overhead in energy utility networks. These innovative measures have the potential to transform the fundamental structure of our energy landscape, heralding in unprecedented efficiency and sustainability. [ABSTRACT FROM AUTHOR]

DC microgrids (DCMGs) have significant advantages, but their protection can be a challenge for DCMGs expansion expressly in distributed generation sources' (DGS) tendance. This paper proposes a quick, and precise strategy to perceive and trip any fault in DCMGs in the free tendance of DGS. A bi‐level multi‐agent system (MAS) is proposed to protect the DCMG and DGs. The MAS first level perceives the fault in DCMG via a discrete wavelet transform (DWT). The multiply of two harvest levels' summation of DWT is exerted to detect and distinguish DC lines faults. The MAS second level detects the fault in DGS and their switchers to the point of common connection (PCC) via a differential pole (DP) controller. A four bus DCMG containing solar PV and wind sources is implemented, and the results demonstrate that the proposed plan can recognize and trip the fault by 100% of reliability. [ABSTRACT FROM AUTHOR]

Integration of Distributed Energy Resources (DERs) in power systems exacerbates the existing information problems between power utilities and regulators. DER policies oblivious to the trilemma of information asymmetry between power utilities, DER aggregators, and regulators result in distorted price signals to DER investors, and socially inefficient DER roll‐out. Therefore, in this paper, a game‐theoretic approach is proposed for modeling information asymmetry in distribution network information and consumer data between the DER aggregators and the power utilities. The proposed framework is based on Single Leader Single Follower (SLSF) games, reformulated as Mathematical Programs with Equilibrium Constraints (MPECs), and solved using the Scholtes's relaxation technique. The results, based on the 7‐bus Manhattan power network, show that unless the DER aggregators have complete information about the distribution network characteristics, the welfare along with the realized installed capacity of DERs in the system decreases. Moreover, progressively decreasing DER investment costs alleviate the effects of information asymmetry, suggesting that early adopters face disproportionately high welfare losses attributed to incomplete information between the DER stakeholders. Hence, policy interventions to alleviate the rampant information problems are imperative to ensure an optimal DER roll‐out. [ABSTRACT FROM AUTHOR]

This paper presents a two‐stage adaptive robust optimization framework for day‐ahead energy and intra‐day flexibility self‐scheduling of a technical virtual power plant (TVPP). The TVPP exploits diverse distributed energy resources' (DERs) flexibility capabilities in order to offer flexibility services to wholesale flexibility market as well as preserving the distribution network's operational constraints in the presence of DER uncertainties. The TVPP aims at maximizing its profit in energy and flexibility markets considering the worst‐case uncertainty realization. In the proposed framework, the first stage models the TVPP's participation strategy in day‐ahead energy market and determines the DERs' optimal energy dispatch. The second stage addresses the TVPP's strategy in intra‐day flexibility market to determine the DERs' optimal flexibility capability provision by adjusting their energy dispatch for the worst‐case realization of uncertainties. The uncertainty characteristics associated with photovoltaic units, electric vehicles, heating, ventilation and air conditioning systems, and other responsive loads as well as the transmission network's flexibility capability requests are considered using an adaptive robust approach. Adopting the duality theory, the model is formulated as a mixed‐integer linear programming problem and is solved using a column‐and‐constraint generation algorithm. This model is implemented on a standard test system and the model effectiveness is demonstrated. [ABSTRACT FROM AUTHOR]

Large‐scale integration of distributed generation and widespread use of power electronic equipment make power quality disturbances (PQDs) more complicated. There are still unsolved problems for the classification of multiple power quality disturbances (MPQDs) that consist of various kinds of single disturbances: (1) since the difference between the contribution degrees of every contained single disturbance to the composite disturbance is ignored, the logical labels cannot completely describe the composite disturbance; (2) the optimal feature in one granular space may not be optimal in another. These drawbacks lead to the degradation of MPQD classification, which should be considered a multi‐label model rather than single‐label model used in existing methods. Therefore, this paper proposes a novel method to improve the classification performance of MPQDs. The label distribution, representing the contribution degree of a single disturbance to the composite disturbance, is introduced. In addition, the high‐dimensional feature space is reduced by multigranular optimization, where the fuzziness and redundancy are removed by the modified rough‐set method. To improve the performance of the classifier, the ensemble classification model based on homogeneous classifier integration is proposed to integrate the base classifiers constructed by the feature vectors from different granularity spaces. A large number of field recordings are applied to validate the proposed method. The results show that the proposed method performs better than traditional methods, especially under noisy environments. [ABSTRACT FROM AUTHOR]

The access of large‐scale distributed generation (DG) easily leads to energy imbalance in distribution network. To deal with this issue, this paper proposes an energy optimal schedule method for distribution network considering the participation of source‐load‐storage aggregation groups (SAGs). Firstly, the system model consisting of distribution network layer and SAGs layer is established, and the schedule objectives and constraints of each layer are also given. Secondly, considering the fluctuation on the load side, a forecasting method based on Adaboost integrated convolutional neural networks and bidirectional long‐short term memory is proposed. Then, the improved sparrow search algorithm (ISSA) is proposed by using the tent map and Levy flight on the original sparrow search algorithm. At the same time, by introducing Pareto dominance relation and adaptive grid algorithm, the multi‐objective sparrow search algorithm (MOSSA) is derived. After that, a two‐layer optimization framework (ISSA–MOSSA) is proposed to solve the studied system. The simulation results verify the accuracy of the proposed load forecasting model, the superiority of ISSA as well as MOSSA, and the effectiveness of ISSA–MOSSA in solving the energy optimal schedule problem of the distribution system with the access of DG. [ABSTRACT FROM AUTHOR]

The distribution system's economic operation is significantly impacted by the management of distributed generation (DG) resources, energy storage (ES), and controllable loads. The paper employs a smart distribution system that incorporates dispatchable and non‐dispatchable DG resources, as well as battery storage, in addition to the demand response (DR) scheme. New modelling was performed in hourly steps to achieve the optimal unit commitment. In smart homes, appliances are prioritized and classified into four types: adjustable, interruptible, shiftable, and uncontrollable loads. Load reduction in smart homes is also considered based on load prioritization and customer participation in the DR scheme to achieve the proposed scheme's objectives. The proposed method considers costs associated with microturbines (MTs), including manufacturing, start‐up, shutdown, and pollution. Additionally, planning is conducted to purchase or sell electricity to the upstream network. The simulation is run on an IEEE 33‐bus system to demonstrate the proposed method's effectiveness. The system is assumed to be capable of operation in both island and grid‐connected modes. The results demonstrate the proposed approach's efficacy in load reduction, operation cost, and execution time. [ABSTRACT FROM AUTHOR]

The present paper introduces an analytical approach for integrating distributed energy resources (DERs) and battery energy storage systems (BESSs) into power grids. The given method aims to simultaneously identify optimal buses and capacities of DERs and BESSs, with regard to the responsive load demand along with the stochastic nature of wind turbine (WT) and photovoltaic (PV) units, and then to minimize energy losses and improve voltage profiles. For this purpose, the responsive load model, the uncertainties in the WT and PV units, and the BESSs are firstly modeled. Secondly, the output curve of BESSs is obtained so that demand and supply can be balanced effectively, so as to utilize the full‐potential output of DERs. Thirdly, a set of formulation is developed for simultaneous integration of the DERs and the BESSs. This formulation reflects on different levels of loads and DERs for each period as well as each segment with their corresponding probability density. Finally, the proposed method is tested on the standard IEEE 33‐bus network. These results verify that sizing and sitting of DERs and BESSs can significantly shape the planning results of DERs and increase their penetration in the power grids at the same time. [ABSTRACT FROM AUTHOR]

Despite improving various technical indices such as operation and voltage profile, the integration of synchronous distributed generations (SDGs) may lead to the loss of protection coordination in the distribution network (DN). To tackle the problem, this paper presents a multi‐objective siting and sizing of SDGs on DN considering operation, economic and protection coordination indices simultaneously. The proposed scheme is structured in the framework of a four‐objective optimization problem, which aims to minimize the energy losses, the worst voltage security index (VSI), planning cost of SDGs and the protection index (PI) (the deviation of coordination time interval). Therefore, it is constrained to power flow equations, VSI, and protection coordination of overcurrent relays (OCRs). Then, the Pareto optimization based on the method of the weighted functions summation obtains an integrated single‐objective problem for the proposed scheme. Next, a hybrid evolutionary algorithm formed by merging particle swarm optimization (PSO) and crow search algorithm (CSA) is incorporated to achieve the optimal solution with unique response approximate conditions. Eventually, the suggested scheme is applied on distribution portion of IEEE 30‐bus ring and IEEE 69‐bus radial DN and numerical results confirm the efficient performance of SDG planning in terms of technical indicators and protective devices coordination. [ABSTRACT FROM AUTHOR]

With the high penetration of distributed generation and gradual increase in loop network structures, existing over‐current protection in distribution networks is difficult to apply. The use of current differential protection has become an ideal solution, and high performance and commercialization of 5G communication provides an effective way to solve the problem of differential protection channel transmission. Aiming at distribution network differential protection based on 5G, this paper adopted an adaptive frequency conversion transmission mechanism to significantly reduce the data flow of differential protection. In terms of protection strategy, the differential allowable signal and the differential protection startup logic are separated, and a novel action method and protection logic suitable for weak infeed distribution networks are proposed. The strategy significantly shortens the protection action time under wireless communication. Furthermore, a comprehensive synchronization scheme using zero‐crossing synchronization of forward sampling points and cycle numbers based on the second pulse signal was established. This scheme can effectively improve the reliability of data synchronization for differential protection. Finally, the method proposed in this study was verified using the dynamic model experiment of real‐time digital simulation (RTDS). [ABSTRACT FROM AUTHOR]

This paper proposes an intelligent approach based on the empirical Fourier decomposition (EFD) to identify harmonic sources at the point of common coupling (PCC) when different inverter‐based distributed generations (DGs) like microturbine (MT), battery energy storage system (BESS), photovoltaic (PV), superconducting magnetic energy storage (SMES), wind turbine with a permanent magnet synchronous generator (PMSG), and doubly‐fed induction generator (DFIG) wind turbine are presented. In order to decrease memory storage and computational burden, strife feature selection is used. Applying just voltage signals consumes less processing time and decreases measurement devices. Moreover, the whale optimization algorithm (WOA) as the optimizer of the parameters of the support vector machine (SVM) classifier is used. Consequently, the results from the proposed method can be helpful for both engineers and researchers to plan and develop a better strategy to mitigate harmonic distortion. [ABSTRACT FROM AUTHOR]

This paper presents an optimal bidding strategy for a technical and commercial virtual power plant (VPP) in medium‐term time horizon. A VPP includes various distributed energy resources (DERs) that can participate in the Pool and Futures markets. Although medium/long‐term scheduling provides the opportunity to participate in the futures market, it also raises the possibility of unit failure. In this regard, the impact of distributed generation (DG) units' failure, as an important challenge in VPP, is incorporated in the proposed model. The model is formulated as a risk‐constrained two‐stage stochastic problem. The VPP signs futures market contracts in the first stage, and in the second stage, it participates in the day‐ahead (DA) market and manages its DERs. Long short‐term memory neural network and scenario generation and reduction methods are used to capture the uncertainty parameters of electrical load, DA market prices, wind speed, and solar radiation in the proposed model. The performance of proposed model is investigated in different cases. The obtained results show that the VPP can compensate the losses caused by the DG units' failure through taking advantage of the arbitrage opportunity. [ABSTRACT FROM AUTHOR]

Presenting cloud energy storage system (CESS) in the landscape of storage devices exposes microgrids (MGs) to a substantial change. Employing a specific type of inverter namely synchronverter as the connecting interface for CESS gains high inertial response in MGs with high penetration level of inverter‐based distributed generations (IBDGs). However, high fault contribution of synchronverters can lead to challenging issues. Nevertheless, presence of fault resistance which results in malfunctioning of the recloser‐fuse pair intensifies the cruciality of the dilemma. In this paper, at the outset, the effects of contribution of synchronverter‐based CESS and also fault resistance on recloser‐fuse protection are explored and then, a new algorithm is proposed for tackling these bottlenecks. To overcome these hurdles, the conventional recloser‐fuse scheme is applied at first. Then, by using the obtained schemes for fast and slow operations of the recloser, a specific part of them is set in a manner that the fuse‐saving task is performed properly even when the synchronverter‐based CESS is deployed. On the other hand, the other part of the recloser scheme is altered in a way that the maloperation of the recloser‐fuse pair owing to the fault resistance is alleviated. Adequate numerical analyses are conducted to evaluate the proposed scheme. [ABSTRACT FROM AUTHOR]

Energy storage devices become an indispensable part of modern power systems with high renewable energy penetration level. To reduce the operating costs, it is a promising way to allow the sharing and leasing of energy storage devices. In this paper, a bi‐lever optimized dispatch scheme is proposed to improve the usage efficiency of cloud energy storage in multi microgrids (MMG) system. Minimizing the operating costs of shared cloud energy storage is the main task of the upper lever while maximizing the profits of MMG is the goal of the lower lever. Moreover, the transaction cost and benefit between the two levers play an important role in system level optimization. This leads to a hybrid optimization problem with both discrete decision variables and continuous decision variables. To solve the problem, a relaxation‐based bi‐lever reformulation and decomposition algorithm is developed. The effectiveness of the proposed bi‐lever dispatch optimization model is verified by carrying out numerical experiments in three scenarios. It is shown that the proposed cloud energy storage service can effectively reduce the operating cost of MMG. [ABSTRACT FROM AUTHOR]

The locational marginal price (LMP) theory is the foundation of nowadays electricity markets. With the rapid growth of intermittent renewable generation, new features are emerging in power systems, such as the uncertainty of power supply, the scarcity of flexibility, and the increase of distributed generation. In this situation, the electricity pricing scheme needs to be augmented with new features to meet requirements of incentive compatibility, cost causation‐awareness, revenue adequacy, and transparency in a new market environment. Though a broad spectrum of literature has investigated extensions of the LMP addressing different challenges, a panorama of these extension directions is absent. To this end, this paper provides a systematic review of existing LMP extension research from four aspects, including pricing with non‐convexity, pricing with multiple intervals, pricing with uncertainty, and pricing in distribution systems. These extension directions are derived from the impacts of the power system evolution on dispatch and pricing models. For each extension direction, the motivation and basic problem setup are introduced, followed by a critical survey of related research progress. Future directions and research gaps of the LMP extension are also indicated in this paper. [ABSTRACT FROM AUTHOR]

Growing penetration of distributed energy resources (DER) leads to emerging changes and issues in future power systems. A system oprator aims to maximise demnad side energy trading while minimising energy improts from upstream grid. This paper proposes a reliable local energy market (LEM) trading mechanism in which consumers and prosumers can trade self‐produced energy in a multiple community‐based market (MCBM) framework to optimally provide the balance. The proposed framework intends to maximise social welfare by fair allocation of resources, increasing the provided reserve for the main grid, and shaving the peak power resulting in enhancement of network flexibility. The overall model is formulated in the style of a bi‐level problem in which the lower‐level clears the market and the upper‐level is designated to redistribute the costs and benefits among market participants. Furthemore, the conditional value at risk (CVaR) approach is employed to evaluate how risk affects social welfare. Moreover, the impact of multiple communities and joint energy trading on the outcomes of the market is examined. The proposed model has been evaluated by analysing IEEE 33‐bus standard test system, and numerical studies verify the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

Reduced rotational inertia in power grids due to increasing penetration levels of distributed generations (DGs) may lead to degraded performance of the traditional frequency control scheme. In response to this challenge, inertia adequacy has recently emerged as a new research area in modern power systems. Accordingly, an attempt is made in this paper to tackle inertia adequacy in the generation expansion planning (GEP) problem. This in turn helps to realize sustainable economic development. For this purpose, the inertia adequacy constraint is tied to the frequency stability metrics. In other words, minimum permissible inertia that satisfies frequency dynamic standards is defined as an inertia adequacy constraint in the GEP formulation. Further, an experimentally validated model of a cluster of DGs is employed to realize a penetrated power grid to deal with sustainable planning development. Finally, an iterative‐based algorithm is proposed to expand the system with minimum cost and with the highest permissible penetration level of DGs. The effectiveness of the proposed algorithm is examined in the Garver test system. [ABSTRACT FROM AUTHOR]

A virtual power plant (VPP) is a solution that brings distributed generation (DG) resources together and allows them to be optimally utilized to meet load demands in the presence of technical and pollution constraints. Electricity, heat, and natural gas are interdependent at the levels of generation, transmission, and consumption, and the interactions of these energy sources need to be considered. This paper presents an optimal model for daily operation of a multi‐energy virtual power plant (MEVPP), including electric, thermal, and natural gas sectors. MEVPP includes small‐scale gas‐fired and non‐gas‐fired DGs, combined heat and power (CHP), power to gas (P2G), boilers, electrical storage, electric vehicles (EV), and thermal storage. Renewable energy resources (RES), including wind turbines (WT), photovoltaic (PV), and PV‐thermal (PVT), also supply P2G technology. Smart grid technologies such as price‐based demand response (PBDR) and incentive‐based demand response (IBDR) are employed for electric loads. The proposed MEVPP model is eligible to participate in day‐ahead electricity, natural gas, heat markets, and electrical spinning reserve market. The scheduling model is multi‐objective to maximize MEVPP profit and minimize carbon dioxide emissions. The Epsilon constraint method is utilized to solve the problem, and the best Pareto point is chosen using the fuzzy satisfying approach. [ABSTRACT FROM AUTHOR]

In recent years, microgrids (MGs) have attracted much attention from researchers due to the aggregation of distributed generation (DG) sources for visibility purposes, proper connection of these DGs and the power system, as well as more efficient control of the sources. However, high reliance on communication networks makes MGs vulnerable to deliberate cyber‐attacks. Also, since the basis of attack detection is to process monitoring and state estimation of the system, this paper presents a Kalman filter (KF) algorithm to monitor the network while modelling MGs in the state space. Moreover, as uncertainty and disturbance are two critical challenges in modelling and estimating states of a system, robust detection of cyber‐attacks along with separation of the effect of disturbances and uncertainties are of particular importance. Therefore, in this study, a novel attack reconstruction algorithm is designed using a combination of an unknown input observer method and KF for robust attack detection. Simulation results show excellent performance of the proposed approach in detecting, identifying and neutralizing the effect of cyber‐attacks in the presence of disturbance and noise. [ABSTRACT FROM AUTHOR]

With the development of electric energy substitution technologies such as electric auxiliary heating, the relationship between electric energy and thermal energy is getting closer, and it is of great significance to in‐depth study of integrated energy micro‐grids containing electricity and heat. However, the integrated energy microgrid power flow (PF) model has non‐smooth characteristics such as distributed generations (DGs) limits, converter stations limits and the unknown direction of pipeline mass flow, which can easily lead to the failure of PF convergence. This paper establishes an integrated energy microgrid model including three‐phase unbalanced AC/DC hybrid microgrid and heating system. Firstly, the correctness of the converter station model is verified by electromagnetic transient simulation, and then the non‐smooth constraint models considering DG and converter station's reactive power limits and pipeline mass flow direction unknown are established based on complementary constraints, and the non‐smooth constraints are smoothed by Fischer‐Burmeister (FB) function. Finally, the integrated energy microgrid is used for PF analysis, and the results verify the rationality of the model and the effectiveness of the proposed non‐smooth characteristics treatment method. [ABSTRACT FROM AUTHOR]

This paper explores the procurement of flexibility services in the power system by the collaboration between transmission system operators (TSO) and distribution system operators (DSO) in the day‐ahead market (DAM). With the coordination and interaction among the operators, the existing flexibility sources in transmission and distribution levels are exploited efficiently to procure flexibility services. For motivation of the distributed generation (DGs) sources and microgrids (MGs) to provide flexibility services, DSO aggregates the flexible sources of its grid and offers them to the upstream market. Doing so addresses the TSO uncertainties and improves the flexibility of the entire grid. The simulation results suggest the increased market efficiency and reduced operating costs for transmission and distribution levels using flexible sources. Furthermore, the results demonstrate that utilization of existing flexible sources in the distribution grid enhances the flexibility of the entire system and, consequently, increases the absorption from renewable energy sources (RES). Also, the flexibility procurement for DSO is associated with an increase in revenue and motivation of MGs. An examination of the impact of MG's ownership on the market clearing mechanism is also investigated in this regard. Finally, the reserve affects the system's flexibility. This effect is helpful for flexible systems while reducing the flexibility metrics for inflexible systems. [ABSTRACT FROM AUTHOR]

The complexity of the design of the protection system using directional over current relays, for modern power distribution systems has been increased due to the looped/meshed operation and the penetration of distributed generations. Finding a reliable and efficient protection scheme that can be easily implemented in these distribution systems is a major challenge. An efficient solution could be the use of artificial intelligent‐based multi‐agent systems. This paper proposes a novel distributed intelligent based multi‐agent protection scheme, which makes use of current‐only directional over current relays as agents for detecting and locating faults and isolating faulty areas (lines/busbars) in the distribution systems. All agents can make on‐board decisions by exchanging binary data, and do not need a control centre, so the safety of the protection system against one‐point failures and cyber‐attacks is increased. The proposed scheme does not need to exchange analogue data, and, therefore, it prevents the high bandwidth communication links. Moreover, it is free from the traditional coordination between relays. This scheme is implemented on the IEEE‐14 bus and IEEE‐30 bus test systems with the distributed generations and several scenarios have been simulated to evaluate its performance. [ABSTRACT FROM AUTHOR]

Despite various advantages of integrating distributed generation (DG) units into distribution networks such as power loss reduction and voltage profile improvement, they may disrupt the performance of the conventional protection system due to bidirectional power flow and change of short‐circuit power. With the development of multi‐agent systems (MASs), intelligent protection schemes have been introduced that operate on the basis of data processing by a central controller. However, the possibility of communication failure and cyber attacks reduce reliability of these protection systems. To address this problem, this paper proposes an intelligent protection scheme that relies on peer‐to‐peer communication between agents in the first layer of the MAS. In the case of communication failure, the agents react to the fault condition by using the available data for similar conditions. The main advantages of the proposed scheme are reduction of number of employed agents by using only relay agents and no need for communicating with higher layers of MAS. Implementation of the proposed scheme in the ETAP simulation model of a 14 bus active distribution network shows that data exchange between relay agents properly modifies the operating time of the relays, resulting in protection coordination between main and backup protections. [ABSTRACT FROM AUTHOR]

This paper investigates stability of a DC microgrid with integrated constant power loads (CPLs). The investigation is based on an interconnected model of the DC microgrid with two subsystems. One subsystem consists of a CPL under examination and the other subsystem is constituted by remainder of DC microgrid (ROM). Analysis is carried out to indicate when an oscillation mode of CPL subsystem is in the proximity of an oscillation mode of ROM subsystem on complex plane, stability of the DC microgrid decreases as caused by the CPL, leading to growing oscillations in the DC microgrid in the worst case. Hence, the investigation reveals the mechanism about why the CPL may cause instability of DC microgrid from a new perspective of modal proximity. An index is proposed to detect the instability risk by applying the modal analysis to subsystems. The proposed application extends the merit of widely used frequency‐domain analysis to the modal analysis, because instability danger can be detected by the proposed modal analysis in practice without having to establish parametric model of the DC microgrid. Two example DC microgrids with CPLs are presented to demonstrate and evaluate the analysis and conclusions made in the paper. [ABSTRACT FROM AUTHOR]

Classic droop control ensures the synchronization of distributed generation (DG) units inside a microgrid without requiring any deployment of communication links, however it causes unwanted frequency fluctuations and degrades system dynamics. Angle droop control and V−I control have been developed as two major global positioning system (GPS)‐based control methods, both of which realize a fixed‐frequency operation of the microgrid through synchronizing DG units with GPS timing technology and brings improvement to the dynamic response of the overall system. This paper reveals the similarities and the correlations between these two methods that they can both be regarded as different forms of virtual impedance control. A novel adaptive virtual impedance control method is proposed accordingly to generalize GPS‐based control strategies into a unified control frame. An impedance and inner controller design approach considering both stability constraints and power quality requirements based on the small‐signal model of GPS‐based microgrids is presented for practical implementation. An adaptive transient resistance concept is adopted to enhance the system stability during large disturbances and grid faults. Case studies are presented to validate the system performance and fault ride‐through abilities of the proposed control scheme. [ABSTRACT FROM AUTHOR]

The motivation of this paper is to introduce a new Hebbian least mean square control algorithm for two level self‐supported voltage source converter based distributed static compensator. The Hebbian least mean square controller is employed on the various aspects such as, weight updating, direct and quadrature unit voltage template, active and reactive part of reference supply currents and switching signal generation. Firstly, a set up equations using Hebbian least mean square are premeditated to compute both active and reactive weight updating. Secondly, DC and AC proportional integral controller outputs are involved with the updating weight to generate the reference supply current. The error signal obtained from both reference and actual source current is processed through the hysteresis current controller for the gate signal firing. The MATLAB/Simulink results as well as experimental results prove that the proposed algorithm is competent to afford the better voltage regulation, voltage balancing, source current harmonic reduction and power factor correction. Finally, performance obtained from the proposed controller reveals the applicability for various loading condition in the distribution grid. [ABSTRACT FROM AUTHOR]

Generation maintenance scheduling (GMS) is an important factor that can improve the reliability of power systems and decrease revenue achieved by generation companies (GenCos). Several GMS models, therefore, are based on these two crucial values. Nonetheless, there is no GMS problem that simultaneously considers unexpected failure of distributed generator (DG), financial return of GenCo, and reserve of system. This paper proposes the GMS model based on a global criterion approach to compromise functions that maximise the GenCo's annual return and probability that no DG fails unexpectedly. The system reserve (SR) is considered as a reliability constraint, while surplus reserve is exchanged with the main grid. To support alternative energy sources that have uncertain outputs and ensure continuous operation of DG, short‐term GMS model including power from wind farm, photovoltaic system, energy system storage, and demand response (DR) is also run by adding the SR and inconstant cost of DR. Effectiveness of the proposed model is examined using the IEEE 6 and IEEE 18‐bus test systems. Results show that not only the proposed model provides a better GMS solution for the GenCo, resulting in appropriate values of the two objectives, but also alternative energy sources are useful for the short‐term GMS. [ABSTRACT FROM AUTHOR]

A cluster with multiple AC or DC microgrids (MGs) based on flexible DC interlinking and distributed energy storage systems is studied in this paper, which has been identified to have the following issues in terms of its primary control scheme: coordinated power control among slack terminals in the MG cluster, seamless operation mode transition for the interlinking converters and the common DC bus voltage control. A novel flexible control scheme that unifies the control of all the MGs only using local measured signals without further communications is proposed in this paper, which aims to improve control stability, and operation reliability and flexibility. Theoretical introduction and analysis are presented to explain the proposed control. The detailed average value model and small‐signal model of an MG cluster with two AC MGs and two DC MGs are simulated, respectively, with the proposed control in power systems computer‐aided design/electro‐magnetic transient design and control to verify the effectiveness in control stability and flexibility enhancement, and the impact of control parameters on the small‐signal stability of the considered cluster is analysed through root locus. [ABSTRACT FROM AUTHOR]

In the literature, many works detail the benefits of Volt‐VAr control to minimise the losses in a distribution system. However, it is also important to understand the impact of it on the life of the other assets in a distribution system. Since, distribution transformers (DTs) are the important assets of a distribution system, the main objective of this paper is to appraise the impact of Volt‐VAr control on the life of DTs. The paper presents a detailed methodology to estimate the loss of life (LoL) of the DTs under various Volt‐VAr control schemes, such as base‐case (without any control), voltage control, and Volt‐VAr control (VVC). The proposed methodology is implemented on modified IEEE 13‐bus and IIT‐Roorkee distribution systems considering the voltage‐dependent load models, seasonal load influences, and harmonics. The simulation results are presented to explore the ability of VVC in reducing the hottest‐spot temperature in the DTs during peak hours. The results reveal that the life of the DT can be extended by a considerable amount by optimally controlling the voltages and reactive power flows in the distribution system. Moreover, it gives a significant reduction in energy losses and improvement in power factor in distribution systems. [ABSTRACT FROM AUTHOR]

This paper proposes a novel method for quantifying fault level in future grid scenarios with various penetrations of power electronics‐connected renewable energy sources. As it is known, the information regarding the fault level is critically important for designing protection schemes, different control loops, understanding voltage profile in the grid, etc. This method is focused on the steady‐state fault level calculation and it can be used to analyse future grid scenarios including uniform and non‐uniform penetration of power electronics‐based generation displacing all, or just specific conventional synchronous generation in the grid. Due to different possibilities for type, size, and location of power electronics‐based RES generation in future grid, it is required to analyse the unprecedented scale of scenarios. The proposed method for FLC enables us to assess the system fault level for large numbers of FG scenarios without a need for detailed system modelling and/or time‐domain simulations. The simulation results demonstrated the suitability of our proposed FLC method for various penetration levels of PE‐based RESs in the 2‐area and the IEEE 39‐bus test systems. The obtained results are compared with time‐domain simulations and the IEC 60909 standards performed in DIgSILENT PowerFactory, where the efficacy of the proposed methodology is demonstrated. [ABSTRACT FROM AUTHOR]

Unlike traditional microgrids, Provisional Microgrid (PMG) utilizes only renewable generation and small energy storage units; thus, it does not have an inherent self‐islanding capability and instead, relies on importing power from any coupled microgrid (CMG) for islanding purposes. Therefore, assuring adequate power sharing between interconnected provisional and coupled MGs is crucial for assuring self‐islanding capability and reliable operation. The optimal power that can be transferred between the coupled MG and the PMG is mainly restricted by the size of the interconnecting tie‐line; hence, determining the tie‐line optimal size becomes a crucial task that must be tackled. Furthermore, the amount of power transferred is significantly influenced by the flexibility level of each microgrid. Since battery storage systems (BSS) is the main source of flexibility in PMGs, it becomes also vital to obtain the optimal size of the BSS for planning islanded PMG system. This paper presents an optimization model to jointly determine the optimal size of the BSS in each MG and the tie‐line size to assure optimal power sharing and minimum system cost (tie‐line investment cost, BSS investment cost, and interconnected system's operation cost). Numerical results demonstrate the effectiveness of the proposed model. [ABSTRACT FROM AUTHOR]

Microgrid inverters in the presence of faults, unavoidable modelling uncertainties, disturbance and harmonic current resulting from nonlinear loads should have small steady state tracking error, small THD and high robustness hence this subject has turned one of the motivations of this investigation. To achieve the stated goals, fractional adaptive sliding mode controller (FASMC) is proposed in this paper. The proposed controller increases the robustness, flexibility and degree of freedom. As far as in practice it is not easy to define the bounds of disturbances and guarantee the system stability, hence in next step, to overcome this challenge the adaptation laws are suggested. Then for the problem of determining the controller parameters, Particle Swarm Optimization (PSO) algorithm is used. The performance of the proposed technique is investigated for an islanded microgrid under different disturbances, also to verify the advantages of the proposed controller, the results are compared with other controllers. Finally, the proposed controller and PID controller are implemented experimentally on Arduino mega 2560 microcontroller. [ABSTRACT FROM AUTHOR]

With the integration of more and more renewable energy generations (REGs), the structure of traditional distribution networks is hard to accommodate the volatile power injections of REGs. As a new power electronic device, soft open point (SOP) can be installed to control both active and reactive power flow among active distribution networks (ADNs). This paper presents a comprehensive optimization method for allocating SOPs within an ADN with high penetration of REGs. In order to find proper SOP candidate locations, a selection strategy based on two technical indices is proposed. To mitigate the risk of voltage violation caused by REG forecast errors and improve the adaptiveness of allocation results, a two-stage robust optimization model for SOP allocation is formulated to minimize the total cost of SOP investment and network operation. The proposed model is converted into a mixed-integer second-order cone programming (MISCOP) problem, which is then decoupled into a master problem of planning and a subproblem of operation and solved by column and constraint generation (CCG) algorithm. Simulation results show that the proposed method can effectively find the optimal SOP allocation schemes. Comparisons with different mathematical formulation and solution methods show the advantages of the proposed method. [ABSTRACT FROM AUTHOR]

This paper investigates the false data injection attacks (FDIA) in an AC smart island and the detection solution of the attack on distributed energy resources in a smart island. In this study, a new scheme of FDIA detection is proposed based on wavelet singular values as input index of deep learning algorithm. In the proposed method, switching surface based on sliding mode control breaks down for adjusting accurate factors of wavelet transform and then features of wavelet coefficients are extracted by singular value decomposition. Indexes are determined according to the wavelet singular values in switching surface of voltage and current which defines the input indexes of deep machine learning and detecting FDIA. This cyber‐protection plan has been put forward for cyber diagnostic and examined in different types of attacks happening in voltage and current signals derivation of measuring sensors as well as sending and receiving data from communication and control systems. The main priority of the suggested detection plan is the high capability to detect FDIA with a high accuracy. To show the effectiveness of the proposed method, simulation studies are performed on AC smart island in MATLAB/Simulink environment. [ABSTRACT FROM AUTHOR]

This paper proposes a load control module based on the consumers' vulnerability indices to improve the ability of radial microgrid (MG) to deal with line contingencies. This consumer switching module (CSM) increases the operational flexibility and is suitable for the radial MGs, where, a sudden line outage restricts access to the energy resources and deviates the system frequency in the created island. To cope with this condition, CSM can instantly disconnect some of the loads and reconnects them in an appropriate time sequence, considering loads' vulnerabilities. To include the CSM in the short‐term operation of MG, with the lowest complexity, a simple four‐stage structure is used. At first, the capability of CSM is determined in different islands related to potential line events. Then, the approximate cost function of CSM is applied to the short‐term MG operation which is hour‐ahead scheduling (HAS) including both the normal and the contingency state operation. Eventually, the determined optimal CSM participation level in each island is allocated to the consumers based on their exact offered price to calculate the load switching sequence. To evaluate the performance of the proposed scheduling manner, the 13‐bus and 123‐bus IEEE test systems are precisely analyzed considering different simulation scenarios. [ABSTRACT FROM AUTHOR]

Types I, III and IV wind distributed generators show different and wide range of current sharing capacity during the occurrence of faults in the distribution feeders. In a hybrid microgrid consisting of any of the above mentioned types of wind distributed generators and photovoltaic distributed generators, the fault current in a feeder shows different behaviour which changes as per the type of distributed generators, grid/islanded connection of microgrid operation, distance of the fault from the point of common coupling and nature of the loads in the microgrid system. The novel contribution of this paper is the implementation of a fuzzy logic based adaptive protection scheme through analysis of the q0 components of fault current which are used to detect the low X/R ratio of distributed generators, modes of operation, transient reactance during the series and shunt faults in types I, III and IV wind turbines and PV integrated hybrid microgrid. Considering q0 components and transient reactance, a new relation between the relay current settings and modes of operation has been identified for adaptive relaying. The effectiveness of the proposed adaptive protection scheme for the hybrid microgrid is verified through a simulation case study using Matlab -Simulink software. [ABSTRACT FROM AUTHOR]

This research presents a robust model predictive controller of two microgrids (MGs) interconnected via tie‐line (TL) power. Power system operations continue to face new challenges due to the large integration of renewable energy generation with an active load demand uncertainty and the management and control of bidirectional power flow between MGs and others uncertainties and system nonlinearities due to the power system operating condition. To handle these uncertainties and system nonlinearities a robust model using predictive control scheme is presented in this paper to achieve the control of the active power between two MGs when considering three disturbances scenario models. In the design process, uncertainties and nonlinearities of the system were taken into account and contributed to the robustness of the closed‐loop system. Robust control scheme development considering power system nonlinearities and uncertainties were used to improve the online close‐loop robustness. The model helped to achieve a desired active power regulation by coordinating the MGs and active power over‐shoot and under‐shoot time were reduced outstandingly. A Comparison was made between open‐loop and close‐loop simulation results, which indicate that the model can handle robustness while settling power deviation of the interconnected system. MATLAB environment was used to solve the optimisation problem. [ABSTRACT FROM AUTHOR]