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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]

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]

Power system protection and asset management present persistent technical challenges, particularly in the context of the smart grid and renewable energy sectors. This paper aims to address these challenges by providing a comprehensive assessment of machine learning applications for effective asset management in power systems. The study focuses on the increasing demand for energy production while maintaining environmental sustainability and efficiency. By harnessing the power of modern technologies such as artificial intelligence (AI), machine learning (ML), and deep learning (DL), this research explores how ML techniques can be leveraged as powerful tools for the power industry. By showcasing practical applications and success stories, this paper demonstrates the growing acceptance of machine learning as a significant technology for current and future business needs in the power sector. Additionally, the study examines the barriers and difficulties of large‐scale ML deployment in practical settings while exploring potential opportunities for these tactics. Through this overview, insights into the transformative potential of ML in shaping the future of power system asset management are provided. [ABSTRACT FROM AUTHOR]

An introduction is presented in which the editor discusses articles in the issue on topics including distributed generation of electric power; low-voltage distribution network; and wind-battery energy storage hybrid systems.

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]

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]

Due to intermittent renewable energy and fluctuating load demand, distribution networks with renewable distributed generation (DG) installations are more likely to suffer voltage issues and significant power losses. The performance of conservation voltage regulation (CVR) schemes may be adversely affected by the undesirable voltage profile at specific nodes. This paper aims to reduce power losses in CVR‐implemented networks by optimally planning new renewable DGs without changing the existing ones. A scenario‐based optimal renewable DG planning model is proposed with a novel scenario formation method. The uncertainties of load demand and renewables are captured jointly and formed into a finite number of scenarios based on a multivariate Gaussian mixture model (MultiGMM). The locations and capacities of different types of new renewable DGs are optimally planned for CVR performance improvements on power loss saving by aggregating the operation status and probabilities of the scenarios using mixed‐integer non‐linear programming (MINLP). A time‐series simulation is formulated for accuracy verification. The results of case studies show that the proposed model can significantly reduce power losses, active load demand, and reactive load demand. The accuracy of the planning results can be guaranteed with fewer scenarios compared to a widely used classical scenario‐based planning method. [ABSTRACT FROM AUTHOR]

An editorial is presented on future distribution grids and integrated energy systems (IES). Topics include distributed energy resources (DERs) such as wind, solar, energy storage, combined heat and power plants, electric vehicles, and smart loads; and taking into account long-term uncertainties in natural gas prices and electric and natural gas demands through scenario realizations.

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]

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]

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]

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]

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]

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 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]

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 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]

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]

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]

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]

The grasshopper heuristic optimisation algorithm (GOA) is one of the newest heuristic techniques. It attempts to imitate locust's behaviour in solving different problems. In this paper, first, optimal location and size of fixed capacitor banks on distribution systems have been obtained using the GOA. Determination of the optimal number of capacitor banks and their optimal locations and sizes represent one of the major challenges facing distribution system operators. Therefore, second, a combined power loss sensitivity and GOA technique has been introduced to obtain the optimal number, location and size of the capacitor banks on distribution systems. Third, a proposed technique for optimal placement of fixed and switched capacitor banks considering daily load variations is introduced. Finally, a new technique of combined rough set theory and GOA is proposed to minimise daily switching of the capacitor banks and minimise daily power losses. Four test systems with different sizes and complexities are considered to evaluate the proposed techniques which are the 33, 69, 85 and 141‐bus systems. To clarify the validation and effectiveness of the proposed solution techniques, the obtained results have been compared with other previously used solving techniques. The obtained results demonstrate the accuracy and effectiveness of the introduced techniques. [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]

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]

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]

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]

Recently, microgrids (MGs) present a vital role in the transformation of the existing power networks to the smart grids. Connecting MGs to construct the multi-microgrid (MMG) system enhances the robustness of the system against disturbances and upgrades overall network performance. In this paper, the MMG, as a source of self-healing support to the distribution networks, is analysed extensively. In fact, the MMG strengthens the self-healing of the network by participating in the restoration of disturbed loads. In this study, an operational framework is proposed for the self-healing problem in radial interconnected MGs based on two-stage cyber communication network architecture. In the first stage, the local control system (LCS) within each MG, schedules the accessible resources according to the local power consumption target. In the second stage, a number of LCSs are communicated globally to perform self-healing action. The communication of LCSs is accomplished using a consensus algorithm. Nevertheless, when a fault takes place in MG and a line is eliminated, the healthy MGs, due to demand and supply information in the first stage, supply the on-outage loads as far as possible. To validate the effectiveness of the proposed framework, two benchmark distribution networks (the 33-bus and the 119-bus) are employed. [ABSTRACT FROM AUTHOR]

The conventional distribution network is becoming an active grid due to widespread integration of distributed energy resources (DERs). This integration raises great concerns about security of the power system considering the growing interactions between the transmission and active distribution systems. One way to ensure stability of the integrated power system is prediction of critical contingencies which can jeopardize the power system security. Therefore, this paper aims to investigate transient stability contingency ranking in power grids considering the uncertainties raised by DERs of active distribution networks. To this end, probabilistic transient stability prediction framework is provided, in which the probability density function of transient stability condition is calculated based on the normalized stability indicators. The normalized stability indicators are based on the rotor angle and rotor speed. The normalized stability indicators are only utilized in the case of using fault data for prediction. Based on the proposed scheme, the instability of generators is anticipated through the proposed probabilistic transient stability prediction framework. Also, the effects of the probable topology changes on the line overload and also the voltage profile are investigated. Finally, the performance of the proposed method is validated and compared with the time domain simulation under various operating conditions. [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]

Faced with the uncertainty of wind and photovoltaic power output and load fluctuation caused by the increase of new energy penetration in active distribution network, the demand for operational flexibility and the construction demand for flexible resources of distribution network are gradually increasing. The flexible operation of active distribution network can be realized by coordinated planning of the soft open point integrated with energy storage system (ESOP) and flexible resources. Firstly, the flexibility resource adjustability evaluation and margin indicators are proposed for the response model of typical flexibility resources. Secondly, a two‐stage distributionally robust coordinated planning model considering the coordination planning scheme of distributed generation, flexibility resource, and ESOP as well as the comprehensive norm uncertainty of wind power and photovoltaic outputs multi‐operation scenarios is established with the distribution network construction cost, annual operation cost, and annual power sales revenue as the objective functions meanwhile the investment and flexibility resource operation as constraints. Finally, the column constraint generation algorithm is used to solve the problem, and the effectiveness of the proposed model is verified by the modified IEEE33 node system. [ABSTRACT FROM AUTHOR]

To construct a multi‐energy complementary system for intelligent building group, a direct control strategy for central air conditioning based on discrete Fourier transform is proposed. This strategy can reduce the deviation between actual load and transaction results while absorbing photovoltaic (PV) power generation and improving the enterprise economy in the power market environment. The strategy uses the discrete Fourier transform (DFT) to find the scheduling demand of the central air‐conditioning (AC) group and realizes the scheduling demand by changing the temperature setting value. Also, the strategy can assess AC status in real‐time, which combines with ultra‐short‐term load forecasting to adjust future purchase planned values. The simulation results show that the strategy can realize a real‐time load track with the power purchase plan while absorbing PV power generation with low action times and temperature changes, which improves the absorption of distributed PV power generation and reduces the assessment bias. [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]

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]