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Abstract Grid stability can be affected by the large‐scale utilisation of renewable energy sources because there are fluctuations in generation and load. These issues can be effectively addressed by grid‐scale battery energy storage systems (BESS), which can respond quickly and provide high energy density. Different roles of grid‐scale BESS in power systems are addressed, following optimal operation approaches classification. Furthermore, integrating BESSs into distribution grids is discussed to manage challenges from distributed generation. BESSs aid in voltage control, enhance frequency regulation, and offer black‐start services. Aggregating distributed BESSs can provide ancillary services and improve grid economics. For consumers, BESSs optimise energy costs, enhance reliability, and support self‐consumption from renewables. Novel BESS services include congestion relief, system adequacy, and power quality enhancement. Moreover, the ancillary services provided in different European countries through BESS are analysed. Finally, a case study was conducted among three Baltic DSOs to analyse the required amendments to Grid Codes and Electricity Market Acts for the integration of grid scale BESS.

Medium-voltage DC (MVDC) technology has gained increasing attention in recent years. Power electronics devices dominate these grids. Accurate simulation of such a grid, with detailed models of switching semiconductors, can quickly became very time-consuming, according to the number of connected devices to be simulated. A simulation approach based on interactions on a continuous time model can be very interesting, especially for developing a system-level control model of such a modern MVDC distribution grid. The aim of this paper is to present all the steps required for obtaining a continuous time modelling of a +/−10 kV MVDC grid case study, including a solid-state transformer (SST)- and modular multilevel converter (MMC)-based active front end (AFE). An additional aim of this paper is to supply educational content about the use of the continuous time simulation approach, thanks to a detailed description of the various devices modelled into the presented MVDC grid. The results of a certain number of simulation scenarios are eventually presented. [ABSTRACT FROM AUTHOR]

The traditional approach to planning the distribution grid has focused on reliability in the context of gradual and reasonably predictable load growth. Forecasts of load growth, combined with asset management practices, were used by system planners to identify upgrades to the system to maintain or improve reliability. The decisions, typically based within load flow analysis tools, included considerations about contingency scenarios and corporate forecasts (i.e., top-down predictions at a summary level of what would happen in a particular area that could impact load growth and behavior). Today, this traditional approach no longer fits all purposes.

In AC/DC power distributions networks, power converters are interfacing buses to ensure DC voltage regulation and power distribution. Active front ends are used between AC and DC buses and two typical control schemes that can be implemented are voltage regulation or power regulation. On the DC side, open‐loop operated DC transformers could be used between two DC buses to provide voltage adaptation, isolation and natural power flow. In this context, power flows and DC bus voltages in the power distribution network are dependent on the combined operation of the active front ends and the DC transformer. Mainly studied from a stability perspective, this interdependency between active front ends and DC transformers has lacked investigations in terms of dynamics. Fast dynamics is nevertheless important to operate optimally a network. In this paper, the assessment of the dynamic performance for distribution systems with DC transformers is performed for different mixes of voltage regulating and power regulating active front ends. The influence of DC line length and DC transformer power reversal method on the system is further investigated. A model of the system is proposed, validated experimentally and can be used to aid system level design and analysis of future DC systems. [ABSTRACT FROM AUTHOR]

Abstract Non‐effectively grounded power distribution systems (NGDS) are widely used in China and other countries. However, over a long time, single‐phase‐to‐ground faults (SGF) have been misjudged or omitted by the monitoring system, threatening the security of the power supply system and human safety. Based on the reason analysis for the omitted and misjudged SGFs in NGDS, the concept of NGDS fault eigenparameters to correctly reflect fault characteristics and a method of SGF detection based on fault eigenparameters are proposed. Then, the detection mechanism of phase voltage and fault current resistive elements for SGF is revealed. The variation characteristics of typical fault parameters changing with distribution system scale (parameter) and fault transition resistance, such as residual voltage and Zero‐sequence current (iA‐iO), are analysed. The eigenparameters of SGF in certain NGDS with specific scales/parameters are also proposed, which can correctly reflect the fault characteristics under different transition resistances.

Abstract Among all types of onboard load demands in all‐electric ships (AESs), the propulsion power predominates (usually >70%), and a large‐scale hybrid energy storage system (HESS) tends to be installed to provide multi‐timescale flexibility. A two‐part dynamic power management method is therefore proposed consisting of a novel multi‐scenario propulsion power model, which models the impacts of floating conditions separately from other uncertain factors, and a three‐layer dynamic allocation strategy based on feedforward control to coordinate the main/auxiliary generators and the HESS. Three case studies are adopted to verify the validity of the proposed method, including a real‐time simulation experiment in RT‐Lab. The proposed method has three advantages: (1) the proposed multi‐scenario propulsion power model accounts for power fluctuations brought by floating conditions, which greatly alleviates the required regulating flexibility for AESs; (2) the proposed three‐layer dynamic power allocation strategy better shares the power demand on the main/auxiliary generators and the HESS, which reduces battery power fluctuations and prevents the overdischarging/overcharging of HESS; and (3) the RT‐Lab experiment proves that the proposed method can be used in real‐time applications for AESs.

Abstract 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 Economic operation and reliable supply‐demand balance are problems of paramount importance in power grids with a massive share of intermittent renewable energy sources (RESs) of great interest. This paper sought an optimal coordinated generation scheduling for day‐ahead power system operation considering RESs and energy storage units. Renewable power generation, particularly, wind and photovoltaic are uncontrollable, whereas can be predicted using forecasting models. Within the proposed framework, a hyperparameter‐optimized long short‐term memory (LSTM) regression model is employed to forecast the day‐ahead weather from the historical time‐series weather data. Eventually, an empirical formula is used to estimate the power conversion from the day‐ahead weather forecasts for a selected PV module and wind turbine. The objective of the scheduling framework is to keep a delicate supply‐demand balance at the lowest possible cost of generation while maintaining the prevailing generation and system constraints. A variance measure uncertainty handling‐based grey wolf optimizer (GWO) technique is used to find the optimal day‐ahead generation schedules and dispatches under RESs forecast uncertainty. The proposed generation scheduling framework is examined on the IEEE 6 and 30‐bus systems. In the studied scenarios, the coordinated operation of generators can decrease the total day‐ahead operating cost for the modified IEEE 6‐bus system by 2.57% compared to supplying electricity generation with conventional generators alone. Likewise, the total operating cost from the coordinated operation of all generation portfolios was reduced by 6.93% from the operating cost of generation during base case simulation (supply only from dispatchable thermal units) on the modified IEEE 30‐bus system. Moreover, the case studies show that coordinated generation scheduling can mitigate the RESs power variability problem, provide secure supply‐demand operation, and minimize the operating cost of electricity generation.

Among all types of onboard load demands in all‐electric ships (AESs), the propulsion power predominates (usually >70%), and a large‐scale hybrid energy storage system (HESS) tends to be installed to provide multi‐timescale flexibility. A two‐part dynamic power management method is therefore proposed consisting of a novel multi‐scenario propulsion power model, which models the impacts of floating conditions separately from other uncertain factors, and a three‐layer dynamic allocation strategy based on feedforward control to coordinate the main/auxiliary generators and the HESS. Three case studies are adopted to verify the validity of the proposed method, including a real‐time simulation experiment in RT‐Lab. The proposed method has three advantages: (1) the proposed multi‐scenario propulsion power model accounts for power fluctuations brought by floating conditions, which greatly alleviates the required regulating flexibility for AESs; (2) the proposed three‐layer dynamic power allocation strategy better shares the power demand on the main/auxiliary generators and the HESS, which reduces battery power fluctuations and prevents the overdischarging/overcharging of HESS; and (3) the RT‐Lab experiment proves that the proposed method can be used in real‐time applications for AESs. [ABSTRACT FROM AUTHOR]

Abstract Electrical power systems are continuously upgrading into networks with a higher degree of automation capable of identifying and reacting to different events that may trigger undesirable situations. In power systems with decreasing inertia and damping levels, poorly damped oscillations with sustained or growing amplitudes following a disturbance may eventually lead to instability and provoke a major event such as a blackout. Additionally, with the increasing and considerable share of renewable power generation, unprecedented operational challenges shall be considered when proposing protection schemes against unstable electro‐mechanical (e.g. ringdown) oscillations. In an emergency situation, islanding operations enable splitting a power network into separate smaller networks to prevent a total blackout. Due to such changes, identifying the underlying types of oscillatory coherency and the islanding protocols are necessary for a continuously updating process to be incorporated into the existing power system monitoring and control tasks. This paper examines the existing evaluation methods and the islanding protocols as well as proposes an updated operational guideline based on the latest data‐analytic technologies.

Abstract In order to deal with the problems of complex optimisation model and computing speed in the multi‐objective operation control of the power distribution network, this paper is oriented to the basic model and process of the feeder partition decoupling method for the distribution network. Firstly, the necessity of developing partition decoupling for the distribution network is expounded according to the development status and control mode of the complex distribution network. Secondly, the objective models commonly used in the distribution network optimisation control are given to illustrate the importance of partition decoupling for the complex distribution network, including line loss and voltage offset. Finally, three general decoupling equivalent models are presented, namely Ward equivalent model, virtual generator equivalent model, and radial equivalent independent model, and then the partition decoupling equivalent process is proposed.

Abstract In this study, a partition optimisation method for distribution network is proposed to realise decoupling coordination, which provides a research basis for optimising power flow and operation regulation. Firstly, a partition model of distribution network is established, in which the electrical distance, parallel computing efficiency, and operation stability indexes are considered at the same time; Secondly, the AHC algorithm is used to realise the automatic search partition of the distribution network, and the class spacing measurement factors of point‐to‐point, cluster‐to‐cluster are considered in this method. Finally, the Distributed Sequential Quadratic Programming for Distributed Generation (DSQP‐DG) is introduced, and the parallel decoupling coordination of the distribution network is realised by alternate iteration of its inner and outer layers.

Abstract Optimal power flow (OPF) plays an important role in the secure and economical operation of the distribution network. This paper proposes a novel generalized linear‐constrained optimal power flow (GLOPF) model for both radial and mesh distribution networks, which iteratively approaches the optimal solution to the original OPF problem. The first‐order Taylor series approximation method is applied to linearize the non‐linear and non‐convex power flow constraints for a given Taylor expansion point (TEP). In addition, the objective function of the GLOPF model is only added with an easy‐compute second‐order penalty on state variables, which is at least positive semi‐definite and guarantees the convexity of the quadratic optimization. Then a TEP‐based iterative (TEP‐I) method is proposed in the GLOPF model to construct a series of linear‐constrained convex quadratic optimizations, which avoids the complex calculation of quasi‐Hessian or Hessian matrices in traditional sequential programming methods. The converged solution to the GLOPF model is proved to satisfy the Karush–Kuhn–Tucker conditions of the original OPF problem. Furthermore, the GLOPF model at first and second iterations can be implemented as the ‘cold‐start’ and ‘warm‐start’ LOPF models, respectively. Case studies verify the super‐linear convergence and high accuracy of the proposed GLOPF model.

The future circular collider (FCC) is a cutting-edge particle accelerator being planned by the European Organization for Nuclear Research (CERN). It is designed to delve deeper into the mysteries of the universe than its predecessor, the large hadron collider (LHC). With a circumference of over 80 km, the FCC requires a reliable and efficient power transmission network to operate smoothly. The available power options for the FCC include a high-voltage dc transmission and radio frequency powering networks based on HVdc converters, such as the modular multilevel power converters or the 12-pulse thyristor rectifiers, each providing several benefits in power transmission efficiency and cost-effectiveness. However, the converter selection, its control, and the protection aspects must be carefully designed to meet the unique requirements of the installation. This article examines different dc powering scenarios for the FCC and proposes a control and protection scheme compatible with the accelerator's operation mode. This approach ensures that the power system meets the FCC's specific needs and operates safely and effectively. The validity of the proposed control and protection strategies is verified by means of detailed computer simulations.

As conventional power generation units are being replaced with distributed energy resources, operational practices such as voltage regulation and congestion management are expected to be challenging. To address these challenges, regular and automated intercontrol center operational coordination will be needed between transmissions and distributions system operators (TSO and DSO). In this study, the data exchange required for the near-real-time operational coordination is investigated for a reactive power management use case. A realistic ICCP/TASE 2 protocol is implemented in a laboratory environment where the physical network is simulated in a real-time simulator while optimal set-points are communicated from the control centers to simulated assets being communicated through the IEC 60870-5-104. In addition, the sufficiency of the common information model (CIM) and common grid model exchange standard (CGMES) is evaluated for TSO-DSO network data exchange. The results from the cyber-physical test setup show that the detailed DSO grid model knowledge by the TSO results in lower system losses. Such data can be difficult to prepare, exchange, and compute. However, results show that simplified equivalent models can be acceptable if they are properly tailored to the specific use case. The experiences from the CIM implementation with the CGMES profile are found out to be sufficient for such operational data exchange.

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]

Economic operation and reliable supply‐demand balance are problems of paramount importance in power grids with a massive share of intermittent renewable energy sources (RESs) of great interest. This paper sought an optimal coordinated generation scheduling for day‐ahead power system operation considering RESs and energy storage units. Renewable power generation, particularly, wind and photovoltaic are uncontrollable, whereas can be predicted using forecasting models. Within the proposed framework, a hyperparameter‐optimized long short‐term memory (LSTM) regression model is employed to forecast the day‐ahead weather from the historical time‐series weather data. Eventually, an empirical formula is used to estimate the power conversion from the day‐ahead weather forecasts for a selected PV module and wind turbine. The objective of the scheduling framework is to keep a delicate supply‐demand balance at the lowest possible cost of generation while maintaining the prevailing generation and system constraints. A variance measure uncertainty handling‐based grey wolf optimizer (GWO) technique is used to find the optimal day‐ahead generation schedules and dispatches under RESs forecast uncertainty. The proposed generation scheduling framework is examined on the IEEE 6 and 30‐bus systems. In the studied scenarios, the coordinated operation of generators can decrease the total day‐ahead operating cost for the modified IEEE 6‐bus system by 2.57% compared to supplying electricity generation with conventional generators alone. Likewise, the total operating cost from the coordinated operation of all generation portfolios was reduced by 6.93% from the operating cost of generation during base case simulation (supply only from dispatchable thermal units) on the modified IEEE 30‐bus system. Moreover, the case studies show that coordinated generation scheduling can mitigate the RESs power variability problem, provide secure supply‐demand operation, and minimize the operating cost of electricity generation. [ABSTRACT FROM AUTHOR]

Optimal power flow (OPF) plays an important role in the secure and economical operation of the distribution network. This paper proposes a novel generalized linear‐constrained optimal power flow (GLOPF) model for both radial and mesh distribution networks, which iteratively approaches the optimal solution to the original OPF problem. The first‐order Taylor series approximation method is applied to linearize the non‐linear and non‐convex power flow constraints for a given Taylor expansion point (TEP). In addition, the objective function of the GLOPF model is only added with an easy‐compute second‐order penalty on state variables, which is at least positive semi‐definite and guarantees the convexity of the quadratic optimization. Then a TEP‐based iterative (TEP‐I) method is proposed in the GLOPF model to construct a series of linear‐constrained convex quadratic optimizations, which avoids the complex calculation of quasi‐Hessian or Hessian matrices in traditional sequential programming methods. The converged solution to the GLOPF model is proved to satisfy the Karush–Kuhn–Tucker conditions of the original OPF problem. Furthermore, the GLOPF model at first and second iterations can be implemented as the 'cold‐start' and 'warm‐start' LOPF models, respectively. Case studies verify the super‐linear convergence and high accuracy of the proposed GLOPF model. [ABSTRACT FROM AUTHOR]

Abstract The objective of the microgrid secondary control system (MSCS) is to regulate frequency and voltage and allocate active and reactive power among distributed generations in the microgrid. Sequential denial‐of‐service (DoS) attacks have a lasting impact that reduce the vulnerability of the MSCS. A vulnerability assessment method is proposed for when the microgrid experiences DoS attacks. The sequence model of attack actions and N–1 contingency actions are proposed to find the traversal expression. With the traversal method, vulnerable factors of the microgrid can be interpreted by the proposed comprehensive vulnerability metric, which provides an intuitive and easy way to understand the vulnerability of the MSCS. The metric is composed of four basic indicators concerning not only final states of the microgrid when a DoS attack ends, but also the dynamic process of the microgrid. To test the proposed metric, two mitigation methods with the purpose of mitigating the impact on the physical system caused by DoS attacks are proposed: the self‐adaptive coefficient method and the fault‐tolerance method. Finally, a 33‐node microgrid platform with eight distributed generations has been built to test the proposed vulnerability assessment method. From the analysis results, nodes with a high cyber‐degree are vulnerable and the fault‐tolerance method can provide a better mitigation result with an average metric of 9.41 compared with the self‐adaptive coefficient method with a metric of 9.03.

Abstract This paper presents a co‐simulation platform (CSP) developed as a part of the “Microgrids, Infrastructure Resilience and Advanced Controls Launchpad (MIRACL)” project, hereafter called MIRACL‐CSP, to allow simulation‐based testing, demonstration, and evaluations of distributed wind under various grid operating conditions. MIRACL‐CSP provides modular interactions among the power distribution system, distributed wind, and utility decision‐making framework. A hierarchical engine for large‐scale infrastructure co‐simulations (HELICS) is used as the core engine of MIRACL‐CSP to establish time and information coordination among the MIRACL‐CSP modules. In this study, MIRACL‐CSP performance is demonstrated using the IEEE 123‐node test distribution grid modelled in GridLAB‐D and the utility decision support application modelled in Python. The functionality of MIRACL‐CSP is demonstrated through various grid operational scenarios in a microgrid and networked microgrid environment. A co‐simulation study is described that demonstrated MIRACL‐CSP capabilities for the microgrid operational scenario in the IEEE 123‐node test system. MIRACL‐CSP is a generic platform that facilitates distributed wind research for different test systems, applications, and valuation of distributed wind.

Extreme temperature outages can lead to not just economic losses but also various non-energy impacts (NEI), such as increased mortality rates, property damage, and reduced productivity, due to significant degradation of indoor operating conditions caused by service disruptions. However, existing resilience assessment approaches lack specificity for extreme temperature conditions. They often overlook temperature-related mortality and neglect the customer characteristics and grid response in the calculation, despite the significant influence of these factors on NEI-related economic losses. This paper aims to address these gaps by introducing a comprehensive framework to estimate the impact of resilience enhancement not only on the direct economic losses incurred by customers but also on potential NEI, including mortality and the value of statistical life during extreme temperature-related outages. The proposed resilience valuation integrates customer characteristics and grid response variables based on a scalable grid simulation environment. This study adopts a holistic approach to quantify customer-oriented economic impacts, utilizing probabilistic loss scenarios that incorporate health-related factors and damage/loss models as a function of exposure for valuation. The proposed methodology is demonstrated through comparative resilient outage planning, using grid response models emulating a Texas weather zone during the 2021 winter storm Uri. The case study results show that enhanced outage planning with hardened infrastructure can improve the system resilience and thereby reduce the relative risk of mortality by 16% and save the total costs related to non-energy impacts by 74%. These findings underscore the efficacy of the framework by assessing the financial implications of each case, providing valuable insights for decision-makers and stakeholders involved in extreme-weather related resilience planning for risk management and mitigation strategies. • Framework for the value of customer resilience by extreme temperature-related outages • Resilience valuation using customer characteristics and grid variables in simulations • Loss scenarios using customer factors and temperature-based damage models • Applying resilience valuation to 2021 Winter Storm Uri use-case [ABSTRACT FROM AUTHOR]

Abstract The power distribution system has increasing importance and complexity as a result of the exponential growth in the adoption of smart grid technologies. The ability to model the power distribution system is critical to ensure a smooth transition to a sustainable power system. This study presents a distributed data‐driven framework based on Cellular Computational Networks (CCN) for power distribution system modelling where the CCN framework facilitates for system decomposition. The learning in CCN is distributed and asynchronous, thus adaptive models can be developed. The computational engine of the CCN cells is based on data‐driven, physics‐driven, or a hybrid approach. The CCN‐based distribution system modelling secures the privacy and security of the sensitive utility information, thus allowing third‐party application providers access to system models and behaviours. The application of a CCN‐based power flow model is illustrated on a modified IEEE 34 test system. Typical results show the suitability of the new approach in modelling the sample distribution system, as well as its enhanced performance when compared with the centralised modelling approach.

Abstract The fundamental goal of the distribution system operator (DSO) is to serve its customers with reliable and low‐cost electricity. Failures in power distribution systems are responsible for 80% of customer service interruptions. The emergence of smart distribution system (SDS) with advanced distribution automation (DA) and communication infrastructure offers a great opportunity to improve reliability, through the automation of fault location, isolation, and service restoration (FLISR) process. DA includes the installation of protection and control devices (PCD). The use of PCD makes fault management more efficient, reduces average outage duration per customer in case of faults, reduces costs due to unsupplied energy, and improves distribution system reliability. Although the use of PCD remarkably enhances distribution system reliability, it is neither economical nor affordable to install them in all potential locations. To obtain the optimal allocation of PCD (OAPCD), an optimisation problem has to be formulated and solved. Several models and methods have been suggested for the OAPCD in SDSs. Herein, an overview of the state‐of‐the‐art models and methods applied to the OAPCD in SDSs are introduced, identifying the contributions of reviewed works, identifying advantages and disadvantages, classifying and analysing current and future research directions in this area.

Abstract Hybrid AC‐DC microgrids (HMGs) are formed by interconnecting AC microgrids (MGs) and DC microgrids via AC‐DC interlinking converters (ICs). In the islanded mode, apart from power sharing in a single MG, power sharing expansion throughout HMG is desirable. Conventionally, this is achieved by employing an IC control mechanism in coordination with the droop characteristics of sources. Because the conventional control strategy of IC relies on measuring the frequency variations in AC MG, accurate coordination necessitates a wide range of frequency deviation. Also, this strategy employs the current‐controlled method, which fails to accomplish superior voltage quality during load transients and in the presence of an unbalanced load obtainable by the voltage‐controlled method (VCM). An IC control strategy for single IC HMGs is proposed that does not require the measurement of frequency variation and employs VCM in the inner control loop. As a consequence, the power quality of AC MG is improved. The proposed control strategy is phase locked‐loop‐less. In addition, by supporting the related MG with the disconnection of sources in AC MG or DC MG, it provides a uniform control property. Time domain simulations and experimental results are provided to verify the efficacy of the proposed strategy.

The transition towards fully renewable energy-based power systems will require to increase the number of reserves at the System Operators’ (SOs) disposal to provide flexibility on the energy management process. The microgrid’s ability of integrating distributed energy resources, loads and energy storage systems (ESS) appears as a powerful flexibility tool. Nevertheless, the associated control problem of microgrids increases with the number of connected devices. A structuration of the distribution grids in networks of microgrids is proposed, focusing on their ability to provide flexibility services. The complexity of the associated optimization algorithm is faced using Distributed Model Predictive Control (MPC). The algorithm is divided in two steps. The first one is applied to the cooperative participation of microgrids in the day-ahead market. The second step covers the interaction with the SO offering flexibility services in exchange for a financial benefit. The financial benefit is optimally shared between the networked microgrids to satisfy the power profile requested by the SO at the lowest cost. As the proposed control algorithm presents both continuous and binary variables, its associated optimization problem is formulated using the Mixed Logic Dynamic (MLD) framework, which results in a Mixed Integer Quadratic Programming problem (MIQP). [ABSTRACT FROM AUTHOR]

To realise the distributed control of the hybrid energy storage system (HESS) in an islanded AC microgrid, a dynamic HESS power allocation strategy based on the virtual impedance (VI) for supercapacitor (SC) and the battery is proposed. Dynamic power-sharing of two kinds of energy storage devices can be achieved without real-time measuring of load power. The state of charge (SOC) recovery of SC is achieved with a SOC loop integrated into the VI loop. The principle of dynamic power-sharing of HESS is derived based on the establishment of HESS equivalent circuit model. By analysing the influence of the voltage and current double loop controller parameters on the output impedance and the VI of the DC/AC converter, the method of setting the controller parameters for power distribution is presented. A simulation model is established with the designed equivalent power fluctuation conditions. The simulation results show that under various working conditions, the SC loop can compensate for the high-frequency part of the equivalent power fluctuation and the battery loop absorbs the low-frequency part of the power fluctuation. The dynamic power-sharing of HESS with the SC SOC recovery is realised effectively.

This study presents a practical control method for electric vehicle (EV) charging optimisation for detached and attached houses. The developed EV charging control method utilises real-time measurements to minimise charging costs of up to two EVs in a single household. Since some Finnish distribution system operators have already launched peak power-based distribution tariffs for small-scale customers and because there is a lot of discussion on this kind of tariff development, the control method considers peak power-based charges. Additionally, the proposed smart charging control method utilises charging current measurements as feedback to reallocate unused charging capacity if an EV does not utilise the whole capacity allocated for it. The control method is implemented and tested with commercial EVs. The conducted hardware-in-the-loop simulations and measurements confirm that the control method works as intended. The proposed smart charging control reduces EV charging electricity distribution costs around 60% when compared to the uncontrolled EV charging.

Peer-to-peer (P2P) energy market has emerged as a promising way to absorb local generations. However, unregulated P2P transactions are likely to exacerbate voltage violations at distribution networks. The challenge is how to ensure P2P markets to flourish whilst maintaining system voltages within the stator limits. This study proposes a distributed-hierarchical control structure consisting of a central controller and peer controllers to address the challenge. The central controller computes the optimised P2P transaction levels and the nodal voltage references simultaneously and sends the outcomes to the peers as routing-update messages at regular intervals. The peer controllers are developed based on individual phase decupled P–Q theory where two individual channels follow the optimised transaction levels and nodal voltage references. The peers, also, apply a current limit strategy to release the network capacity and improve voltage profiles when confronting with short-term voltage magnitude variations between the two update intervals. A case-study-based investigation shows that reactive power contributions improve the power transaction levels up to 30% while the node voltage violations are reduced. The effectiveness of the proposed strategy is validated using simulation and compared with state-of-the-art voltage mitigation methodologies over the IEEE 19-bus system.

Voltage control devices are employed in power distribution systems to reduce the power consumption by operating the system closer to the lower acceptable voltage limits; this technique is called conservation voltage reduction (CVR). The different modes of operation for system's legacy devices (with binary control) and new devices (e.g. smart inverters with continuous control) coupled with variable photovoltaic (PV) generation results in voltage fluctuations which makes it challenging to achieve CVR objective. This study presents a two-timescale control of feeder's voltage control devices to achieve CVR that includes: (i) a centralised controller operating in a slower time-scale to coordinate voltage control devices across the feeder; and (ii) local controllers operating in a faster timescale to mitigate voltage fluctuations due to PV variability. The centralised controller utilises a three-phase optimal power flow model to obtain the decision variables for both legacy devices and smart inverters. The local controllers operate smart inverters to minimise voltage fluctuations and restore nodal voltages to their reference values by adjusting the reactive power support. The proposed approach is validated using the IEEE-123 bus (medium-size) and R3-12.47-2 (large-size) feeders. It is demonstrated that the proposed approach is effective in achieving the CVR objective for unbalanced distribution systems.

This study provides a solution for the feeder reconfiguration of autonomous microgrids (MGs). The objective is to minimise power loss, switching costs, and enhance voltage stability index, considering time-variations of loads. The daily load profiles for different seasons (spring, summer, fall, and winter) of different customers (i.e. residential, industrial, and commercial) are considered. In order to reduce the dimensions of the optimisation problem, k-means algorithm is implemented that clusters seasonal/yearly load profile into a few groups. The daily load profile is obtained based on the average of the group which has maximum members. This ensures the selection of a subset of load profiles that effectively represent the entire year's profile to reduce the complexity and execution time of the model. Subsequently, a new method is developed to break the daily load profile into intervals that guarantee less switching frequency for dynamic network reconfiguration. A controlled mutation differential evolution algorithm (CMDEA) compatible with long-term reconfiguration problem is developed with superior performance compared to conventional DEA and invasive weed optimisation algorithm. The CMDEA is employed to solve the reconfiguration problem on 33-bus and 69-bus autonomous MGs. Simulation results validate the effectiveness of the proposed method to reduce operational costs and computational burden in a smart grid environment.

This paper presents a hierarchical coordination method to improve operation conditions between the medium‐voltage distribution network (MVDN) and low‐voltage distribution networks (LVDN) considering high‐level residential PV units integrating LV distribution networks. It addresses the following issues: (i) rapid power fluctuations and unbalance caused by high‐level residential PV units passes to the MV distribution network via the point of common coupling (PCC) and thus increase operation challenges; (ii) power fluctuations, voltage violations and unbalance simultaneously happens in the LVDNs. A hierarchical coordination structure the MVDN and LVDN is proposed. In the MV level, a centralized dispatch method based on three‐phase optimal power flow is developed in the timescale of minutes to minimize the power losses, unbalance and PCC adjustments, which are achieved by regulating energy storage systems (ESSs) and PV inverters in the LV level. In the LV level, a distributed control model based on a consensus algorithm is proposed in the timescale of seconds to track the reference active (or reactive) power at the PCC given by the MV level and mitigate its fluctuations. Simulations studies are performed to verify the proposed method. [ABSTRACT FROM AUTHOR]

The controlled islanding problem is typically considered only for pure ac power systems, with the ultimate objective of either minimising power imbalance or power-flow among islands. However, as ac/dc hybrid power systems are becoming popular worldwide, current controlled islanding schemes should be redesigned to take into account the presence of high-voltage dc (HVDC) links, possibly connecting different islands. Accordingly, in this study, the authors solve the classic islanding problem combining HVDC power modulation with the conventional ac cutset search. The flexibility of the HVDC allows the authors' strategy to jointly capture the previously mentioned objectives, and provides even lower power imbalances than the minimum imbalance strategy, at a relatively small cost of increasing power-flow impact. Then, the optimisation problem is formulated as a mixed-integer linear programming problem, which can be conveniently solved with existing commercial solvers. Finally, they validate their proposed strategy in two case studies, corresponding to a modified IEEE-118 system and to the China Southern Power Grid system. In both cases, dynamic simulations show that their proposed approach outperforms classic algorithms where the presence of HVDC power modulation is not explicitly taken into account. [ABSTRACT FROM AUTHOR]

With the real-time changes of wind speed and operating conditions, it is a challenge to fully tap the active power regulation ability and improve the control performance of automatic generation control (AGC) in a wind farm (WF). The essence of tapping the active power regulation ability is to realise the coordination and complementarity of each wind turbine's (WT's) dynamic adjustment performance (DAP). To address this, a novel data mining method is developed to derive the internal relations between WTs' output power and pitch angle, impeller speed and pitch angle during the power adjustment process, and a unified mechanism model is established to describe DAP of WTs. Based on the discovered relationship between WTs' DAP and its operating states, an active power distribution algorithm and a dynamic interval control method are proposed. Then, an active power dynamic interval control strategy that has been implemented using Java script in MyEclipse for WFs is further developed. The control strategy has been tested and applied in a 50 MW WF in northwest China. The preliminary results showed that the control strategy has improved the rapidity and accuracy of AGC in the WF. [ABSTRACT FROM AUTHOR]

This study presents a comprehensive study of microgrid systems using a single‐phase self‐excited induction generator (SEIG) using renewable energy sources (RESs) and their integration with other energy sources. It investigates on the use of a single‐phase two‐winding SEIG for off‐grid single‐phase power generation from different RESs. Various solid‐state controllers are implemented for each configuration. This is the first time, such an attempt is made to use a specially designed SEIG for sustainable energy application to feed single‐phase loads vastly prevalent in isolated and distant locations in accessible to the grid. This work has great importance due to the non‐availability of the power in remote regions in developing countries. Moreover, there is a need to use local RESs such as bio, hydro, wind in combination with the solar energy. The present global need to generate pollution free electricity makes this work quite important. Thus, this study presents a comprehensive review of different modes of SEIG using RESs for single‐phase power generation realising the microgrid feeding a combination of practical loads with viable and successful controllers to ensure desired quality power across loads. [ABSTRACT FROM AUTHOR]

Due to the rapid increase in electrical energy requirements in marine power systems (MPSs), and to reduce the consumption of fossil fuel, there is an emergent need to utilise renewable energy sources (RESs) in MPSs, which has been an attractive field of research. This research aims to present a novel load frequency control (LFC) scheme for a shipboard micro‐grid (SMG) system. Therefore, a MPS with photovoltaic, wind turbine, hybrid energy storage system (ESS), and diesel generator (DG) have been simulated to relate an exact mobile islanded SMG. The system is designed using the transfer function models with the above said generating units and storage systems. Grasshopper optimisation algorithm (GOA) tuned fuzzy‐based proportional–integral–derivative with filter control technique has been proposed to investigate the performance of the LFC scheme for the proposed SMG system. GOA and particle swarm optimisation optimised controllers have been designed and performance evaluation has been carried out on the conventional, adaptive neuro‐fuzzy inference system, and fuzzy cascaded with a conventional controller. The responses obtained from the simulations for different cases are analysed to justify the novelty and superiority of the proposed technique for frequency and power regulation. [ABSTRACT FROM AUTHOR]

The popularity of electric springs (ESs) has been grown in the last years mainly due to the boost in the growth of smart grids (SGs) and micro‐grids (μGs), as well as the high penetration of renewable energy sources. In general, ESs have a hardware structure similar to other compensator devices such as distributed flexible AC transmission systems or active filters. ESs offer the exchange of active and reactive powers with the electrical grid and the demand‐side load management. Their ability to simultaneously perform multiple tasks without the need of modifying their hardware structure classifies them as smart loads, distinguishing them from other types of compensators such as active filters, hybrid filters, dynamic voltage restorers, and distribution static VAR compensators, among others. In this work, an exhaustive review of ESs is carried out to cover their three main research trends, i.e. hardware structure evolution, different types of controllers, and applications in electric power distribution systems, SGs, and μGs. Moreover, their main advantages, disadvantages, and contributions in the power quality improvement are discussed. This review clarifies future research trends that have to be explored to advance the subject. [ABSTRACT FROM AUTHOR]

In this study, a new non‐local active compensation method is developed for a multi‐microgrid (MMG) system. The current industry practice is to utilise local harmonic current and reactive power compensation methods, however, local compensation methods are not practical for large MMG system with widely dispersed non‐linear loads, because each non‐linear load would require its own compensator. To overcome this problem, a novel compensating technology called a series–shunt network device (SSND) is installed between a pair of microgrids in the proposed MMG system. The SSND reduces the number of local compensators required while also performing additional functions in comparison with conventional devices. For effective control of the SSND, an improved model predictive control (MPC) algorithm, which gives better tracking accuracy and faster set‐point change than that of a conventional proportional–integral controller, is also presented. Analysis and simulations verify the capability of SSND in performing both local and non‐local active compensation of harmonic current and reactive power in the proposed MMG system under various test scenarios. Simulation results show that the MPC‐controlled SSND can achieve effective compensation, thereby resulting in a very low current total harmonic distortion value of 2.4% and a unity power factor at the distribution grid side. [ABSTRACT FROM AUTHOR]

Three‐phase unbalanced conditions in distribution networks are conventionally caused by load imbalance, asymmetrical fault conditions of transformers and impedances of three phases. The uneven integration of single‐phase distributed generation (DG) worsens the imbalance situation. These unbalanced conditions result in financial losses, inefficient utilisation of assets and security risks to the network infrastructure. In this study, a phase‐changing soft open point (PC‐SOP) is proposed as a new way of connecting soft open points (SOPs) to balance the power flows among three phases by controlling active power and reactive power. Then an operational strategy based on PC‐SOPs is presented for three‐phase four‐wire unbalanced systems. By optimising the regulation of SOPs, optimal energy storage systems dispatch and DG curtailment, the proposed strategy can reduce power losses and three‐phase imbalance. Second‐order cone programming (SOCP) relaxation is utilised to convert the original non‐convex and non‐linear model into an SOCP model which can be solved efficiently by commercial solvers. Case studies are conducted on a modified IEEE 34‐node three‐phase four‐wire system and the IEEE 123‐node test feeder to verify the effectiveness, efficiency and scalability of the proposed PC‐SOP concept and its operational strategy. [ABSTRACT FROM AUTHOR]

In the present day, there is an enormous demand in the supply of energy to all users. Since the voltage stability for the distribution system is not steady under any circumstances, therefore, to solve the problem of voltage instability the entire distribution system must simplified properly. Thus, some active support is provided for balancing the demand for electrical energy supply. Hence, the problem of voltage instability has been solved by considering phasor measuring units (PMUs) using antlion optimisation proposed in this study. The cost of PMU has been analysed along with other factors such as observability for effectively placing the PMUs with the identification of the weakest node. The problem is solved by using a non‐linear model and the effectiveness of the proposed approach is tested using IEEE‐15, IEEE‐33, IEEE‐69 Radial Distribution Systems and Croatia distribution grid. The result shows that the suggested algorithm is more effective in getting the optimal PMU placements considering multi‐objective. Hence, the maiden state estimation values for distribution topologies are used. [ABSTRACT FROM AUTHOR]

The design of the control system in an inverter‐based microgrid (μGs) is a challenging problem due to the large number of parameters involved. Different optimisation methods based on obtaining an approximated mathematical model of the μG can be found in the literature. In these approaches, the non‐linearities and uncertainties of the real system are typically not considered, which may result in a non‐optimal tuning of the control parameters. In addition, in most applications, the problem has been simplified, assuming that all controllers have the same value for their control parameters. However, in this case, the behaviour of the system is sub‐optimal since the particularities of each node of the μG are not taken into account. In this study, an experimental approach for tuning the control parameters of an inverter‐based μG is introduced. The approach is based on the methodology of design of experiments and it considers different values for the control parameters of all controllers. In this study, this methodology is applied to the design of a droop‐free control scheme; however, it can be easily extended to other control schemes. The validity of the proposal is verified through selected experimental results. [ABSTRACT FROM AUTHOR]

This work deals with the implementation, control and operation of a reconfigurable small hydro‐solar photovoltaic (PV)‐battery energy storage (BES)‐based distributed generation system (DGS) working in isolated mode (IM) and grid connected mode (GCM). The DGS consists of a hydro generation‐based on a PMSG integrated with a PV array supported by the BES. It operates in an IM during the grid outage and when the grid is available, it synchronizes and operates in GCM. A frequency adaptive comb filter‐frequency locked loop (FLL)‐based control is adopted to estimate errorless phase angles of the hydro generator and grid voltages for quick and accurate grid synchronization. A third‐order band pass filter‐based control technique is used to extract fundamental component of load currents and determine switching pulses to VSC. The overall multi‐objective control is used to maintain voltage and frequency of the system at the point of common coupling during IM and GCM. The power quality of grid and generator currents are maintained at non‐linear loads. The modified perturb and observe‐based control technique is used to extract maximum power from the PV array and it provides drift‐free operation during the change in insolation with de‐rating capability to protect the BES from overcharging in IM. [ABSTRACT FROM AUTHOR]

Voltage profiles may exceed the upper limit in a distribution network with a high penetration of distributed generation (DG). Voltage can be effectively regulated by curtailing the active power of DG and adjusting the reactive power. Soft open points (SOPs) have flexible active power transfer and reactive power regulation capabilities that can help reduce the active power curtailment of DG. Asymmetric network parameters, single‐phase loads, and DGs cause voltage unbalance in distribution networks. This study proposes an optimal power control model of SOPs and DG converters in unbalanced distribution networks (UDNs). First, the individual phase power control characteristics of SOPs and DG converters in UDNs are modelled. Second, an optimisation model is constructed with the minimum active power curtailment of DG and the total power loss and voltage unbalance of UDNs as the objective function and with consideration of the networks and SOP operation constraints. The original optimisation model with non‐convex and non‐linear characteristics is transformed using power flow linearisation and linear relaxation into a linear programming model that can be efficiently solved. Finally, the feasibility and efficiency of the proposed model are verified using an IEEE 33‐node system. [ABSTRACT FROM AUTHOR]

To realise the distributed control of the hybrid energy storage system (HESS) in an islanded AC microgrid, a dynamic HESS power allocation strategy based on the virtual impedance (VI) for supercapacitor (SC) and the battery is proposed. Dynamic power-sharing of two kinds of energy storage devices can be achieved without real-time measuring of load power. The state of charge (SOC) recovery of SC is achieved with a SOC loop integrated into the VI loop. The principle of dynamic power-sharing of HESS is derived based on the establishment of HESS equivalent circuit model. By analysing the influence of the voltage and current double loop controller parameters on the output impedance and the VI of the DC/AC converter, the method of setting the controller parameters for power distribution is presented. A simulation model is established with the designed equivalent power fluctuation conditions. The simulation results show that under various working conditions, the SC loop can compensate for the high-frequency part of the equivalent power fluctuation and the battery loop absorbs the low-frequency part of the power fluctuation. The dynamic power-sharing of HESS with the SC SOC recovery is realised effectively. [ABSTRACT FROM AUTHOR]

The photovoltaic (PV) hosting capacity of active distribution networks is usually restricted by network overvoltage at peak PV generation hours. In the literature, several methodologies are presented to mitigate this problem caused by PVs reactive power regulation. However, the feeder transformer's thermal limit and branch lines loading confine the PVs reactive power capability. This study proposes a fully local reactive power regulation strategy enabling the PV systems to increase the feeder hosting capacity without using communication infrastructure. In the suggested framework, the distribution feeder is partitioned into several zones based on the feeder's electrical bottlenecks from the perspective of lines loading condition. The PV units placed in the vicinity of the electrical bottlenecks are equipped with the proposed local controller to moderate burden on the corresponding bottlenecks. Other PV units support the network voltage using a conventional local voltage-dependent reactive power controller. Consequently, the feeder hosting capacity can be enhanced while equipment loadings remain in their permissible limits. Moreover, the network power loss is decreased due to the local reactive power management. Furthermore, the proposed approach provides superior coordination between the PV systems controller and the transformer feeder tap changing mechanism. The advantages of the proposed approach are demonstrated by simulation results on 33- and 69-node radial and meshed distribution feeders. [ABSTRACT FROM AUTHOR]

Line impedance mismatch and unregulated harmonic currents cause serious problems for an islanded microgrid, such as inaccurate reactive power sharing and voltage distortion at the point of common coupling (PCC). To overcome these issues, a coordinated virtual resistance and capacitance are introduced together with its control scheme for parallel distributed generation (DG) in an islanded microgrid. The proposed coordinated virtual impedance control scheme directly modifies the DG output impedance at the fundamental frequency to realise accurate current sharing among DG units. In addition, a variable harmonic impedance control loop is proposed for each DG to absorb the non-linear load harmonic current. Thanks to the proposed control scheme, the PCC harmonic voltage distortion is successfully compensated and power-sharing among DG units is accurately achieved. The stability of the microgrid system was analysed in detail to verify the feasibility of the coordinated virtual impedance control scheme. Experiments on a laboratory prototype microgrid are performed to validate the performance of the proposed control scheme. [ABSTRACT FROM AUTHOR]

This study develops a three-stage energy management system (EMS) for renewable energy microgrid operation. The core of this framework is based on a unit commitment problem integrated with model predictive control (MPC) to address the problem of uncertainty in renewable sources. Meanwhile, it is shown that an MPC approach may be insufficient to fully address the hurdles for optimal and safe operation of wind power-integrated energy systems due to the severity of wind speed fluctuations within even short time intervals. Spinning reserve resources can have a positive impact to ensure a reliable operation, yet their availability is highly dependent on the existence and capacity of dispatchable energy sources, such as diesel generators, in energy systems. Consequently, a supplementary Constrained Information Gap Decision Theory approach is utilised in this study to optimise the system's robustness against severe uncertainty of wind generations. In order to evaluate the presented framework, a descriptive index is first introduced, and then the model is applied to an isolated microgrid. The results indicate that by deploying these three stages, the renewable energy support index increases, ensuring an optimal, reliable, and safe operation. [ABSTRACT FROM AUTHOR]

This study presents a model predictive control (MPC)-based centralised control approach for maintaining the voltages of the nodes within permissible limits in the presence of high photovoltaic (PV) penetration. The proposed control scheme coordinates the actions of on-load tap changer (OLTC) and PV inverters optimally to fulfil the desired objectives. The objectives are minimisation of change in control variables, slack variables, energy loss, and voltage error. These objectives are weighted to form the overall objective function. Three rules are formulated based on the severity of voltage magnitudes. The weights of the objectives are adjusted according to these pre-defined rules. Simulations are performed in an active distribution network (ADN) integrated with and without microgrids, where both demands and generations vary hourly over the day. As power is injected by the microgrids during most of the time of the day, the excursions of node voltages are slightly higher in the microgrids integrated ADN. Moreover, the incorporation of the proposed rule-based MPC drastically reduces the energy loss due to active power loss in distribution networks, as is evident from the simulation results obtained by comparing the proposed approach with an existing MPC-based approach. [ABSTRACT FROM AUTHOR]

Distributed energy resources such as solar photovoltaic, wind and energy storage systems are increasingly being utilised within isolated and grid-connected microgrids. Their integration has prompted the move towards more advanced coordinated control for flexible, efficient and secure operation of microgrid-based power systems. This study presents a new power control method based on a canonical inverse model and implied synthetic inertia (SI), which is implemented on a voltage source converter-based power generator (VSC-PG) for frequency response support. The control method augments a traditional power controller whilst the SI technique is blended with a new switching mechanism which enhances the performance of the VSC-PG when it is utilised with SI provision capability. The switching mechanism acts only when necessary, without contradicting the main frequency regulating sources. For assessment, the above method and SI technique have been designed and modelled for a 630 kVA VSC-PG with DC-link battery bank. The VSC-PG was connected within an isolated/remote microgrid formed by an 11 kV feeder, 1 MVA diesel generator and variable load. The performances of the proposed power controller and SI provider have been tested and analysed using detailed Matlab/Simulink simulations and found to compare favourably with methods published in the literature. [ABSTRACT FROM AUTHOR]