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Abstract A novel control mechanism is presented for rural microgrids, standing out in the current literature with its advanced approach to load prioritisation and energy allocation. The system's main goal is to maximise energy supply to essential loads while effectively managing available resources. Distinct from traditional methods, this mechanism dynamically classifies loads according to user‐defined priorities, adjustable based on the control system's computational power and complexity. A critical feature is the utilisation of the Particle Swarm Optimisation (PSO) algorithm to optimise demand side management (DSM). This innovative approach leverages day‐ahead load and generation forecasts to ensure optimal energy distribution across load levels, maintaining continuous power supply to high‐priority loads and reducing blackout risks due to generation and load fluctuations. Analyses under stochastic scenarios demonstrate the robustness of the control action, with percentile‐based day‐ahead forecasting allowing for adaptation to significant variations in renewable energy generation patterns. The implementation results are significant, maintaining 100% supply continuity to essential loads throughout the day, even with generation fluctuations up to ‐20%. This marks a considerable improvement in load satisfaction, increasing it from 83% to 96%. A significant advancement in microgrid control is contributed, providing an adaptive, user‐centric approach that enhances load management and energy distribution, and facilitates more resilient and efficient microgrid systems in the face of highly variable renewable energy sources (RESs).

Today’s power system is transforming into an increasingly complex entity, consisting of numerous components, such as transmission lines, controllable loads, and especially different types of distributed renewable energy sources (DERs). With the growing integration of DERs into the grid, multiple operational challenges arise, including overvoltage, undervoltage, or increased energy losses. Resolving these issues demands the implementation of both advanced and effective control strategies. As the dynamic power system evolves by incorporating new technologies, these control strategies need to consider other different technical aspects, such as communication protocols or real-time considerations. Additionally, the rise of smart metering devices has transformed conventional power systems into cyber-physical power systems (CPPS), which can integrate the advanced control strategies into the cyber layer. Given the operating challenges and the integration of diverse technologies, it is proposed that a CPPS testbed platform constitutes an ideal solution for developing and validating technologies in future smart grids. For this purpose, this paper introduces a co-simulation framework for implementing a CPPS testbed, utilising the real-time simulator, Typhoon HIL, within a laboratory environment. Additionally, it presents a proposed optimal power flow (OPF) control strategy that emphasises two key objectives, minimisation of operating costs and power network loss. The investigation is illustrated by a modified version of IEEE 39-bus test system with the high integration of DERs. The findings indicate that adopting a CPPS testbed can be advantageous for implementing real-time research on monitoring and control in a wide area network.

Abstract Future distribution networks (DN) are subject to rapid load changes and high penetration of variable distributed energy resources (DER). Due to this, the DN operators face several operational challenges, especially voltage violations. Optimal power flow (OPF)‐based reactive power control (RPC) from the smart converter (SC) is one of the viable solutions to address such violations. However, sufficient communication and monitoring infrastructures are not available for OPF‐based RPC. With the development of the latest information communication technology in SC, cyber‐physical co‐simulation (CPCS) has been extensively used for real‐time monitoring and control. Moreover, deploying OPF‐based RPC using CPCS considering the controller design of SC for a realistic DN is still a big challenge. Hence, this paper aims to mitigate voltage violations by using OPF‐based RPC in a real‐time CPCS framework with multiple SCs in a realistic DN. The OPF‐based RPC is achieved by performing the CPCS framework developed in this study. The CIGRE medium‐voltage DN is considered as a test system. Real‐time optimization and signal processing are achieved by Python‐based programs using a model‐based toolchain of a real‐time DN solver and simulator. Real‐time simulation studies showed that the proposed method is capable of handling uncertain voltage violations in real time.

Despite there are significant advancements in modern power systems, blackouts remain a potential risk, necessitating efficient restoration strategies. This paper introduces an innovative concept for power system restoration, focusing on balancing active and reactive power while ensuring voltage stability. For instance, this paper employs an agglomerative clustering technique, which partitions the power system into segments with balanced reactive power, facilitating swift restoration postblackout. Central to this methodology is the use of the line stability factor, which assesses the voltage stability of individual lines, identifying the system’s stronger and weaker sections based on voltage stability levels. This paper demonstrates the effectiveness of the proposed methodology through case study analysis, comparing voltage stability levels across agglomerative clusters and their geographical locations. The power system is divided into two stable partitions, considering the number of black-start generators, available reactive power, and voltage stability levels. This partitioning reveals that the clusters formed by the agglomerative method are inherently stable, suggesting enhanced system stability, dependability, and availability during the restoration phase following a blackout. In addition, this paper discusses the potential causes of blackouts, offering insights into their prevention, and finishes with a novel clustering methodology for power systems, considering reactive power and voltage stability. This method facilitates the parallel restoration of the system’s independent partitions, significantly reducing restoration time; it addresses critical challenges and outcomes, underscoring the methodology’s potential to revolutionize blackout recovery processes in modern power systems.

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.

Because power electronic converter (PEC) dominated power generators do not provide the rotational inertia and the proportion of synchronous generators is reducing, the modern electrical grids are confronting a challenge of transient stability as the penetration rate rises. Analyzing the system characteristics is important for minimizing possible instabilities during regular operation as well as during emergencies. In this article, the parametric sensitivity of indicators for rotor angle stability is analyzed by taking a case study of a power system. The indicators are identified and investigated for different case scenarios with varying inertia constants. From the study, it is observed that if the inertia in any segment of a power system is lowered, the critical fault clearing time (CCTs) for an individual element will be decreased. Although all cases and sub-cases used in the analysis were found to be stable, the reducing inertia constant has a substantial influence on the results.

The growing installation of distributed energy resources (DERs) in a distribution network (DN) poses substantial issues related to voltage regulation. Due to constrained switching operation and slower response time, traditional voltage regulation devices cannot handle current voltage-related challenges. One alternative to solve these problems is to use smart converters to control the reactive power to regulate the voltage. Volt-Var control (VVC) is one of the simplest approaches for controlling the reactive power from smart converters. Among several converters, grid forming converters (GFCs) are more suitable in DER-enriched distribution networks. Since DER-enriched distribution networks have a higher fluctuation in voltage profile, real-time control is advantageous. Therefore, this work presents an advanced real-time reactive power control for handling voltage violations in a DN using GFC. The uniqueness of this method is that it controls the voltage magnitude of affected nodes by dispatching reactive power from smart converters in real-time. By running cyber-physical co-simulation (CPCS) between the Typhoon HIL 604 and OpenDSS, the Volt-Var control can be done in real time. The grid-forming converter is modelled in Typhoon HIL 604, which acts as a physical layer of the proposed cyber-physical system for real-time VVC. A CIGRE medium voltage distribution network is designed in OpenDSS and serves as one of the parts of the cyber layer. The CPCS between Typhoon HIL and OpenDSS and the control algorithm are both done by a programme written in Python. The execution of the control algorithm is performed in real time using the Supervisory Control and Data Acquisition (SCADA) developed in this study. The real-time simulation shows that the proposed real-time VVC is capable of handling voltage violations in real time in DER-enriched distribution networks.

Abstract The conventional structure of operating transmission and distribution systems is currently experiencing new challenges in maintaining the system operability with the significant changes such renewable energy sources inclusion, technology development, infrastructure revolution, and services provision. A futuristic operation management paradigm at the high level of interaction between Transmission System Operators (TSOs) and Distribution System Operators (DSOs) is presented that supports the usage of flexibility services to simplify the congestion management, and ancillary services procurement by involving the DSO actively in the DSO‐TSO boundaries and the downstream network. The architecture considers new actors such as Distributed Services Aggregator, Prosumers, and Services Market Operators. A comparison between the typical grid structure (including the short‐term smart grid requirements) and the proposed one is presented considering different actors and interactions involved in the operation management of the grid. The opportunities and challenges of the proposed architecture are discussed.

The transient stability analysis of large-interconnected power systems using time-domain simulations (TDS) is a significant challenge since it represents a huge computational cost. Besides, for dynamic security assessment is required have a quick response. Consequently, recent approaches are relying on using the wide-area measurement system combined with other techniques to perform transient stability assessment and counteract the drawbacks of the TDS method. However, these approaches still requiring to perform TDS to set initial parameters. This paper proposes a new algorithm to estimate the critical clearing time (CCT) based on the eigenvalue calculation and the singular value decomposition using data from wide-area measurement systems. The proposed algorithm uses the phase angles of the voltage phasors measurements at the generation buses to represent the dynamics of the internal angles of the generators. First, from a set of signals, a measurement matrix is formed using a sliding window. Then, a threshold based on the maximum singular value and the dominant eigenvalue of the measurement matrix are computed. Finally, the CCT is estimated using the dominant eigenvalue (the most energetic eigenvalue) and the threshold. The proposed algorithm is evaluated using the Kundur four-machine system and New England 39-Bus system. Its performance contrasts to the CCT calculated using the classical TDS. The simulation results demonstrated acceptable precision of the CCT against TDS. Also, it presents robustness against the effect of the noise in the measurements. Therefore, it is suitable for online applications.

The power system continuously deals with frequency fluctuations. When a power disturbance occurs, the transmission system operators rely on the underfrequency load shedding (UFLS) scheme to address severe underfrequency (UF) events to maintain the frequency at the permissible level and prevent blackouts. Defining settings of a conventional UFLS scheme is a very complex problem due to the nonlinear nature of the frequency response, and the size of the problem is vast because of the number of UF-relays spread on the power system. The under or over total load disconnection produced by the wrong setting of the UF-relays can create secondary frequency events or even a total blackout. This paper introduces a novel method to compute an optimally parametrized conventional UFLS scheme in specific given operating conditions by formulating it as a constrained problem and using the Improved Harmony Search (IHS) algorithm to solve it. Since there is no previous knowledge of using IHS to solve the UFLS scheme, a numerical parameter sensitivity analysis (PSA) is developed to tune the parameter of the IHS algorithm. The IEEE 39-bus system was modelled in DIgSILENT® PowerFactory™ and used as a test system. The optimally parametrized conventional UFLS methodology presented in this paper reveals superior results against the conventional UFLS scheme, and the suitability of using the IHS algorithm is confirmed.

The oscillatory behaviour of the power system is an aspect that is significantly affected by the increasing integration of converter-based generation sources. Several works address the impact of non-synchronous generation on the operation of the system from different points of view, but only a few studies focus on power-frequency oscillations with a prevalence of generation sources interfaced through power electronics. A lack of research can be found in particular in the comparative analysis of the two main control strategies for power converters, namely grid-following and grid-forming. The article aims to contribute to this direction, starting from a theoretical analysis of the two control structures and then examining the case study of an existing transmission system. The research provides a specific insight into the fundamental aspects related to synchronisation mechanism and inertial capabilities of both grid-following with synthetic inertia and grid-forming controls. The difference in the relationship between synchronisation unit and inertial capability is recognised as the fundamental aspect determining the different impacts on the oscillatory characteristics of the system. The observation derived in the theoretical analysis is then applied to an actual power system with a high predominance of converter-based generation, considering the Colombian interconnected national system as a case study.

The need for Phasor Measurement Units (PMUs) is rising as renewable energy sources become more prevalent in power networks since the rate of change of frequency is being deteriorated. Appropriate and accurate network measurements are a requirement for the precise monitoring and control of the system. This paper presents a low-cost PMU development, the so-called PhasorsCatcher, for the frequency and rate of change of frequency measurements in power networks, using sufficient but straightforward modular and reconfigurable friendly technology for its implementation. The entire hardware design, schematics, and instrumentation components are shown. Moreover, the visualisation has been calibrated and verified through an experimentation set-up and the existing electrical and communication standards.

Induction motors are key pieces of equipment in today’s society, powering a variety of industrial drives and home appliances. The induction motor speed is often used to monitor the performance of all kinds of industrial drives. For example, in the industrial field, the motor speed is very often used to determine the efficiency and mechanical load of motors. In this work, a new simple, low-cost, and nonintrusive procedure is proposed for infield measurement of induction motors speed, which is based on the spectral analysis of the vibration signal of the motors. The motor vibration signal is first acquired using the accelerometers integrated into a basic phone. The acquired signal is then treated by a MATLAB-based algorithm, which can determine the motor speed by identifying the mechanical frequency of the rotor shaft from the harmonic content of the vibration signal. In this way, it is shown that the mechanical frequency corresponding to the speed of rotation of the motors can be acquired by means of the embedded accelerometers of a common smartphone, avoiding the acquisition and installation of external accelerometers. To the authors’ knowledge, this could be the first time that a smartphone has been proposed as a practical means of measuring the speed of a motor by analysing its vibration. Experimental results from an extensive set of tests, including the supply of the motor from a frequency converter, show that the speed can always be measured with a relative error of less than 0.15%.

Generation dispatching is a challenge in islanded microgrids due to the operational and economic restrictions in isolated zones. Furthermore, the impact of usual operational network changes in topology, load demand, and generation availability may become significant considering the grid size. This research paper presents a detailed multiple cost function modeling methodology of an optimal power flow algorithm applied to a non-interconnected zone in Colombia. The optimal power flow (OPF) formulation includes cost functions related to renewable resources as presented in the isolated zone and a complete model of the charging and discharging of batteries. Additionally, the flexibility of the proposal is tested using three different network topologies with a characteristic daily load curve from the zone. The main contribution of this paper lies in the implementation of an optimal power flow including cost functions of renewable sources for isolated microgrids. A test case for a non-interconnected zone in Colombia is performed for various operation cases.

The increased use of distributed energy resources, especially electrical energy storage systems (EESS), has led to greater flexibility and complexity in power grids, which has led to new challenges in the operation of these systems, with particular emphasis on frequency regulation. To this end, the transmission system operator in Great Britain has designed a control scheme known as Enhanced Frequency Response (EFR) that is especially attractive for its implementation in EESS. This paper proposes a Type-2 fuzzy control system that enables the provision of EFR service from a battery energy storage system in order to improve the state-of-charge (SoC) management while providing EFR service from operating scenarios during working and off-duty days. The performance of the proposed controller is compared with a conventional FLC and PID controllers with similar features. The results showed that in all scenarios, but especially under large frequency deviations, the proposed controller presents a better SoC management in comparison without neglecting the EFR service provision.

Electricity markets provide valuable data for regulators, operators, and investors. The use of machine learning methods for electricity market data could provide new insights about the market, and this information could be used for decision-making. This paper proposes a tool based on multi-output regression method using support vector machines (SVR) for LMP forecasting. The input corresponds to the active power load of each bus, in this case obtained through Monte Carlo simulations, in order to forecast LMPs. The LMPs provide market signals for investors and regulators. The results showed the high performance of the proposed model, since the average prediction error for fitting and testing datasets of the proposed method on the dataset was less than 1%. This provides insights into the application of machine learning method for electricity markets given the context of uncertainty and volatility for either real-time and ahead markets.

Modern distance relays have integrated numerous protection functions, including power-swing blocking and out-of-step or pole-slip tripping functions. The main purpose of the power-swing blocking function is to differentiate faults from power swings and block distance or other relay elements from operating during stable or unstable power swings. Most power-swing blocking elements are based on traditional methods that monitor the positive sequence impedance rate. The required settings for the power-swing blocking elements could be difficult to calculate in many applications, particularly those where fast swings can be expected. For these cases, extensive stability studies are necessary to determine the fastest rate of possible power swings. This paper presents a detailed step-by-step method for settings calculation of out-of-step (OOS) protection, both blocking and tripping functions considering a generic two-source system. Then the method is applied to define the protection relay settings installed at the interconnection between the Russian and Mongolian power systems, as it is crucial to feed the demand-rich Mongolian power system. In this paper, a specific impedance method is used for defining the OOS protection settings. This paper innovates by testing the settings using the recordings of the major events of 15 September 2018 in two approaches: hybrid co-simulation and cyber-physical. Both tests have demonstrated the appropriate performance of the proposed settings and proving the proposed methodology works appropriately.

With the increasing penetration rate of Power Electronic Converter (PEC) based technologies, the electrical power systems are facing the problem of transient stability since the PEC based technologies do not contribute to the system inertia, and the proportion of synchronous generators (i.e., the source of inertia) is in decreasing rate. In addition, PEC based technologies’ components have poor inherent damping. It is very important to analyze the system characteristics of a power system to minimize the potential instabilities during the contingencies. This paper presents the parametric sensitivity analysis of the rotor angle stability indicators for the 39-bus New England power system. The indicators of rotor angle stability analysis such as critical fault clearing time (CCT), Eigenvalue points, damping ratio, frequency deviation, voltage deviation, and generator’s speed deviation are identified and analyzed for three case scenarios; each scenario has six sub-cases with different inertia constants. The results show that the CCTs for each component will be reduced if the inertia reduces at any section of a multi-machine power system. Although the applied three scenarios with six sub-cases are identified to be stable in this analysis, the decreasing inertia constant has significant impact on the power system dynamics.

The reactive power control mechanisms at the smart inverters will affect the voltage profile, active power losses and the cost of reactive power procurement in a different way. Therefore, this paper presents an assessment of the cost–benefit relationship obtained by enabling nine different reactive power control mechanisms at the smart inverters. The first eight reactive power control mechanisms are available in the literature and include the IEEE 1547−2018 standard requirements. The ninth control mechanism is an optimum reactive power control proposed in this paper. It is formulated to minimise the active power losses of the network and ensure the bus voltages and the reactive power of the smart inverter are within their allowable limits. The Vestfold and Telemark distribution network was implemented in DIgSILENT PowerFactory and used to evaluate the reactive power control mechanisms. The reactive power prices were taken from the default payment rate document of the National Grid. Simulation results demonstrate that the optimal reactive power control mechanism provides the best cost–benefit for the daily steady-state operation of the network.

The European Union considers that offshore wind power will play a key role in making the EU the first climate-neutral continent by 2050. Currently, the potential of offshore wind energy is still untapped in Spain. Furthermore, the characteristics of the coastline in Spain require floating technology, making it challenging to install wind farms due to their current high cost. This work seeks to quantify the impact that Spanish offshore wind energy would have on the Iberian electricity market. Several offshore wind scenarios are evaluated by combining available information in relation to areas suitable for installing wind farms and wind resource data. The impact on the day-ahead electricity market has been obtained by reproducing the market, including these new offshore wind generation scenarios. The introduction of this renewable energy results in a market cost reduction in what is known as the merit-order effect. According to our estimates, for each MWh of offshore wind energy introduced in the market, there would be a market cost reduction of 45 €. These savings can serve as a reference for regulators to adjust their policy framework to boost floating wind offshore generation.

Today, the power system operation represents a challenge given the security and reliability requirements. Mathematical models are used to represent and solve operational and planning issues related with electric systems. Specifically, the AC optimal power flow (ACOPF) and the DC optimal power flow (DCOPF) are tools used for operational and planning purposes. The DCOPF versions correspond to lineal versions of the ACOPF. This is due to the fact that the power flow solution is often hard to obtain with the ACOPF considering all constraints. However, the simplifications use only active power without considering reactive power, voltage values and losses on transmission lines, which are crucial factors for power system operation, potentially leading to inaccurate results. This paper develops a detailed formulation for both DCOPF and ACOPF with multiple generation sources to provide a 24-h dispatching in order to compare the differences between the solutions with different scenarios under high penetration of wind power. The results indicate the DCOPF inaccuracies with respect to the complete solution provided by the ACOPF.

The massive integration of variable renewable energy (VRE) in modern power systems is imposing several challenges; one of them is the increased need for balancing services. Coping with the high variability of the future generation mix with incredible high shares of VER, the power system requires developing and enabling sources of flexibility. This paper proposes and demonstrates a single layer control system for coordinating the steady-state operation of battery energy storage system (BESS) and wind power plants via multi-terminal high voltage direct current (HVDC). The proposed coordinated controller is a single layer controller on the top of the power converter-based technologies. Specifically, the coordinated controller uses the capabilities of the distributed battery energy storage systems (BESS) to store electricity when a logic function is fulfilled. The proposed approach has been implemented considering a control logic based on the power flow in the DC undersea cables and coordinated to charging distributed-BESS assets. The implemented coordinated controller has been tested using numerical simulations in a modified version of the classical IEEE 14-bus test system, including tree-HVDC converter stations. A 24-h (1-min resolution) quasi-dynamic simulation was used to demonstrate the suitability of the proposed coordinated control. The controller demonstrated the capacity of fulfilling the defined control logic. Finally, the instantaneous flexibility power was calculated, demonstrating the suitability of the proposed coordinated controller to provide flexibility and decreased requirements for balancing power.

Stable power supply has become a crucial thing in the current era of technology and automation. Although the power system has multiple stability issues and causes, frequency fluctuation plays a vital role in normal operation, whereby a system with significant frequency deviation can lead to the needless blackouts of the whole power system. With the rapid growth in power electronic converter (PEC)-based technologies and the huge penetration of nonsynchronous generators, the modern power system is becoming more complex by the day. This paper provides a comprehensive study on the stability issues that occur in modern power systems, mainly due to PEC-based technology integration. The in-depth reasons and the impacts of unstable power systems, along with their controlling techniques, are discussed to generate a clear understanding. Furthermore, the importance of frequency stability in a power system is discussed with respect to some important events that occurred in the past. This paper also discusses some potential techniques that could be performed to overcome the existing and/or upcoming challenges in the upgrading power system.

Withthe massive penetration of electronic power converter (EPC)-based technologies, numerous issues are being noticed in the modern power system that may directly affect system dynamics and operational security. The estimation of system performance parameters is especially important for transmission system operators (TSOs) in order to operate a power system securely. This paper presents a Bayesian model to forecast short-term kinetic energy time series data for a power system, which can thus help TSOs to operate a respective power system securely. A Markov chain Monte Carlo (MCMC) method used as a No-U-Turn sampler and Stan’s limited-memory Broyden–Fletcher–Goldfarb–Shanno (LM-BFGS) algorithm is used as the optimization method here. The concept of decomposable time series modeling is adopted to analyze the seasonal characteristics of datasets, and numerous performance measurement matrices are used for model validation. Besides, an autoregressive integrated moving average (ARIMA) model is used to compare the results of the presented model. At last, the optimal size of the training dataset is identified, which is required to forecast the 30-min values of the kinetic energy with a low error. In this study, one-year univariate data (1-min resolution) for the integrated Nordic power system (INPS) are used to forecast the kinetic energy for sequences of 30 min (i.e., short-term sequences). Performance evaluation metrics such as the root-mean-square error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE), and mean absolute scaled error (MASE) of the proposed model are calculated here to be 4.67, 3.865, 0.048, and 8.15, respectively. In addition, the performance matrices can be improved by up to 3.28, 2.67, 0.034, and 5.62, respectively, by increasing MCMC sampling. Similarly, 180.5 h of historic data is sufficient to forecast short-term results for the case study here with an accuracy of 1.54504 for the RMSE.

The replacement of conventional generation sources by DER creates the need to carefully manage the reactive power maintaining the power system safe operation. The principal trend is to increase the DER volume connected to the distribution network in the coming years. Therefore, the microgrid represents an alternative to offer reactive power management due to excellent controllability features embedded in the DER, which enable effective interaction between the microgrid and the distribution network. This paper proposes a microgrid–iterative reactive power management approach of power-electronic converter based renewable technologies for day-ahead operation. It is designed to be a centralised control based on local measurements, which provides the optimal reactive power dispatch and minimise the total energy losses inside the microgrid and maintain the voltage profile within operational limits. The proposed optimal-centralised control is contrasted against seven local reactive power controls using a techno-economic approach considering the steady–state voltage profile, the energy losses, and the reactive power costs as performance metrics. Three different reactive power pricing are proposed. The numerical results demonstrate the optimal microgrid–interactive reactive power management is the most suitable techno-economic reactive power control for the day–ahead operation.

The increasing deployment of wind power is reducing inertia in power systems. High-voltage direct current (HVDC) technology can help to improve the stability of AC areas in which a frequency response is required. Moreover, multi-terminal DC (MTDC) networks can be optimized to distribute active power to several AC areas by droop control setting schemes that adjust converter control parameters. To this end, in this paper, particle swarm optimization (PSO) is used to improve the primary frequency response in AC areas considering several grid limitations and constraints. The frequency control uses an optimization process that minimizes the frequency nadir and the settling time in the primary frequency response. Secondly, another layer is proposed for the redistribution of active power among several AC areas, if required, without reserving wind power capacity. This method takes advantage of the MTDC topology and considers the grid code limitations at the same time. Two scenarios are defined to provide grid code-compliant frequency control.

The Altai-Uliastai regional power system (AURPS) is a regional power system radially interconnected to the power system of Mongolia. The 110 kV interconnection is exceptionally long and susceptible to frequent trips because of weather conditions. The load-rich and low-inertia AURPS must be islanded during interconnection outages, and the under-frequency load shedding (UFLS) scheme must act to ensure secure operation. Traditional UFLS over-sheds local demand, negatively affecting the local population, especially during the cold Mongolian winter season. This research paper proposes a novel methodology to optimally calculate the settings of the UFLS scheme, where each parameter of the scheme is individually adjusted to minimise the total amount of disconnected load. This paper presents a computationally efficient methodology that is illustrated in a specially created co-simulation environment (DIgSILENT® PowerFactoryTM + Python). The results demonstrate an outstanding performance of the proposed approach when compared with the traditional one.

The decommissioning of synchronous generators, and their replacement by decoupled renewable power plants, has a significant impact on the transient stability performance of a power system. This paper concerns with an investigation of the degree of transient stability enhancement that can be achieved in power systems with high shares (e.g., around 75%) of wind generation. It is considered that the wind generators can work either under the principle of current control or under the principle of fast local voltage control. In both cases, a power–angle modulation (PAM) controller is superimposed on the current control loops of the grid side converters of the wind generators. The investigation of the degree of enhancement takes into account different approaches of the tuning of PAM. It considers a simple approach in the form of parametric sensitivity, and also a sophisticated approach in the form of a formal optimization problem. Besides, the paper gives insight on what is a suitable objective function of the optimization problem, which entails the best performance of PAM. The whole investigation is conducted based on a synthetic model of the Great Britain (GB) system

The integration of renewable resources is quickly growing in the Nordic power system (NPS), and it has led to increasing challenges for the operation and control of the NPS. Nordic countries require that the first-generation power plants have a more flexible operation regime to overcomes power imbalances coming from fluctuations of the demand and supply. This paper assesses optimal frequency support of variable-speed hydropower plants installed in Telemark and Vestfold, Norway, considering future scenarios of NPS. The total kinetic energy of the NPS is expected to be significantly reduced in the future. This paper looks into the implementation of hydropower units with a variable-speed operation regime and battery energy storage systems (BESS), equipped with fast-active power controller (FAPC) technology, to provide fast frequency response after a system frequency disturbance. The frequency support was formulated as an optimization process; therefore, the parameter of the FAPC was optimally calculated for future scenarios of low inertia in NPS. Three main futures scenarios were developed for technology penetration in the Vestfold and Telemark area in Norway. The simulation results showed that the integration variable-speed hydropower units and BESS technologies improved the frequency response even in low-kinetic energy scenarios.

During the last few years, electric power systems have undergone a widespread shift from conventional fossil-based generation toward renewable energy-based generation. Variable speed wind generators utilizing full-scale power electronics converters are becoming the preferred technology among other types of renewable-based generation, due to the high flexibility to implement different control functions that can support the stabilization of electrical power systems. This paper presents a fundamental study on the enhancement of transient stability in electrical power systems with increasing high share (i.e., above 50%) of power electronic interfaced generation. The wind generator type IV is taken as a representative form of power electronic interfaced generation, and the goal is to investigate how to mitigate the magnitude of the first swing while enhancing the damping of rotor angle oscillations triggered by major electrical disturbances. To perform such mitigation, this paper proposes a power-angle modulation (PAM) controller to adjust the post-fault active power response of the wind generator type IV, after a large disturbance occurs in the system. Based on a small size system, the PAM concept is introduced. The study is performed upon time-domain simulations and analytical formulations of the power transfer equations. Additionally, the IEEE 9 BUS system and the test model of Great Britain’s system are used to further investigate the performance of the PAM controller in a multi-machine context, as well as to perform a comparative assessment of the effect of different fault locations, and the necessary wind generators that should be equipped with PAM controllers.

This paper presents a comprehensive analysis of the effect of the converter synchronizing methods on the contribution that Battery Energy Storage Systems (BESSs) can provide for the support of the inertial response of a power system. Solutions based on phase-locked loop (PLL) synchronization and virtual synchronous machine (VSM) synchronization without PLL are described and then compared by using time-domain simulations for an isolated microgrid (MG) case study. The simulation results showed that inertial response can be provided both with and without the use of a PLL. However, the behavior in the first moments of the inertia response differed. For the PLL-based solutions, the transient response was dominated by the low-level current controllers, which imposed fast under-damped oscillations, while the VSM systems presented a slower response resulting in a higher amount of energy exchanged and therefore a greater contribution to the support of the system inertial response. Moreover, it was demonstrated that PLL-based solutions with and without derivative components presented similar behavior, which significantly simplified the implementation of the PLL-based inertia emulation solutions. Finally, results showed that the contribution of the BESS using VSM solutions was limited by the effect of the VSM-emulated inertia parameters on the system stability, which reduced the emulated inertia margin compared to the PLL-based solutions.

This study proposes a very effective formulation to carry out the security-constrained direct current (DC)-based optimal power flow (OPF) problem using two linear factors: (i) the power transmission distribution factors (PTDF) and (ii) the line outage distribution factors (LODF). The security-constrained (SC) DCOPF problem has been reformulated using these linear distribution factors, and mainly the pre- and post-contingency constraints have been added into the optimization problem based on the active power unit generation (decision variables). The main advantage of this formulation is the reduction of decision variables as well as equality and inequality constraints. To validate the introduced formulation, several experiments have been conducted using MatPower, DIgSILENT Power Factory and Gurobi. Simulation results demonstrate both the feasibility to carry out the SCOPF problem and the potential applicability of the proposed formulation to medium and large-scale power systems.