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Energy efficiency is more and more important for modern electrified transportation systems, requiring an understanding of the various indexes of performance (regenerability, receptivity, and energy losses, thus including braking recovered energy and energy loss in catenary) and of the influence of the main system parameters (headway, line voltage, substation separation, etc.). By means of electromechanical simulation, the most relevant parameters and system conditions are identified as influencing the efficiency performance and optimization capability. Besides the assessment of such efficiency performance indexes, identifying their typical ranges of variation, one further outcome is the identification of characteristic system parameter combinations that lead to extreme variations in the system energy efficiency itself. Such peculiar variations are caused by occasionally synchronized patterns of trains along the line and result in a significant local increase or decrease in efficiency. Efficiency drop scenarios in particular should be taken into consideration for worst-case analysis and to devise effective mitigations. To this aim, the effect of differently distributed passenger stations is considered.

Accurately calculating the transmission‐line constants of underground cables is important for various types of power system simulations such as electromagnetic transient, power flow, and transient stability simulations. The transmission line constants of cables installed in a tunnel must be calculated taking the skin and proximity effects into account, since the cables are spaced closely to each other and also to a wall face of the tunnel. However, the conventional method, which is capable of considering the skin and proximity effects, has been restricted to circular cross‐section conductors such as cables and a circular tunnel. Therefore, the method cannot handle a tunnel with a rectangular cross section. In this paper, a method for calculating the transmission‐line constants of a conductor system in which both circular and rectangular cross‐section conductors present in the same space is proposed. Then, the walls of a rectangular tunnel are represented by eight rectangular conductors, and cables represented by circular conductors are placed inside the eight rectangular conductors. In this paper, the proposed method is verified by experiments using a conductor system in which three circular conductors are arranged in a rectangular conductor. Calculated results obtained by the proposed method agree well with the measured results. [ABSTRACT FROM AUTHOR]

Summary: The intermittent, random, and uncertain characteristics of the energy harvested from solar or wind are threatening the commercial efficiency and reliability of power system. With the continuous expansion of renewable energy installation scale, it has become a new challenge to improve the level of renewable energy accommodation and reduce the rate of renewable energy abandonment. Power system production simulation provides basis for the planning and development of renewable energy to assess the capacity of renewable energy accommodation in the power grid accurately. Traditional power system production simulation ignores sequential variation characteristics of load and new energy power output, thus bringing non‐negligible errors. Moreover, most reported studies ignore the impact of power source location on the level of renewable energy accommodation. This paper is therefore prepared with the objective to establish a time‐series production simulation model of multi‐energy power system and carry out multipoint layout planning and design of multi‐energy power supply. To achieve this objective, extensive literature reviews are conducted with more attention given to recent studies on the field. On the basis of the traditional production simulation model, this paper adds the power flow constraints of the transmission network, and proposes a time‐series production simulation model. A multipoint layout planning and design method for multi‐energy power systems is proposed to give full play to the synergistic effects of natural resources, to achieve optimal resource allocation, and to provide a theoretical basis for improving the consumption of wind and renewable energy. The method is simulated with the actual meteorological and operation data of a province power grid in Northwest China. The simulation results of different scenarios are compared and analyzed, and the effectiveness of the method is verified. [ABSTRACT FROM AUTHOR]

As a result of their natural capacity to recover harmonic current and reactive power from alternating current sources, power electronic devices utilized in conjunction with nonlinear loads have the potential to generate significant harmonic problems within the power system when employed in this way. When this occurs, voltage instability occurs, which must be avoided in order to maintain the consistency and dependability of the power system's power flow. With this approach, the series controller has been replaced by a multilevel modular controller in order to improve power handling capability and achieve higher modular levels with minimal distortions. The shunt compensator is the most effective way to achieve an extremely protected energy system as well as righteous steadiness in electric potential difference under a variety of load constraints. The DQ thesis is employed in this proposed converter to separate the harmonic components by establishing reference frame current, which is accomplished by machine learning techniques. As part of the constant mode operation, the PI controller contributes to maintaining the direct current-potential difference, which is given to the PWM generator. Optimization of the values of K p and K i is accomplished by the use of particle swarm optimization (PSO). The construction of this power system simulation model has been made feasible by the use of time-fluctuating characteristics modeling and the MATLAB programming environment. The new (unified power flow controller) UPFC research that has been made available is persuasive in its capacity to reduce distortions and watt-less power components while simultaneously enhancing efficiency and reducing costs. [ABSTRACT FROM AUTHOR]

Identifying the sensitivity of future power systems to climate extremes must consider the concurrent effects of changing climate and evolving power systems. We investigated the sensitivity of a Western U.S. power system to isolated and combined heat and drought when it has low (5%) and moderate (31%) variable renewable energy shares, representing historic and future systems. We used an electricity operational model combined with a model of historically extreme drought (for hydropower and freshwater‐reliant thermoelectric generators) over the Western U.S. and a synthetic, regionally extreme heat event in Southern California (for thermoelectric generators and electricity load). We found that the drought has the highest impact on summertime production cost (+10% to +12%), while temperature‐based deratings have minimal effect (at most +1%). The Southern California heat wave scenario impacting load increases summertime regional net imports to Southern California by 10–14%, while the drought decreases them by 6–12%. Combined heat and drought conditions have a moderate effect on imports to Southern California (−2%) in the historic system and a stronger effect (+8%) in the future system. Southern California dependence on other regions decreases in the summertime with the moderate increase in variable renewable energy (−34% imports), but hourly peak regional imports are maintained under those infrastructure changes. By combining synthetic and historically driven conditions to test two infrastructures, we consolidate the importance of considering compounded heat wave and drought in planning studies and suggest that region‐to‐region energy transfers during peak periods are key to optimal operations under climate extremes. Key Points: Contemporary and future Western U.S. power grids are evaluated with stochastic and historically based compound climate extreme scenariosDrought has most impact on simulated generation mix and production cost; load changes under heat have more impact on regional power flowTotal summer regional power flows decrease in the future power system simulations, but power flows remain critical during peak hours [ABSTRACT FROM AUTHOR]

Low‐frequency oscillation (LFO) analysis has become increasingly important in large scale power systems. The current LFO analysis methods regard the measured signal as stationary signal. Some methods, such as Prony and HHT, are too slow for online application. In order to solve these problems, based on the long short‐term memory neural network (LSTM), this paper proposes a method to identify LFO modal features rapidly. It is the first time in this field to formulate LFO modal feature classification problem rather than LFO modal identification problem. In order to realize it, first, LFO's frequency and attenuation factor are artificially divided into 12 and 4 segments, respectively. For each segment, more than 20,000 data are generated and tagged as training set and test set. Then two bi‐directional LSTM networks are constructed separately, and each network is trained alone with the data of the training set. Finally, the proposed method is tested and verified with the data from the test set, power systems simulation, and phasor measurement unit (PMU) of real power systems. The test results prove effectiveness of the proposed method and its advantage is demonstrated through comparison with the Prony, FFT and EDSNN methods. [ABSTRACT FROM AUTHOR]

Power system planning is essential for ensuring development of a safe and stable power system. Articles on power system planning have been published in recent decades. In this paper, bibliometric analysis is applied to power system planning to identify its basic characteristics, and to summarize the research hotspots and trends. A total of 4562 publications were obtained from the Web of Science during 1971–2020. The 4562 publications cover 8136 keywords, 1526 journals, 107 countries/territories, and 2519 institutions. IEEE Transactions on Power Systems is the key journal in power system planning; USA, China, and England are the countries that dominate publication production. Research hotspots and trends were analyzed using author-keyword co-occurrence analysis and keyword burst detection. Four clusters were identified and topics from Cluster I (central nodes as power system stability and transient stability) and Cluster IV (central nodes as power system simulation and economics) are important for power system planning research. However, their relative popularities have declined over the past two decades. This indicates that Cluster II (central nodes as renewable energy, wind power, and energy storage) and Cluster III (central nodes as distributed generation and smart grids) will be the focus of future research. [ABSTRACT FROM AUTHOR]

The assessment of transient stability of multi-machine power system, in a post-fault scenario, is a very challenging task due to highly non-linear nature of the system equations. In this work, the physical concept of maximum relative acceleration of a machine at a fault scenario is related with the boundary of stability region. This approach is extended to develop a quadratic Lyapunov function using singular perturbed modelling. Unlike the conventional energy function methods, this Lyapunov function candidate is a more general energy function and has a decaying nature around an equilibrium point. Moreover, with higher order corrections, an improved Lyapunov function candidate is presented with simulation results of power system examples. The decaying nature of Lyapunov function candidate remains similar even without higher order corrections. However, the relevance of inclusion of higher order corrections is brought out in the cases of faults occurring at other than generator buses. Also, the upper bound of singular perturbation parameter in the model is within allowable limits and ensures the accuracy of results. [ABSTRACT FROM AUTHOR]

Accurate evaluating the lightning induced voltages of distributed networks has been the subject for several decades. The technique on the interface between the field-to-line coupling model and power system simulators are of particular interest. In this article, a solution of the Agrawal's field-to-line coupling model is derived and an easy-to-implement macro-model is developed. Combining with the “Frequency Dependent (Phase) Model” component included in PSCAD, the proposed macro-model can be directly integrated into PSCAD to evaluate the lightning induced voltages on the overhead lines. The validity and efficiency of the proposed method is demonstrated by several examples. Finally, a 1-km 35 kV overhead line above an imperfectly conducting ground is studied, and the influences of the metal-oxide arrester to the lightning induced voltages are discussed. [ABSTRACT FROM AUTHOR]

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In the daily demand profile of the Sri Lankan power system, it can observe a significant-excessive peak in the evening from 6.30 p.m. to 10.30 p.m. and another between 5.30 a.m. and 6.30 a.m. It is revealed that two peaks in the daily load profile had been caused due to the usage of the domestic sector. Since level off this daily electricity demand cycle, by flattening the peak & filling the valley is a necessity. Suggestions to introduce a low-cost battery storage system which will get charged during off-peak hours and use this stored energy during peak demand time will be a low-cost option to reduce the matter. The present study proposing a mathematical model to level off the daily load profile in Sri Lanka by utilizing concept of storing energy gathered from the main grid during the off-peak hours and reusing it during the on-peak hours. To develop the model three types of the household were selected based on the monthly consumption of 90 units, 150 units, and 180 units. Analysis of the household load profile of an average middle-class house utilizing 180 kWh, 150 kWh and 90 kWh per month shows that during peak hours, it will utilize around 3 kWh, 2 kWh and 1 kWh per day respectively. This can be stored in a low-cost battery by charging it during off-peak hours (say from 11.00 pm to 5.00 am) & can be utilized during peak demand time of 6.30 pm to 10.30 pm. As a storage device, a novel household battery technology will be introduced with 160 Ah (~2kWh) and 250 Ah (~3kWh) capacity. The model house that we have considered uses 3 kWh per day during the peak demand time, therefore proposed, 3 kWh storage battery to be installed with charging & inverter circuits. This house will not draw electricity from the national grid during peak hours. This energy saving option, even though it will not generate electrical energy by way of installation of a solar panel or any other renewable option, this will be a low-cost option to the household while saving a massive cost to the nation. This will also maximize the capacity utilization of all existing generation plants. [ABSTRACT FROM AUTHOR]

The escalating integration of renewable energy sources necessitates enhanced power system flexibility. Gas units, with their rapid start-stop capabilities, emerge as crucial assets for system operators grappling with supply-demand fluctuations. This paper proposes a novel multi-stage fully adaptive distributionally robust unit commitment (MFA-DRUC) model to optimize the operation of these flexible units under the uncertainties inherent in real-time dispatch. Leveraging the Wasserstein metric, our approach significantly expands the feasible solution space compared to traditional multi-stage adaptive unit commitment (MA-DRUC) models, bolstering resilience against extreme scenarios. To overcome the computational challenges posed by the model's multi-stage structure, we introduce a mixed approximation rule (MAR) that effectively handles high-dimensional variables and strong coupling characteristics. By employing duality theory, we transform the unit commitment (UC) problem into a computationally tractable mixed-integer linear programming problem. Comprehensive simulations across power systems of varying scales, encompassing scenarios such as coal-fired unit decommissioning and gas unit integration, validate the efficacy of our proposed MFA-DRUC model. These results underscore its potential to enhance the reliability and efficiency of power systems navigating the complexities of a renewables-driven future. • A multi-stage unit commitment model considering the sequential decision-making characteristics of practical power systems is developed. • The start-up and shutdown of gas-fired units during intra-day rescheduling are incorporated to provide a larger feasible region. • A mixed approximation rule based on nonlinear lifting operators is proposed to enhance solution accuracy for the high-dimensional variables and strong coupling arising from the multi-stage structure. • A distributionally robust unit commitment model is constructed using the Wasserstein metric to address the uncertainty of renewable energy. • Leveraging optimization theory, the unit commitment model is reformulated as a mixed-integer linear programming model. [ABSTRACT FROM AUTHOR]

This paper studies the frequency fluctuation problems of a multi-area power system with renewable energy sources (RESs) under denial-of-service (DoS) attacks. (i) Due to the decoupling of the RESs from power system using electronic devices, the RESs have no natural frequency response capability, which result in decreasing of entire power system equivalent inertia with large penetration of RESs. (ii) DoS attacks cause the insecurity of network communication, which can vanish data transmission and yield data packet dropout. To address the above issues, a virtual synchronous generator (VSG) incorporated with load frequency control (LFC) method (VSG-LFC) is proposed by introducing a hybrid-triggered mechanism (HTM) to (i) reduce the system sensitivity to the penetration level of RESs; (ii) compromise between frequency regulation performance and the reasonable usage of network resource under unsecured communication environments. Then, a switched system model is constructed considering non-identical DoS attack situations. Furthermore, theoretical analyses using Lyapunov functional related methods are carry out for asymptotical mean-square stability with H ∞ performance on frequency regulation. Simulation evaluations of power system verify the effectiveness of this development. It shows that in a two-area power system frequency derivation performance indicators (IAE, ITAT, ISE) in A r e a 1 are reduced by (82.996%, 86.273%, 85.823%) and in A r e a 2 are reduces by (77.996%, 83.613%, 82.315%). • VSG-LFC is proposed to reduce the sensitivity to the penetration level of RESs. • An HTM is proposed to balance control performance and network utilization. • A VSG-LFC power system under DoS attack is reconstructed as a switched system. [ABSTRACT FROM AUTHOR]

This work proposes a convex methodology that uses power system measurements (power generation and total demand) to accurately estimate transmission loss coefficients (B -coefficients). The main contribution of this research is the possibility of incorporating the stochastic behavior of demand consumption in the final calculation of said coefficients. Power system simulations are considered, employing random variations in the active power injection of voltage-controlled nodes, in addition to power demands, using uniform or Gaussian distributions (for each variation, the power flow problem is solved using the classical Newton–Raphson approach). Based on the properties of the B -coefficients, a semi-definite programming model is proposed to obtain these parameters, considering that, for a power system with N g generators, 0. 5 N g N g + 3 + 1 measurements are required. The robustness of the proposed measurement-based optimization model is contrasted with a recent literature report using a linear solution method. Numerical results in the IEEE 14-, 39-, 57-, and 118- test feeders demonstrate the effectiveness of the proposed convex-based approach when using a different set of measurements (power system simulations) for cross variations, whose average estimation errors are between − 0. 1109 % and 3.3967% for all the tested cases. All the numerical simulations were carried out using the MATLAB software and the MATPOWER 7.1 tool. • A measurement-based approach using SDP allows for determining transmission losses coefficients. • A power flow solution generates data regarding power generation and losses for the proposed SDP model. • Cross-validation with 1000 simulation cases found low estimation errors in the tested transmission networks. [ABSTRACT FROM AUTHOR]

The modernization of power systems faces uncertainties due to fluctuating renewable energy sources, electric vehicle expansion, and demand response initiatives. These uncertainties require consideration in power flow analyses by calculating power flow across a spectrum of generation and load values. Traditional power flow methods, which rely on iterative solutions of non-linear equation sets, become computationally burdensome under these uncertain conditions. Surrogate models have been used to reduces the computational cost of power flow analysis under uncertainty. Recently, graph neural networks (GNNs) have gained increasing attention as surrogates for power system simulations. However, GNNs, similar to other machine learning models, require significant amounts of training data. This paper proposes an innovative approach combining a multi-fidelity methodology with a GNN-based surrogate model for efficient power flow calculations. This model is trained using both high-fidelity power flow simulations and low-fidelity power flow simulations. Our multi-fidelity GNN model not only reduces the cost of generating training data, but also outperforms both single-fidelity GNN models trained solely on high-fidelity data and conventional neural network models. Additionally, the proposed model exhibits robustness to minor topology changes and achieves reasonable performance with unseen topologies. The model's effectiveness is validated through simulations on standard IEEE systems. • The paper proposes a multi-fidelity GNN model for power flow analysis under uncertainty. • The proposed model combines high-fidelity and low-fidelity simulations to enhance training efficiency. • The proposed multi-fidelity model outperforms traditional and single-fidelity models in power flow calculation accuracy. • The proposed multi-fidelity model demonstrates robustness to minor grid topology changes, enhancing model adaptability. [ABSTRACT FROM AUTHOR]

A perfect combination of weather and a power system backed by battery-based energy storage enabled Ireland to break a renewable penetration record in February 2022, with 96 % of electricity demand covered by wind generation at its peak. In high renewable energy penetration scenarios seen worldwide, ensuring the resilience of power systems against major events has received increased attention. Supplementing traditional generation units with renewables and distributed energy resources (DER) in the energy mix to meet the load demand and net-zero emission goals has affected power system inertia, black-start readiness, service restoration, and operations. Maintaining adequate resources to retain black-start readiness in anticipation of widespread outages is becoming challenging. This study reviews the technical aspect of a 100 % inverter-based resources (IBR) based distributed restart zone (DRZ) to assist black-start. It investigates the feasibility of using a set of IBR control schemes to help restart a non-black start combined cycle unit by aggregated energy storage system and PV via transmission lines. Through assistance from power system operators, common operation practices are incorporated and simulated in a black start cranking path case study. Simulation results are reported and compared against the traditional practices based on hydropower. The results show that the IBR could supplement the traditional black-start resources. The functional requirements identified in this study would be useful for developing GFL and GFM inverter controls in the industry to enable black-start ancillary service by IBR. [Display omitted] • Shows how distributed renewables can reboot a power system post-blackout. • Proposed restart zone complements traditional methods, boosting grid resilience. • Simulations on a real power system prove distributed restart zones aid black-start. [ABSTRACT FROM AUTHOR]

• A zero-carbon hybrid powertrain based on an ammonia-hydrogen ICE is proposed. • Fuel supply strategy based on ammonia suppression hydrogen combustion knock is established. • A simulation model of the ammonia-hydrogen hybrid system is developed. • Ammonia-hydrogen hybrid systems are superior in both performance and economy. In the context of carbon neutrality, high efficiency, low carbon, and zero environmental impact have become an essential development direction of internal combustion engines (ICEs). Hydrogen energy has the advantage of having a high calorific value. It also has zero carbon emissions and is considered one of the significant alternative fuels for ICEs. Moreover, ammonia has a high octane number and has an anti-knock effect, which facilitates the mitigation of knock in hydrogen ICEs and potentially mitigates the negative impact of knock on engine volume power. Scholars have carried out some explorations on ammonia-hydrogen ICEs (AHICE), which have been applied in marine power systems. It is anticipated that AHICE will become one of the most significant development directions in the field of vehicle power systems in the future. However, there are still some problems with using AHICEs in passenger cars. The proposed work presented a zero-carbon hybrid power system based on an AHICE. Specifically, the external characteristics curve and power output boundary were obtained by bench experiments of the ICE under wide open throttle (WOT) conditions and diverse engine speeds and λ. Indeed, a hybrid system model consisting of an AHICE and a power battery was built where the AHICE was used to respond to the demanded power and the power battery was used to provide additional power and store the electrical energy converted from braking. Incidentally, an engine control strategy was developed to expand the knock limit and power boundary by dynamically adjusting the ammonia-hydrogen volume ratio. Finally, a hybrid power system simulation model was established based on MATLAB/Simulink. The CLTC-P and WLTC simulation results demonstrated that the zero-carbon hybrid system which comprised AHICE and power battery can work in the high efficiency area. The AHICE demonstrates lower fuel consumption while satisfying power requirements. This work provides a promising route to zero-carbon hybrid technology for the passenger car industry facing the challenge of carbon neutrality. [ABSTRACT FROM AUTHOR]

• The inherent physical information of the system is extracted from single-ended field data measurements. • The "target dataset" is generated via simulation, to minimize the gap between simulation and practical power system. • The proposed fault location method is compatible with digital fault recorders in practical substations, and works with a short data window of half a cycle before and during the fault. • The proposed data driven fault location method is validated using field data experiments. Data driven transmission line fault location methods have the potential to more accurately locate faults by extracting fault information from available data. However, most of the data driven fault location methods in the literature are not validated by field data for the following reasons. On one hand, the available field data during faults are very limited for one specific transmission line, and using field data for training is close to impossible. On the other hand, if simulation data are utilized for training, the mismatch between the simulation system and the practical system will cause fault location errors. To this end, this paper proposes a physics-informed data-driven fault location method. The data from a practical fault event are first analyzed to extract the ranges of system parameters such as equivalent source impedances, loading conditions, fault inception angles (FIA) and fault resistances. Afterwards, the simulation system is constructed with the ranges of parameters, to generate data for training. This procedure merges the gap between simulation and practical power systems, and at the same time considers the uncertainty of system parameters in practice. The proposed data-driven method does not require system parameters, only requires instantaneous voltage and current measurements at the local terminal, with a low sampling rate of several kHz and a short fault time window of half a cycle before and after the fault occurs. Numerical experiments and field data experiments clearly validate the advantages of the proposed method over existing data driven methods. [ABSTRACT FROM AUTHOR]

This paper presents an accurate and efficient initialization strategy for modular multilevel converters (MMCs) based on the shooting method, a numerical technique aimed at deriving the periodic steady-state operating condition of any circuit. This technique is compatible with MMC models of different levels of detail and whose control scheme may include modulation strategies and capacitor voltage balancing algorithms. Electromagnetic transient simulations of the NORDIC32 power system modified by adding a high-voltage direct current link with 128-level MMCs prove that the proposed initialization strategy allows starting simulations close to steady-state, thereby significantly limiting initialization transients and their corresponding extra CPU time. • We present a technique to initialize grids with modular multilevel converters (MMCs). • The proposed technique is based on the shooting method (SHM) and is purely numerical. • Initialization transients (and, thus, CPU time) are minimized by the SHM. • The approach is compatible with different MMC models and control schemes. • A benchmark grid is simulated to validate the accuracy and efficiency of the method. [ABSTRACT FROM AUTHOR]

Digital controllers are involved in every aspect of today's power systems, from local device-level to wide-area supervisory applications. However, the existing dynamic simulation tools are still struggling to capture an accurate response of such systems with adequate computational performance. The reason is that digital controllers introduce numerous discontinuities to the simulation and handling them is computationally expensive, thus forcing the users to compromise between accuracy and simulation performance. This paper investigates different traditional approaches for incorporating digital controllers in power system dynamic simulations and compares them with new interpolation-based approaches in terms of simplicity, accuracy, and performance. • Reviewing methods for numerical simulation of power systems with digital controllers. • Comparing the methods using case studies in terms of accuracy, and performance. • Providing insights on the Jacobian formulation, and their impact on performance. [ABSTRACT FROM AUTHOR]

This work provides an approach that automatically optimizes the component computations on graphics processing unit (GPU) devices from different vendors. The approach consists of a two-level optimization, where the first level considers the linear part of the computation for vectorization and applies mixed matrix formats to increase computational throughput further. Then, the second optimization level treats the combination of linear and non-linear parts as a black box and searches for the optimal configuration of parameters such as the degree of vectorization, the combination of matrix formats, and the group (of threads) sizes during parallel execution on GPU. Moreover, we also introduce constraints that reduce the optimization procedure's execution time. Finally, we select three different types of components that could be representative to computational tasks in power system and perform our optimization approach on these kernels. The computational performance is compared with unoptimized baseline and sparse linear algebra library based implementations, result shows that our optimization leads to better performance and more efficient memory utilization. • Automatic vectorization on linear algebraic operations. • Optimized memory access by combined matrix formats and storage strategies. • Automated benchmarking and code generation to allow automatic performance tuning. • Exploration space reduction algorithm to reduce benchmark time. • Performance outperforms the implementation based on linear algebra libraries. [ABSTRACT FROM AUTHOR]

• Introducing a modeling framework designed for simulating the power response dynamics of air-source heat pumps, tailored explicitly for high-speed demand-side response applications such as fast frequency response services. • Validating the real-time performance of the proposed modeling framework by demonstrating its deployment on conventional computational hardware, achieving a simulation rate of 10 kHz. • Presenting a Power Hardware-in-the-Loop experiment that employs the proposed model framework to implement a virtual heat pump, providing a valuable simulation tool for power system laboratories to design controllers for high-speed demand-side response applications. This paper presents a standard power-hardware-in-the-loop testing platform to simulate detailed air-source heat pump dynamics based on well-established modeling knowledge. Distributed air-source heat pumps can be potentially used for fast frequency response. However, using air-source heat pumps for rapid modulation cannot be based on the current assumptions of linear speed-power transient characteristics developed for low-speed temperature control applications. Customized setups with experimental validation options are needed to design the new fast frequency response compatible heat pump controllers. Most power system laboratories struggle to build a customized air-source heat pump, which hinders research progress. The proposed platform is relatively universal, can fit different heat pumps with minor modifications, and can be implemented on standard PHIL emulators in power system laboratories. Emulation results, real-time implementation details, and model complexity metrics are presented to assist in the transference of the setup to other laboratories. [ABSTRACT FROM AUTHOR]

Power systems around the world are rapidly transitioning to much higher shares of inverter‐based resources (IBRs) with few synchronous generators remaining online. IBRs and synchronous generators have fundamentally different dynamic performance characteristics resulting in a difference in the overall power system dynamic performance. IBRs are generally more flexible and controllable than synchronous generators; however, at the same time they exhibit significantly more complex control systems. Furthermore, new and emerging capabilities are being developed progressively and in particular the so‐called grid‐forming inverters (GFM). GFM offer several new capabilities not previously possible with conventional grid‐following inverters (GFL). However, they are not well understood currently when applied in a mega scale and moving forward when they will likely take over the role synchronous generators have been performing for several decades as the workhorse of system security support. Key questions currently in the technical community include the extent to which GFM shall be similar or different to each of the synchronous machines and conventional GFL, and how various control strategies can assist in maximising the grid support capabilities sought and minimise or ideally eliminate any adverse impacts. The objective of this special issue is to provide insights into some of these unknowns. [ABSTRACT FROM AUTHOR]

Abstract Modular multilevel converters (MMCs) are favoured in high voltage direct current (HVDC) systems because of huge energy transmission capacity and few harmonics. However, the complicated control and the intricate communication network introduce cyber delay that affects the system dynamics. The communication structure is discussed and delay components are studied. The authors derive the MMC‐HVDC system model considering the cyber delay effect. Padé approximation is utilised to transform the transcendental characteristic equation of the delay model into an algebraic equation so that the dynamics can be observed through the eigenvalues. The comparison between the established model and the simulation in Simulink validates the proposed model's accuracy. The exact delay margin and the root cause of losing the stability are also discussed. The results show that the model is able to obtain the delay margin with a tiny error caused by the omitted high‐order harmonics and the cyber delay destabilises the system by lowering the controller performances.

Trends in power system simulation that demand computationally-intensive, physics-based models may impede the acquisition of useful results for applications like condition-based maintenance, electrical plant load analysis (EPLA), and the scheduling and tasking of finite generation and distribution resources. A tool that can quickly evaluate many scenarios, as opposed to intense, high fidelity modeling of a single operating scenario, may best serve these applications. This paper presents a behavioral simulator that can quickly emulate the operation of a relatively large collection of electrical loads, providing “what-if” evaluations of various operating scenarios and conditions for more complete exploration of a design or plant operating envelope. The presented simulator can provide time-series data of power system operation under loading conditions and usage assumptions of interest. Comparisons to field data collected from a microgrid on-board a 270-foot (82 meter) US Coast Guard medium-endurance cutter demonstrate the utility of this tool and approach.

The electrification of the transportation sector poses an opportunity for reducing greenhouse gas (GHG) emissions from passenger vehicles. Electric vehicle (EV) charging through dynamic wireless power transfer (DWPT), known as roadway electrification, could shift EV demand profiles to better coincide with renewable electricity generation. However, this would be a very large new load and few studies evaluate the regional impacts of DWPT charging in a power transmission system. This paper defines methods that address dataset generation for passenger vehicle trips and models to evaluate regional impacts for this emerging technology. Household vehicle miles traveled (VMT) data form localized EV demand profiles through discrete-event simulation. This data serves as exogenous inputs for a Production Cost Model (PCM) of a synthetic transmission system based on the Electric Reliability Council of Texas's (ERCOT) network. EV charging methods are compared for both a 2018 baseline generation mixture and a high-renewable generation case incorporating 20 GW of installed solar photovoltaic (PV) capacity. The PCM employs unit commitment and economic dispatch (UC&ED) models to compare financial, environmental, and grid reliability impacts from EV charging across passenger EV adoption levels. In-transit charging could reduce grid operational costs by as much as 1.49%, with up to $13.7B saved in annual vehicle operational costs for consumers compared to gas-powered vehicles. Health impacts analysis from power plant and vehicle tailpipe emissions from this study show net health benefits increase by 40% for in-transit charging coupled with high renewable generation. Renewable resources provide an avenue for cost-effective in-transit charging with reduced emissions. The combination of dataset generation and open-source power system modeling establish a foundation for the holistic evaluation of regional DWPT impacts. • PEV dynamic charging with increased renewable generation has positive system impacts. • Public data informs vehicle-miles traveled datasets for energy consumption analysis. • In-transit wireless charging from PEVs decreases power system peak demand hours. • In-transit PEV charging aligns with solar power to reduce curtailment and total cost. • Net health benefits from PEVs improve with in-transit charging and renewable sources. [ABSTRACT FROM AUTHOR]

• Battery modeling allows accurate prediction of the parameters in long-term processes improving decision-making. • The generic modeling algorithm combines three methods in one model: the experimental database, the equivalent circuit, and the analytical equations. • The model input signals are power demand and environment temperature corresponding to power system simulations such as sizing procedures. • The generic model could easily be utilized for any ESS (with similar technology) by a few experimental procedures. The lengthy process of sizing and optimizing hybrid energy sources requires an accurate battery model. This paper presents a generic new energy storage system model premeditated to solve the optimization problem of the sizing procedure. The model comprises several methods, a lookup table, an equivalent battery circuit, and analytical equations. The database is created offline based on experimental results achieved under various conditions. In the first step, the model receives an external vector of signals comprising load power demand, instantaneous generated energy, and ambient temperature. Then, the algorithm predicts the impact of the load on the battery parameters by either interpolation or extrapolation. The results are utilized at an equivalent circuit that supplies the basic parameters and the battery constraints. Next, analytical methods reveal the more advanced parameters such as charge, supplied and remaining energy, etc. The results show that the proposed dynamic battery model can predict the battery states through all operating zones and under different battery conditions. The benchmark results present higher accuracy than other available models. The proposed model was employed in a sizing procedure to verify the model's accuracy. It was shown that the new model estimates the required source rating more precisely than standard models. Since the suggested algorithm is based on actual battery curves, it can be utilized for all types of batteries by reentering the data of any other battery. [ABSTRACT FROM AUTHOR]

The increasing incorporation of solar and wind energy sources into the power system results in a diminishing power system inertia, which compromises the security of power system operation. This paper introduces a new scheduling method for hybrid power systems (HyPS), focusing on frequency security. It considers the time-varying characteristics related to frequency security requirements and the interdependence of components, such as generation units and the delivery network. Firstly, the optimal objective is to minimize overall operational costs and the pressure on energy delivery, ensuring the reserve capacities for fast frequency regulation remained within the predefined limits. Secondly, the frequency constrained unit commitment (FCUC) problem is formulated as a Markov decision process (MDP), and a deep reinforcement learning (DRL) framework is integrated to correct the advanced scheduling scheme in real-time. Thirdly, the coordinated scheduling scheme dynamically adjusts to operational events like fluctuations and line failures in the HyPS by employing the reward function of a comprehensive assessment. Finally, numerical results demonstrate the practicality of the novel coordinated scheduling approach for hybrid power systems through simulations in the Grid2Op environment. As a result, the frequency security margin of the HyPS is capable of increasing the daily average level of the frequency security margin by 3% across diverse scenarios, including fluctuations in power demand, renewable energy variations, and power line failures. PE-interfaced renewable energy sources are thereby able to integrate with conventional synchronous units as a hybrid power system to support frequency regulation services. • A coordinated scheduling method improves frequency security by utilizing variable renewable energy sources. • The optimal scheduling method manages physical network stress while redistributing the controlled units. • A dynamic regulation module is designed to improve the real-time frequency security margin. • The dynamic regulation module is integrated with SAC for energy and reserve scheduling. [ABSTRACT FROM AUTHOR]

The annual yield of bifacial photovoltaic systems is highly dependent on the albedo of the underlying soil. There are currently no published data about the albedo of red soil in western Africa. In this study, the impact of the albedo of red soil in Ghana on the energy yield of bifacial photovoltaic systems is analysed. A bifacial photovoltaic simulation model is created by combining the optical view factor matrix with an electrical output simulation. For an exact simulation, the albedo of red soil at three different locations in Ghana is measured for the first time. The average albedo of every red soil is clearly determined, as well as the measurement span including instrumentation uncertainty; values between 0.175 and 0.335 were measured. Considering these data, a state-of-the-art bifacial photovoltaic system with an average of 19.8% efficient modules in northern Ghana can achieve an annual energy yield of 508.8 kWh/m2 and a bifacial gain of up to 18.3% in comparison with monofacial photovoltaic panels. To summarise, red soil in two out of three locations in Ghana shows higher albedo values than most natural ground surfaces and therefore positively impacts the annual yield of bifacial photovoltaic systems.

Real-time Simulation (RTS) is one of the effective means via which to study device level or system level dynamics, such as power converter online testing, evaluation, and control, and power system stability analysis. The RTS -enabled design-chain offers a time -effective, low-cost, and fail-safe development process. As the penetration of renewable energy is becoming higher, the demand in hybrid system real-time simulation becomes imperative, where fast-dynamic device level power converters and slow -dynamic large -scale power systems are simulated at the same time. This paper introduces a novel hybrid real-time simulation architecture based on the central processing unit (CPU) and the field-programmable gate array (FPGA). Compared with the off-the-shelf power system real-time simulation system, it offers both wide time scale simulation and high accuracy. The multi-time scale model can perform electromechanical electromagnetic transient hybrid simulation, which can be applied to the research of power systems penetrated with power converters. In the proposed simulation platform, the communication delay is introduced when different RTS platforms exchange real-time data. The communication delay should be considered in the stability analysis of the grid-connected inverters in a weak grid environment. Based on the virtual impedance characteristic formed by the control loop with and without communication delay, the impedance characteristics are analyzed and inter-simulator delay impacts are revealed in this paper. Theoretical analysis indicates that the communication delay, contrary to expectation, can improve the virtual impedance characteristics of the system. With the same hardware simulation parameters, the grid-converter system is verified on both the Typhoon system alone and the Typhoon-dSPACE-SpaceR hybrid simulation platform. The THD value of grid current in a weak grid environment that works in the Typhoon system is 4.98%, and 2.38% in the Typhoon-dSPACE-SpaceR hybrid simulation platform. This study eventually reveals the fact that the inter-simulation delay creates the illusion that the control system built in the novel hybrid real-time simulation is more stable under weak grid conditions. [ABSTRACT FROM AUTHOR]

The spread of distributed energy resources (DERs) across the distribution power system demands complex planning studies based on quasi-static-time-series (QSTS) simulations, requiring a significant amount of computing time to complete, leading planners to look for alternatives to QSTS. Diakoptics based on actors (A-Diakoptics) is a technique for accelerating simulations combining two computing techniques from different engineering fields: diakoptics and the actor model. Diakoptics is a mathematical method for tearing networks, reducing their complexity by using smaller subcircuits that can be solved independently. The actor model is used to coordinate the interaction between these subcircuits and their control actions, given the pervasive inconsistency that can be found when dealing with large-scale models. A-Diakoptics is a technique that simplifies the power flow problem for improving the simulation time performance, leading to faster QSTS simulations. This paper presents a simplified algorithm version of A-Diakoptics for modernizing sequential power simulation tools to use parallel processing. This simplification eliminates critical points found in previous versions of A-Diakoptics, improving the performance of the algorithm and facilitating its implementation to perform QSTS simulations. The performance of the new version of A-Diakoptics is evaluated by its integration into EPRI's open-source simulator OpenDSS, which uses standard computing architectures and is publicly available. [ABSTRACT FROM AUTHOR]

This paper presents injection‐shift‐factor‐based linear modelling for various types of series flexible ac transmission system (FACTS) devices within the DC power flow framework. The presented models allow FACTS devices to be properly integrated in current operation and planning software tools, which is key to harnessing the power flow capabilities provided by FACTS technology. Although recent literature has attempted to develop linear models for FACTS devices, the existing models do not accurately reflect the actual operating range for many FACTS devices. Compared to the existing models, the modelling approach presented here reflects the principle of operation of each type of series FACTS device in adjusting transmission line reactance. Through mathematical derivation, linear constraints for FACTS operation are formulated, which are used to formulate power system operation models. The formulated problems are then analysed through simulation studies on various test systems. The results highlight the significant computational efficiency improvements provided by linear FACTS modelling in DC‐based operation models. [ABSTRACT FROM AUTHOR]

This paper proposes a high‐speed and accurate method for extracting the arrival times (ATs) of traveling waves (TWs) in the power system that can be used for fault location applications and transmission line protection. The proposed method is based on the expression of the traveling wave as the exponentially damped component superimposed on the sinusoidal wave in a small time window. Also the sine component is removed by using approximation and consecutive differences of the input signal samples (the modal components of three‐phase voltages or currents) from the resulting wave. Due to the fact that the estimation of traveling wave arrival times (TWATs) is done applying basic mathematical operations in the time domain, the proposed method, in addition to the simplicity of implementation, has the appropriate accuracy and speed for applications such as online fault location and protection purposes. In order to evaluate the performance of the proposed approach in fault locating, a 230 kV transmission line is modelled in EMTP/ATP. Then, the fault location under various conditions of faults such as changes in location and type of fault, fault conditions as well as variations in the measurement noise level and sampling frequency are studied using MATLAB. [ABSTRACT FROM AUTHOR]

The study of integrated electricity systems that consist of several interconnected areas in the long term often results in large‐scale complex models, that are difficult to solve. The already large spatial size of these systems, combined with a fine‐grained time representation, necessary to capture the short‐term variability arising from the high penetration of renewable generation, increases the complexity of the problem, and thus, its computational cost. To overcome this issue, temporal reduction techniques are generally applied. However, the application of time aggregation in interconnected systems represents a challenge. The goal is to select the best possible time aggregation that considers at the same time the particularities of each of the areas that make up the whole system. To do so, the authors propose a new methodology for temporal aggregation in multi‐area energy system models. By implementing a multi‐dimensional clustering algorithm, the original hourly data is transformed into system states, or group of hours that share similar characteristics, reducing significantly the computational burden required to solve it. Together, an accurate representation of the variability of the system is achieved. The main conclusions are derived from a real‐size case study based on the electricity markets of three European countries. The sensitivity analysis performed shows the degree of accuracy of the results obtained, as well as the computing cost incurred for different temporal configurations. Ultimately, the results show the benefits of using this methodology over a more conventional approach. [ABSTRACT FROM AUTHOR]

In power distribution networks, there are many practical fault cases such as high impedance faults, faults and so on. Especially when the faults with electric arc persist, it is dangerous for human beings and circumstances. Nevertheless, it is difficult to classify faults due to various customer load conditions or the presence of distributed energy resources. In this paper, we propose a new mathematical arc model based on experimental event data. For implementing the arc phenomenon, wet gravel was used as a contact conductor after the fault. The experimental results validate the arc transient model. Then, the simulations were performed to verify the success of arc modeling using Kizilcay's arc model as a comparison method. Finally, we developed a fault detector using the kurtosis detection method, and power system simulations were conducted to evaluate fault detection performance using Matlab/Simulink. [ABSTRACT FROM AUTHOR]

With the development of dc renewable power generation and dc power consumption, more and more attention has been paid to residential low-voltage dc (RLVDC) power systems in recent years because of their advantages in conversion efficiency and control flexibility. Meanwhile, there are still some obstacles and challenges in the practical application of RLVdc due to the lack of standardization. One of the most important issues in RLVdc standardization progress is the voltage level standard. In this article, a comparative study on the performance of different RLVdc system voltage levels is presented. The main purpose of the article is to provide a voltage level selection guidance for energy prosumers and equipment manufacturers interested in RLVdc systems. The voltage levels commonly used in academia and industry, from 220 to 750 V, are compared and analyzed considering their influence on compatibility, topology, power supply capability, and safety. The article contains a research surveys, market statistics, power system simulations, and calculations with simplified models. The results of the comparative study show that ±375 V is optimal for the RLVdc system in cases with large power ratings and voltage levels below 240 V are suitable for RLVdc systems with special safety requirements. [ABSTRACT FROM AUTHOR]

Hydrogen-integrated transportation and power systems (HTPS) will become an important way to achieve the goal of carbon neutrality. As an important coupling unit of HTPS, the business mechanism of hydrogen fueling stations (HFS) is an important starting point for improving system economy and promotion value. This article proposed an interaction mechanism between HFS and HTPS and hydrogen and fuel cell EVs (HFEVs) in smart cities for HFS pricing strategies. First, we construct the framework of the HTPS interaction mechanism based on the basic combination of HTPS. Then, the interactive model of HTPS is constructed, including the scheduling model of HTPS, the pricing model of HFS and the response model of HFEVs. Finally, an HTPS system is constructed based on the improved IEEE 33-node power distribution system for simulation and analysis. The results show that the interaction mechanism and pricing strategy can improve the economics of HTPS and HFS, the operating cost of HTPS has been reduced by approximately 5.57%, the operating income of HFS has increased by approximately 4.17%. [ABSTRACT FROM AUTHOR]

Electric power utilities face a wide range of risks that cause financial uncertainty, with potential impacts on prices for customers. Among these, weather variability and retail load defection are perhaps two of the most studied. Whereas weather extremes expose utilities to unpredictable swings in electricity supply and demand, retail load defection, in which customers adopt distributed energy resources or switch to alternative providers, can alter utility business models fundamentally. We showed for the first time that these two phenomena can interact dynamically, with potential negative consequences for electricity ratepayers. We found that retail load defection could alter utilities' financial exposure to weather risk in a matter of years. Using open-source power system simulation software coupled with a utility financial model, we simulated outcomes for a major hydropower-producing California electric utility under stationary hydrometeorological uncertainty, and under three different load defection scenarios ranging from 0% to 90%. We found that as load defection increases, the utility's three main businesses (wholesale generation, transmission, and retail distribution) shift in relative importance. As a consequence, the impacts of interannual variability in hydropower production and demand in the utility's system (a function of streamflow and air temperatures, respectively) become significantly altered. Air temperatures (a proxy for demand) become more predictive of utility financial performance, whereas the utility's exposure to hydrology is poised to shift in complex ways. Drought will remain a major risk, but extremely wet years (which historically are beneficial to the utility's significant hydropower holdings) may become damaging due to their association with low market prices. Our results also suggest that load defection could put much more pressure on utilities to make major annual rate adjustments or quickly adapt current strategies for managing weather risk. [ABSTRACT FROM AUTHOR]

When a power transformer is reconnected to a power grid, if the residual flux in its iron core is large, significant inrush current may be generated and result in closing failure. Therefore, accurate residual flux measurement is necessary to avoid the harmful effects of inrush current. This work proposes a residual flux density measurement method for the power transformer core based on magnetising inductance. Firstly, when positive and negative DC voltages are applied along or opposite to the direction of the initial residual flux density, the measured positive magnetising inductance is smaller than the negative so that the direction of residual flux density can be determined by comparing their values. Secondly, the magnitude of residual flux density can calculated by analysing the empirical formula between residual flux density and positive magnetising inductance using the finite element method. Finally, this work takes the square iron core as the research object, establishes the corresponding empirical formula, and verifies its accuracy through experiments. The experimental results show that the proposed method has higher accuracy compared with the voltage integration method widely used in this field. [ABSTRACT FROM AUTHOR]

The detailed model of the back-to-back converter of the permanent magnet direct drive wind power system contains multiple power electronic devices, and the use of pulse width modulation technology will inevitably increase the mathematical calculation of the simulation system. In view of the problem, a mean value model is proposed to simplify the system so that the wind power system can operate quickly and stably. For the converter mean value model, the controlled power supply is used to replace the converter in structure, and its higher harmonics are ignored in principle, and only the fundamental wave component is retained. In addition, from the perspective of system control, the control strategy of the system is improved by removing the PWM modulation process. Finally, a permanent magnet direct drive wind power system simulation model is built in MATLAB/Simulink, and the system response of the mean model and the detailed model are compared. The simulation results show that the mean value model can not only meet the system accuracy requirements, but also speed up the system simulation speed, greatly improve the system stability, which verifies the rationality of the control strategy. [ABSTRACT FROM AUTHOR]

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This paper presents a novel approach to dynamic phasor-based transient stability simulation. The proposed method is based on the modified nodal analysis (MNA) approach to circuit simulation, which is used to construct continuous differential-algebraic equations (DAEs). The proposed method makes use of the stamp technique, which makes it possible to construct a general purpose MNA-based simulator. Stamp-based models for common power system components are derived in this work. A new MNA-based synchronous machine model is presented, which represents machines as nonlinear inductances instead of subtransient equivalents. The resultant continuous DAEs are numerically solved using the general purpose variable step and variable order library IDA. Simulation results from the IEEE 68 bus test system, a real 400 bus power system, and the IEEE 39 bus test system with an embedded HVdc transmission system demonstrate that the proposed method is suitable for large ac networks with power electronic devices. The results demonstrate good agreement between the proposed method and electromagnetic transient (EMT) simulation. The results also demonstrate that the proposed method is fast and scalable with CPU times that are up to 200 times faster than EMT simulation. [ABSTRACT FROM AUTHOR]

The power grid is transforming with large amounts of distributed energy resource (DER) integration that is impacting the bulk power system planning and operations. Grid regulators have identified that traditional power system analysis techniques are challenged under the changing grid conditions. Transmission and distribution (T&D) co-simulation is an effective methodology to accurately account for the changing power-grid. A scalable multitimescale T&D (SMTD) co-simulation framework is developed with commercial transmission system solver that can handle large-scale system models, and distribution system solver that can model the distribution systems in detail with dynamic models of load and DER. In this article, PSS/E and GridLAB-D are combined using a Python interface with Hierarchical Engine for Large-scale Infrastructure Co-Simulation software to enable T&D co-simulation. This framework is scalable and parallel computing compatible that enables large-scale system simulation and adoption of T&D co-simulation by the industry and utilities. The SMTD cosimulator is designed to integrate with existing system models and new ones. The article also highlights functional specifications for the T&D co-simulation solvers and models along with providing the algorithms for the steady state, quasi-steady state, and dynamic T&D co-simulation. In context of changing power grid, future power grid planning, validation of controls under critical contingencies and validation of various wide area monitoring and controls can effectively utilize the proposed framework that can capture the T&D interactions accurately. The SMTD cosimulator can also be used to generate realistic synthetic measurement-data with noise and packet drop for uncommon grid events enabling development and validation of power system data analytics and controls. [ABSTRACT FROM AUTHOR]

This paper aims to emphasize the approach on energy management with its principles and give a general overview of this field of industry. The basic functionality of power system control is found in the Supervisory Control and Data Acquisition (SCADA) function that collects and records values and statuses acquired from the power system elements via remote telemetry to enable control center operators to supervise and control the power system. [ABSTRACT FROM AUTHOR]

During the last decades, the use of sustainable energies instead of conventional fuel has been increased due to the global anxiety on environmental and economic problems like climate changes, the limitation of traditional resources, and the increase of electricity consumption. In the present work, design, modeling, and simulation of a Hybrid Power System (HPS), which is united a Wind Turbine System (WTS) with a battery bank, is presented. However, the power operation of the HPS is controlled by a power supervisory in order to reduce energy loss. The supervisory has been implemented in STM32F4 by using the 'PIL simulation' technology and tested under different scenarios of climatic conditions. The results indicate that, during a windy climatic condition, the proposed HPS is broadly enough to generate 100% of the required power with 0.005% of LPSP and 99.84% of RF. Whereas, through a moderate wind speed, the HPS reaches 0.675% of LPSP and 66.94% of RF. But, with a low wind speed, the HPS achieves 0.919% of LPSP and 26.10% of RF. Besides, the proposed WTS was broadly sufficient for supplying the needed power, with an empty battery, especially, when the available wind velocity is around 14.3 m/s at least. Furthermore, it illustrates the efficiency of the supervisory control. [ABSTRACT FROM AUTHOR]

Resilient distributed coordination control is studied on multiarea power systems with low inertia under hybrid attacks, including denial-of-service (DoS) attack and deception attack. The communication among various areas under the DoS attack is deteriorated to switching residual topologies whose time characteristic is modeled by model-dependent average dwell time (MDADT). Deception attack with malicious strategy targeting at negative feedback control is modeled by a sign function. To obtain resilience performance of the power system under low inertia and hybrid attacks, resilient distributed scheme combining load-frequency control (LFC) with virtual inertia control (VIC) is proposed. Then, resilient frequency control problem of the studied power system is converted to $H_{\infty }$ control of the switched nonlinear system. By employing the Lyapunov stability theory and switched system method, the resilient conditions are given by the lower bound of the average dwell time of each residual topology and the upper bound of deception attacks. Furthermore, a linear matrix inequality (LMI) technique is used to design the distributed resilient control gains of the LFC-VIC scheme. Finally, a simulation of four-area power systems is carried out to verify the validness of our theory. [ABSTRACT FROM AUTHOR]

Geomagnetically induced currents (GICs), a result of solar wind interaction with the Earth's magnetic field and the resistive ground, are known to flow in power transmission grids, where they can lead to transformer damage and grid operation problems. In this study we present an analysis of five years of continuous GIC measurements in transformer neutral points in Austria. Seven self‐designed stand‐alone measurement systems are currently installed in the Austrian 220 and 380 kV transmission levels, measuring currents up to 25 A. We identify recurrent geomagnetic activity in the measurements, and also find man‐made sources of low frequency currents using frequency analysis. In order to support the transmission grid operators, two GIC simulation approaches are used to simulate GICs in the power grid. The first model uses measurements to derive the sensitivity of the location to northward and eastward geoelectric field components (which requires no detailed grid data), and the second model uses the detailed grid model to compute GICs from a geoelectric field. We evaluate two geomagnetic storms from September 2017 and May 2021 to discuss the effects of GICs on the power transmission grid and its assets. Plain Language Summary: During geomagnetic storms, rapid changes in the Earth's magnetic field induce an electric field in the ground, may drive currents in the power grid. These are called geomagnetically induced currents (GICs) and they can lead to power grid operation problems and even transformer damage. In this study we present learning's from five years of GIC measurements in Austria, which have been carried out in seven different transformers in the grid. Some power grid transformers show larger susceptibility than other transformers to magnetic field variations accompanied by larger GICs. We also identify some of the sources of noise in the data such as a city subway system, and investigate two geomagnetic storms from September 2017 and May 2021 in more detail. Key Points: Measurements of geomagnetically induced currents (GICs) in power grid substation transformers have been carried out since September 2016 in AustriaWe summarize the measurements until now and discuss data quality and sources of noiseA statistical analysis of GIC measurements, a comparison of simulation models for two storms and an attempt to a risk assessment is performed [ABSTRACT FROM AUTHOR]