Search

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. ispartof: IET Energy Systems Integration vol:2021 issue:1 pages:1-12 status: published

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 ongoing reduction of the total rotational inertia in modern power systems brings about faster frequency dynamics that must be limited to maintain a secure and economical operation. Electrical energy storage systems (EESSs) have become increasingly attractive to provide fast frequency response services due to their response times. However, proper management of their finite energy reserves is required to ensure timely and secure operation. This paper proposes a deep reinforcement learning (DRL) based controller to manage the state of charge (SOC) of a Multi-EESS (M-EESS), providing frequency response services to the power grid. The proposed DRL agent is trained using an actor-critic method called Deep Deterministic Policy Gradients (DDPG) that allows for continuous action and smoother SOC control of the M-EESS. Deep neural networks (DNNs) are used to represent the actor and critic policies. The proposed strategy comprises granting the agent a constant reward for each time step that the SOC is within a specific band of its target value combined with a substantial penalty if the SOC reaches its minimum or maximum allowable values. The proposed controller is compared to benchmark DRL methods and other control techniques, i.e., Fuzzy Logic and a traditional PID control. Simulation results show the effectiveness of the proposed approach.

The increased penetration of distributed energy resources (DERs) installed in distribution networks via power electronic converters reduces the overall rotating inertia of the power system, causing faster frequency dynamics after a large disturbance. However, these DERs coupled with energy storage systems (ESSs) can be managed to provide valuable grid support functions such as fast frequency response (FFR) and assist the transmission system operator (TSO) in frequency control. In this study, single- and three-phase clusters of electric vehicles (EVs), acting as mobile-ESSs, are grouped together as virtual power plants (VPPs) to centralise the provision of FFR for the distribution system operator (DSO) whilst considering network unbalance. Furthermore, the parameters of the EV clusters within each VPP are optimised to minimise the inertia-weighed maximum frequency deviation following a disturbance whilst adhering to network security and power quality constraints. To this aim, a variant of the metaheuristic optimisation algorithm called improved harmony search is used for the optimisation process. Finally, the merits of the proposed methodology are shown with an illustrative example of an unbalanced three-phase transmission and distribution network modelled in DIgSILENT PowerFactory. The results show that clusters of EVs grouped as VPPs effectively improve frequency support via the TSO–DSO interaction.

Microgrid (MG) is one of the practical and best concepts to provide energy access to rural communities, where electric grid extension is not techno-economically feasible. Since the trend of load consumption is not uniform with a low load factor in a rural area, the required rating of the system becomes very high. Similarly, the generation is fixed for these MGs, whereas the load increases continuously over time. Such a system faces supply deficit issues triggering a high number of interruptions that may cause frequent blackouts. Hence, rolling blackout and load clipping techniques are preferred during the peak load period in most of the rural MGs. These issues lead to an unreliable power supply and low satisfaction level of the user. This paper presents the load prioritization technique to guarantee the continuous supply for the essential loads within the rural community. A day-ahead energy allocation technique is mathematically formulated and optimized to maximize the total hours of energy served. This technique maximized the hours of energy served to the load with higher priority followed by the load with lower priorities. From this study, it is found that the proposed strategy helps to improve the hours of energy served in the overall system, by improving the state of charge (SoC) level of the battery system. The result shows that the user satisfaction level has been improved by 5% through 100% of continuity for the essential loads.

Inverter based generation (IBG) is a necessary technology in the energy transition and reaching ambitious objectives of zero-net emission. However, the colossal penetration of IBG may create several issues. Using Voltage source converters (VSCs) equipped with the so-called grid forming control is thought of as a long-term solution of IBG-dominated power systems. This paper shows a glance of the dynamic performance during a system frequency event (SFE) considering three of the most common grid forming controller types used to emulate synchronous generation operation: Virtual Synchronous Machine (VSM), the Synchronverter and grid forming droop control; and compared with a classic synchronous generator (SG). Numerical results of time-domain simulations of a tests system show the enormous advantage of the grid-forming converters controls to provide an extremely fast frequency response when compared to the case of the traditional SG.

The static var compensator (SVC) mainly consists of a thyristor-controlled reactor (TCR) and a fixed capacitor (FC). In 2020, the install capacity of SVC was 30 MV Ar, which was connected to the South Energy System (SES) of the Mongolian power system (MPS). The primary purpose of the SVC is to compensate reactive power, increase voltage stability and reduce voltage fluctuations. However, TCR generates a high level of harmonic currents because of the thyristor's firing angle control. Therefore it is necessary to determine the effect of harmonics generated by the SVC on the power system and its components. To perform these analyses, it is needed to determine the harmonic characteristics of the grid at the point of SVC connection, existing levels of harmonics, and appropriate standards regarding acceptable harmonic levels in the power system. To calculate and design harmonics, an accurate harmonic model should be created in the simulation software. For example, the 6-pulse converter model of the DIg SILENT PowerFactory has not considered phase angles for unbalancing the system. Hence, the importance of modelling angles of the harmonics, measuring instrument, analysis of various waveforms are of interest to all engineers. Hence, in this paper, a harmonic model is considered harmonic current phase angles measured by a real system.

The shift to a sustainable energy future is becoming more reliant on large-scale deployment of renewable and distributed energy resources raising concerns about frequency stability. Rate of Change of Frequency (RoCoF) is necessary as a system inertia metric in order for network operators to perform control steps to preserve system operation. This paper presents in a straightforward and illustrative way several relevant aspects of the inertia response and RoCoF calculation that could help to understand and explain the implementation and results of inertial response controllers on power converter-based technologies. Qualitative explanations based on illustrative numerical experiments are used to cover the effects on the system frequency response of reduced rotational inertia in synchronous dominated power systems. One main contribution of this paper is making evident the importance of the governor action to avoid the synchronous machine taking active power from the system during the recovering period of kinetic energy in an under frequency event.

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.

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.

Sweden, a country with abundant hydro power, has expectations to include more wind power into its electrical system. Currently, in order to improve the frequency response requirements of its electr ...

The transformation of the traditional transmission power systems due to the current rise of non-synchronous generation on it presents new engineering challenges. One of the challenges is the degrad ...

The growing installation of distributed energy resources (DER) in the network allows an active interaction between the transmission and distribution system operators. This interaction is possible mainly by the power electronic converters (PECs) incorporated in the DER, used as an interface with the network. The PECs, also known as smart inverters, offers excellent controllability features and allow DER to provide procurement services to the distribution and transmission network. This paper focuses on evaluating the reactive power control features of the smart inverter considering eight control local modes following the IEEE 1547-2018 standard. Moreover, it is proposed an optimal reactive power controller able to minimise the active power losses in the network by optimally adapting the reactive power injection/absorption of the smart inverter. This optimal controller ensures all the busbar voltages are inside the permissible limits, and the reactive power limits of the smart inverter are enforced. The Vestfold and Telemark distribution network model was implemented using DIgSILENT PowerFactory to evaluate the optimal and the eight local reactive power control modes. Simulation results show the proposed optimal reactive power control is the best option to offer the service of active power loss minimisation using smart inverters for the daily steady-state performance of the DSO network.

This research paper proposes a methodology to apply identification methods to find a simplified model of three different governors in a single area electric power system (SAEPS). A SAEPS with different governors-turbine is presented: a hydraulic turbine, a steam turbine and a steam reheat turbine. In this same investigation, an analytic reduction has been performed, a fifth order system was found analytically, thus a transfer function equivalent to the three different governor-turbine elements was obtained, this equivalent transfer function models the complete behavior of the three devices. Two systems identification (SI) algorithms have been proposed to apply them to this generic subspace state-space (N4SID) and generalized poisson moment functionals (GPMF) electrical system, these presented similar results. The results of the performance and simulation analysis exhibit that using the SI technique, fifth, fourth and third-order systems were obtained that graphically show a very small estimation error compared to the original signal, this fact could be check simulating the simplified models using the same input-output data. The results are presented in a table that shows a comparison of the model respond the fifth, fourth, third and second-order systems.

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 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.

Mongolian power grid (MPG) is becoming more eco-friendly as the power system is continuously integrating renewable energy, which reached 20% of the total installed capacity of Mongolia in 2020. The daily operation and the safety of the MPG have become very challenging because of increased levels of energy in the system. Therefore, the dynamic behaviour of conventional power plants (CPPs) must be demonstrated to fulfil the requirements of integrating more renewable energy in the MPG, especially for frequency stability. This paper illustrates the results of the system parameter identification of an actual steam turbine and a governor system with PID controller by using a real-life test performed on Generator 1 (G1) of the biggest thermal power plant (TPP-4) in Mongolia on 6th March 2020. The main contribution of this paper is to clear uncertainties about the PID controller's parameters installed in the steam turbine of G1 in early 2019, consequently giving the system operator an accurate dynamic model of the generation unit. The steam turbine and governor are modelled in DIgSILENT® PowerFactory, and the Particle Swarm Optimization (PSO) method is used for identifying the parameters of the PID controller of the G1 at TPP-4. Simulation results from the PowerFactory software matched firmly (error

Frequency in power systems is a real-time information that shows the balance between generation and demand. Good system frequency observation is vital for system security and protection. This paper analyses the system frequency response following disturbances and proposes a data-driven approach for predicting it by using machine learning techniques like Nonlinear Auto-regressive (NAR) Neural Networks (NN) and Long Short Term Memory (LSTM) networks from simulated and measured Phasor Measurement Unit (PMU) data. The proposed method uses a horizon-window that reconstructs the frequency input time-series data in order to predict the frequency features such as Nadir. Simulated scenarios are based on the gradual inertia reduction by including non-synchronous generation into the Nordic 32 test system, whereas the PMU collected data is taken from different locations in the Nordic Power System (NPS). Several horizon-windows are experimented in order to observe an adequate margin of prediction. Scenarios considering noisy signals are also evaluated in order to provide a robustness index of predictability. Results show the proper performance of the method and the adequate level of prediction based on the Root Mean Squared Error (RMSE) index. article-number: 151 ispartof: Electronics vol:10 issue:2 status: Published online

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.

Power electronic converter (PEC) is an enabling technology for the energy transition, but the massive integration of PEC raises several issues. The use of Voltage source converters (VSCs) enabled with grid forming control offer a long-term solution of PEC-dominated power systems. This paper shows a glance of the dynamic performance during short-circuit of three common grid forming controller types emulating synchronous generation are implemented: Virtual Synchronous Machine (VSM), the Synchronverter and grid forming droop control; and compared with a classic synchronous generator. Simulation results, considering a single generator contacted to an infinite bus, show the grid-forming converters' high-speed and different behaviour compared to the synchronous generator.

The frequency stability of the power system is challenged by the high penetration of power electronic interfaced renewable energy sources (RES). Energy storage systems (ESS) are used to supply extra power injection to enhance the frequency stability during a disturbance. This paper presents a novel approach for improving the frequency dynamics by incorporating a designed ultracapacitor (UC) with a fully decoupled wind power generation (FDWG) unit. To this aim, a suitable model implementation of UC for real-time simulations is presented. The model constitutes a parallel RC branch, which is appropriate for illustrating the relevant fast UC dynamics that occur within the first milliseconds of the time period of action for fast active-power frequency control services. The frequency performance achieved by the support of the FDWG equipped with UC is compared against the performance achieved by using electrical batteries. The comparison includes the application of droop-derivative frequency control.

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.

A critical aspect of power systems is the generation cost of plants in producing the electrical energy required by consumers, this cost will be finally reflected in the monthly consumption bill. A nonoptimal dispatch will produce high tariffs while a well-designed dispatch will result in the lowest generation costs and, therefore, the lowest possible tariffs. The purpose of the present study is precisely to design a strategy to find the generation plan that produces the lowest possible costs and then make a comparison between an optimal economic dispatch that considers generation and transmission without energy contracts versus the dispatch that includes the 2017 energy purchase contracts signed by the state of Honduras. To achieve this goal, this study formulates the cost equation, capacity, and transmission line constraints, and then applies the nonlinear programming techniques to solve it.

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. Australian Education International, Australian Government TEC2016-80242-P Ministerio de Economía y Competitividad DPI2016-75294-C2-2-R

Variable-speed (VS) pumped storage technology has become a new trend for providing better support power system incorporating renewable energies. On the other hand, the transient stability of the power system can be affected by the application of such kind of storage unit. State-of-the-art pumped storage hydropower plants (PSHP) based on doubly fed induction machine (DFIM) known as variable-speed and conventional PSHP-based on synchronous machine (SM) known as fixed speed (FS) have a different effect on transient stability of a large-scale power system. This chapter intends to present the modelling and controller of DFIM-based PSHP of two types of PSHPs, i.e., VS and FS under generating operation mode in DIgSILENT software. Also, the IEEE 10-machine 39-bus system namely New England test system is adopted as a large power network. The results show that using DFIM-based VS-PSHP in the interconnected power grids, not only the oscillation modes of PSHP is eliminated, but also it can strongly improve rotor angle and voltage transient stability of the power system.

The transition to a low-carbon society is the driving force pushing the traditional power system to increase the volume of non-synchronous technologies which mainly use power electronic converters (PEC) as an interface to the power network. Today, PEC is found in many applications ranging from generation, transmission, storage, and even active loads and protections. The variety of types, applications is almost unlimited. However, the behaviour of PEC is radically different to the typical devices used in traditional power systems, and its specificity in terms of control, overload characteristics, etc. entails an entirely different approach for modelling and simulation. This chapter presents a general review of the main concepts related to power electronic converters and their implementation in DIgSILNET PowerFactory. The chapter finalises with a discussion about the modern tendencies in power electronic applications in power systems: grid following and grid-forming converters.

This research paper presents a rate of change of frequency (RoCoF) implementation using low-cost hardware in the loop (HIL) with application to Nordic Power System (NPS). Two methods to calculate the RoCoF are presented: Incremental difference one step and moving window (MW) or rolling window. HIL) approach is used to reach natural noise levels found in the frequency signal obtained from real power devices. The low- cost HIL implementation is based on two Arduinos ® in the loop. An Arduino ® working as standalone is used to generate an analogue signal representative of one area of the NPS, a second Arduino ® in the loop contains the RoCoF calculation methods and filters. This paper analyses the effect of including lowpass filters (LPFs) because the noise of the frequency affects the RoCoF calculation. Three cases are implemented in the Arduino ® and compared with Simulink ® /MTALAB™ simulations: Base Case: no filter and noise signal, Case I: LPF applied to the input frequency signal, Case II: LPF at the frequency signal and LFP at the output of the RoCoF (smoothing). Results demonstrate that RoCoF calculation methods worked correctly in the HIL and using two LPFs clean the signal from the noise produced by the Arduino ® .

Electric power generation in Albania has been almost totally dependent on hydropower since the system inception. In the last decade, although modest, there has been an increased share of power produced from Renewable Energy Sources (RES), mostly from Solar Power Plants. Looking forward, the Albanian government has considered the promotion of Renewable Energy as an important part of energy policies. Some of the future targets are to increase more the share of injected Renewable Energy in terms of hydro, Photovoltaic (PV) and Wind. Wind Energy is one of the most discussed sources regarding renewable energy penetration. Starting from feasibility studies to the quality of power, there are many issues to be addressed before installations of Wind Energy can be considered. This paper gives an overview of the studies performed regarding System Frequency Response (SFR) by replacing hydro inertia with non-synchronous generation. The paper presents a study of frequency behavior under several penetration levels of non- synchronous generation. Also presented are the results of study cases which show how system frequency is affected when replacing hydro-power inertia with wind turbine converter inertia.

This research investigates the positive changes in the system frequency response indicators caused by the implementation of a set of optimal settings of an under-frequency load shedding (UFLS) scheme. The optimal under-frequency load shedding (UFLS) scheme is optimised by minimising the total amount of load shedding and taking into account the recovery process of the system frequency into its operational values after several losses of generation and satisfies the requirements of the under-frequency load shedding standard (PRC-006-SERC-02). The idea of implementing the optimal UFLS scheme is to identify how changes the minimum frequency, minimum time, rate of change of frequency and steady-state frequency when the amount of load shedding change. The optimal UFLS scheme formulation starts with identifying the variables to control with the optimisation and its respective bounds. Then, the objective function is formulated in terms of the total load shedding, and finally, the restrictions and requirements of the systems are written as inequality constraints. The optimal UFLS is evaluated in the IEEE 39-bus system. The simulations results demonstrate the suitability of the optimal UFLS to improve the frequency response indicators.

Increasing amounts of non-synchronous generation in power grids are bringing reductions in system inertia. In a grid with extremely low inertia, the estimation of frequency indicators such as the frequency nadir can be used to feed into predictive system controls that would avoid nuisances such as triggering system protection systems, avoiding needless blackouts. In this paper, the timing of a frequency nadir is predicted using a Nonlinear Auto-Regressive (NAR) model based on an Artificial Neural Network (ANN). The estimation method is tested under a gradual inertia reduction in order to observe the adaptability of the method, under various prediction horizons.

Estimation systems based on PMU (Phasor Measurement Unit) data are a power system requirement based on the increasing expansion over the past decades. Kalman filter has been proved to be an adequate method for state estimation and data-driven methods. This paper applies the Unscented Kalman Filter to estimate in real-time the rotor angles. This paper proposes a predicting window as a time interval to forecast the rotor angle using real-time information. Emulated PMU sampling data have been used for carrying the simulations and have been validated using the 9-IEEE buses test system. The results confirm the method and the performance of the estimation.

The imminent transformation of the power grid with the large inclusion of renewable resources is bringing new challenges to face on. These challenges include an inertia diminution causing drastic changes in the frequency response. This paper analyses the impact of the gradual synthetic inertial control inclusion in the Nordic system as a possible remedial action to contribute in the primary frequency response. Additionally, it proposes slightly changes in the typical synthetic inertial controller to not only reduce the nadir but in the overshoot. Furthermore, the effect of proportional wind power curtailment in improvement of primary frequency response is assessed. Finally, several scenarios for the inertial controller and adjustments are tested in the Nordic 32 test system.

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.

Modern power systems are quickly evolving as many fundamental changes are currently taking place. On the one hand, there is an accelerated market transformation. For example, the European Union (EU) is moving fast to a single European electricity market, thereby increasing the volume of energy trade between countries. As a consequence, the cross-border transmission capacity is expected to increase until it reaches a reasonable target of 15% electricity interconnection by 2030 [1]. On the other hand, there is an unprecedented utilization of renewable energy and other low-carbon technologies, like the impressive expected 392 GW of offshore wind power to be installed in the North Sea, together with more Demand Side Management (DSM) and the new competitive market for Distributed Generation (DG) [2]. A common factor in the previous driving forces is the increasingly rapid number of uncertainties coming to play a critical factor in the planning and operation of the modern power system. This chapter is dedicated to present a complete overview of uncertainty modeling and the mechanism of modeling this in the steady-state permeance analysis of electrical power systems.

This paper investigates the positive changes in the system frequency response indicators caused by the implementation of a set of optimal settings of an under-frequency load shedding (UFLS) scheme. The optimal UFLS scheme is optimised by minimising the total amount of load shedding and considering the recovery process of the system frequency into its operational values after several losses of generation and satisfies the requirements of the UFLS standard (PRC-006-SERC-02). The idea of implementing the optimal UFLS scheme is to identify how changes the minimum frequency, minimum time, rate of change of frequency and steady-state frequency when the amount of load shedding change. The optimal UFLS scheme formulation starts with identifying the variables to control with the optimisation and its respective bounds. Then, the objective function is formulated in terms of the total load shedding, and finally, the restrictions and requirements of the systems are written as inequality constraints. The optimal UFLS is evaluated in the IEEE 39-bus system. The simulations results demonstrate the suitability of the optimal UFLS to improve the frequency response indicators.

Power systems can fail because of various reasons. Often, the effect of smaller failures is limited to the failure and repair of a single network component, as the power system is designed and operated considering \(N-1\,\) redundancy. Serious failures of the power system are therefore caused by combinations of component failures and other influencing factors. In probabilistic reliability analysis, the reliability of the power system is determined based on the reliability of individual components. This chapter discusses how failures of power system components can lead to a large blackout. Failure statistics of components are analyzed and historical blackouts are studied to obtain more insight into this matter.

Probabilistic reliability analysis starts with accurate modeling of the individual components within a system. In the previous chapter, it was explained how power systems can fail, while the failure process and failure statistics of power system components were discussed in detail as well. This information is used for modeling the reliability behavior of individual components within the power system. Several methods for component modeling are discussed in this chapter, starting with a description of the basic reliability functions in Sect. 3.1. Then, in Sect. 3.2 the life cycle of repairable components is discussed. The two-state Markov model is also often used to model the reliability of individual components and is described in Sect. 3.3, while the stress-strength model is shortly introduced in Sect. 3.4. General conclusions are summarized in Sect. 3.5.

Coping with severe active power imbalances constitutes a challenging task in low inertia multi-energy systems. The phase out of the majority of conventional power plants with large size synchronous generators entails that power electronic interfaced devices should take over the primary task of active power balance-frequency control. In view of this, the active power gradient (APG) control of these devices should be carefully designed to ensure effectiveness and to prevent collateral effects on other stability phenomena. This paper presents two novel formulations for the optimal tuning of the parameters of the APG controllers. Both formulations are defined as a constrained single objective optimization problem. The goal is to optimally manage the APG controllers to quickly bound the instantaneous frequency deviations excited by a large active power imbalance. The first formulation concerns with the minimization of the instantaneous variation of the kinetic energy of the synchronous areas of an interconnected system, whereas the second formulation concerns with the minimization of the spatial displacements between the dynamic trajectories of the time frequency responses in different synchronous areas. The formulations are solved by using a new proposed variant of the mean-variance mapping optimization algorithm (MVMO), and their conceptual implications are illustrated based on numerical simulations performed on a small-size multi-energy system.

This research paper proposes a framework to perform (hardware in the loop) HIL simulation in real-time (RT), the framework includes steps for the formulation of the Target RT Computer and Open Source System, which are important elements in RT modelling. In order to carry out tests, the implementation of the frequency response of a single area electric power system, including primary frequency control, is proposed. The electric power system was prepared to be implemented in the RT-Lab software that is compatible with MATLAB Simulink, in order to simulate in real-time with the Opal OP4510 device. Besides, the controller was designed in Simulink to be able to implement through the Arduino programming platform; they were also connected to work in HIL in RT. The results of the simulation and performance analysis show that for the case proposed with HIL, the primary control happens within a few seconds of the frequency variation. The control helps to reestablish the balance between the generated power and power demanded, thus stabilizing the system frequency. Elements formulated using this framework were successfully used in the primary frequency control.

The previous chapter described how to model the reliability of individual components. By combining several individual components, small systems are created. The reliability of these systems can be analyzed by combining the reliability models of the individual components. This chapter discusses the methods that are often used for reliability analysis of small systems. This chapter starts with a description of reliability networks in Sect. 4.1. Then, the application of Markov models to small systems is discussed in Sect. 4.2. Section 4.3 addresses how fault tree and event tree analysis can be used for reliability calculations. Final conclusions are then discussed in Sect. 4.4.

Power grids are increasingly dependent on operational technologies (OT) and information and communication technologies (ICT) networks for real-time monitoring and control of physical facilities. ICT and OT systems are coupled with the power grid and together, they form an interdependent and complex cyber-physical energy system (CPS). In this chapter, cyber security and resilience of power grids are discussed. The security controls and vulnerabilities of power systems are reviewed. Recent cyber intrusions and attacks confirmed the importance of cyber security and resilience of power grids to cyber attacks. A research program and an integrated CPS model are presented to assess and improve cyber security and resilience to cyber attacks and natural disasters of integrated cyber-physical energy systems.

Future plans for integration of large non-synchronous generation and the expansion of the power system in theNordic countries are a concern to transmission system operators due to the common interconnections and electricity exchangesamong these operative areas. The expected reduction in the inertia anticipates an alteration of the frequency response,provoking a high Rate of Change of Frequency (RoCoF) slopes that can jeopardise the security of the interconnected systems.Since power generation in the Nordic countries such as Sweden, Finland and Norway is hydro-dominated, here, the authorspropose a novel solution to tackle this problem including wide area measurements to monitor and share the RoCoF in remoteareas with lower inertia to enhance their primary frequency control. To demonstrate the effectiveness of the proposed solution,first a test benchmark control with optimised parameters is developed and later compared against the proposed method.Additionally, since the proposed solution is based on measurements from remote locations in order to guarantee the stability ofthe system the impact of delays in the communication channels is also included in the problem formulation.

This paper presents a comparison of computational time required to build the admittance matrix of five test systems (ranging from 200 to 70,000 nodes) considering two formation approaches: element-by-element and matrix approach. The algorithms have been implemented in MATLAB ™ and tested in four multi-core platforms. Implementations include sparse and dense matrix representation and parallel/non-parallel computing. Results show the matrix approach considering sparse representation and parallel computing is the best approach in computing time.

Extra-high-voltage (EHV) underground cables are becoming a preferred solution for new connections in transmission networks. The visual impact of high-voltage towers on the landscape and health concerns related to electromagnetic fields are the main drivers for society to prefer underground cables (UGCs), especially in densely populated areas. In the Netherlands, EHV underground cables have been installed recently as part of the Randstad380 project [1]. The configuration, i.e. double circuits of 2x2635 MVA with 2 individual cables per circuit phase, and the fact that these UGCs are part of the heavily loaded 380 kV transmission network make this project rather unique. This chapter studies the reliability of EHV underground cables and the impact on the reliability of large transmission networks.

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

Declining levels of rotational inertia in modern power systems prompt transmission system operators (TSOs) to develop novel ways of maintaining the balance between generation and demand. Services such as fast frequency response (FFR) can help the TSO achieve this balance. The growing penetration of electric vehicles (EVs) promotes the provision of FFR from clusters of EVs. Fast charging stations are more geared towards destination charging, whereas slow charging stations are more attractive as providers of FFR, given the longer connection times. In this study, the provision of FFR from EV clusters is formulated as a multi-objective optimisation problem with network security constraints and two minimisation objectives, i.e. the maximum frequency deviation following a disturbance and the energy provided by public EV charging stations. A methodology was developed to solve the optimisation problem with a variant of the non-dominated sorting genetic algorithm. This methodology allows the decision-maker to consider trade-offs among the objectives, leading to a more informed decision. An enhanced frequency-responsive aggregate model of an EV cluster was developed to study the provision of FFR in a multi-area power system. A reduced model of the Nordic power system was used to illustrate the performance of the proposed methodology.

This paper presents different forms of Fast Active Power Injection (FAPI) control schemes for the analysis and development of different mitigation measures to address the frequency stability problem due to the growth of the penetration level of the Power Electronic Interfaced Generation (PEIG) in sustainable interconnected energy systems. Among the studied FAPI control schemes, two different approaches in the form of a derivative-based control and a virtual synchronous power (VSP) based control for wind turbine applications are also proposed. All schemes are attached to the PEIG represented by a generic model of wind turbines type 4. The derivative-based FAPI control is applied as an extension of the droop based control scheme, which is dependent on the measurement of the network frequency. By contrast, the proposed VSP-based FAPI is fed by the measurement of the active power deviation. Additionally, unlike existing approaches for virtual synchronous machines, which are characterized by high-order transfer functions, the proposed VSP-based FAPI is defined by a second-order transfer function, which can contribute to fast mitigation of the system primary frequency deviations during containment period. The Great Britain (GB) test system, for the Gone-Green planning scenario for the year 2030 (GG2030), is used to evaluate the effects of the proposed FAPI controllers on the dynamics of the system frequency within the frequency containment period. Thanks to proposed FAPI controllers, it is possible to reach up to 70% for the share of wind power generation without violating the threshold limits for frequency stability. For verification purposes, a full-scale wind turbine facilitated with each FAPI controller is tested in EMT real-time simulation environment.

In the previous chapters, reliability models of individual components and small systems were discussed. It was already mentioned that it easily becomes too complicated to combine these models to create a reliability model of a large system. Therefore, for large systems, special reliability analysis approaches have been developed. This chapter discusses three of these approaches. The first, state enumeration, is an analytical analysis of possible system failure states. State enumeration will be discussed in detail in Sect. 5.1. The second approach, generation adequacy, focuses on the reliability of generation systems and is discussed in Sect. 5.2. The third, Monte Carlo simulation, is a (computer) simulation approach of the system behavior. This will be discussed in Sect. 5.3.