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 costâbenefit 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 1547â2018 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 costâbenefit for the daily steady-state operation of the network.
This paper is an experimental study of the electrical conduction of mineral-oil/solid interfaces in negative polarity. This study is performed in a point-plane configuration immersed in mineral oil submitted to impulse voltages. The interface is assembled with an inclined solid in contact with the point electrode tip. Charge recordings and conduction currents of different combinations of mineral-oil/solid interfaces are reported. Different polymers and oil-impregnated papers are used as the solid materials. It is found that for voltages lower than the inception voltage, the injection of charge belongs to a weak injection regime. The spatial limitation with solids of similar permittivity as the mineral oil decreases the charge injection. The charge injection at mineral-oil/solid interfaces follow two conduction current type characteristics. Experiments with mineral-oil/PTFE interface shows the existence of a transition between both conduction current types if the applied voltage is increased.
An experimental study of the inception of the first-mode negative streamer at liquid/solid interfaces is presented in this article. The study is performed with a point-plane configuration under square high voltage pulses. The electrode configuration is immersed in mineral oil and the liquid/solid interface is assembled in contact with the point electrode or in its vicinity. Four polymers and two impregnated papers have been tested as solids of the liquid/solid interface. Thus, it is possible to compare the influence of different parameter of the solid and the interface on the streamer inception. For example: Permittivity, solid surface roughness, chemical composition, etc. It has been observed that streamer inception voltages at interfaces with solids of higher permittivity to that of the mineral oil are statistically similar. Additionally, streamer inception voltages of streamer initiated free in the oil (no liquid/solid interface) are similar to that of the inception voltage of cases with solids with high permittivity. In contrast, the inception voltage of streamers initiated at permittivity matched interfaces are shown to be highest of the cases. The streamer inception voltage is also studied for different distances between the liquid/solid interface and the point electrode with a permittivity matched interface. The results show a dependency of the inception voltage and the distance between the point electrode and the interface. Finally, an analysis of the observation is performed to show that the Townsend-Meek criterion cannot predict the obtained results.
Energy management plays a pivotal role in enhancing the economic efficiency of power systems. However, it is noteworthy that a substantial number of microgrids (MGs) exhibit inherent unbalances that impose a range of critical issues, including voltage instability, elevated losses, power quality violations, safety concerns, and inefficiencies in energy management. Fast-acting power electronic converters present a relevant and efficacious solution for balancing such complex networks. This paper investigates the application of such converters within the realm of 3-phase unbalanced networks, wherein the proposed algorithm not only ameliorates network imbalances but also yields substantial reductions in operational costs, power losses, voltage deviations, and emissions. Demand response (DR) program has been applied to the model to enhance the system efficiency. The uncertainty about electric demand and renewable energy sources is considered in the simulation model for precise results. By implementing DR programs and penetrating distributed generators (DGs), the proposed model has been shown to reduce network losses and operation costs by 23% and 80%, respectively. Also, the total up-to-down voltage deviation of the voltage profile has been significantly reduced by 400%.
The secure operation of power systems should be maintained into secure states under different grid impact events. Such operational and non-operational grid states events occur infrequently, but when they do, they reveal the dynamics of the system and the need for security strategies to counteract events such as cascading failures. The coherency groups identification provides a protecting planning for proposing possible blackouts in the system. Additionally, coherency methods based on measurements are a requirement since the power systems continuous expansion. This paper applies the Self Organizing Maps (SOM) to assess the coherency groups identification based on the measurements obtained. Several observations have been evaluated assuming different time sliding window frames. The results are validated based on simulation of the Nordic test system.
This work presents a distributed in-line strategy to manage an isolated microgrid by optimizing active and reactive power dispatch. The proposed objective function leads to minimize the operation costs and addresses some technical requirements such as diminishing power losses and voltage deviation. Additionally, the strategy deals with temporal multi-scale goals, i.e., robustness to demand disturbances and variation of renewable resources (a short-term objective), and preservation of the health of battery-based storage systems (a long-term objective). The technique uses alternating directions method of multipliers (ADMM), accelerated consensus, and a novel battery degradation model (Quadratic AH-Throughput model). We test the proposed solution in a case study that includes renewable resources and lead-acid and lithium batteries. To obtain the results of the case study, we employ a co-simulation scheme that uses Matlab and DIgSILENT. Finally, the performance of the method is compared with a centralized optimization technique.
This paper presents the design and implementation of an electronic ballast for powering a fluorescent lamp. The purpose of this work is to improve the efficiency of the ballast by implementing a Series Resonant Inverter (SRI) in half-bridge configuration instead classic Series-Parallel Resonant (SPRI); in order to allow to provide the voltage steady state of the lamp. By other hand, this DC-AC converter will supply the voltage lamp ignition. Results on the proposed experimental prototype, using a fluorescent lamp of 32W, shows a better efficiency compared to traditional SPRI configurations.
This paper presents a detailed analysis of a single phase high power factor boost half-bridge rectifier (RPFU-HBB). The purpose of this work is to achieve a unity power factor with tight-regulated output voltage. Using the experimental prototype for 120 Vrms input voltage, output power 80W and output voltage of 450V; a power factor of 0.99 and total harmonic distortion of 2.5% was obtained. In order to eliminate the unbalance voltage of the two output capacitors a special control scheme was developed. Modeling, theoretical linearization around the operating point of the RPFU-HBB, design considerations of the current controller output voltage by means of average current method and experimental work tested through simulation model RPFU-HBB are presented.
Multi-terminal DC (MTDC) networks interconnect isolated systems, asynchronous areas, and renewable energy resources. However, ensuring stability and proper dynamic behavior of MTDC networks can be challenging. Power electronic converters offer increased control capabilities to achieve predictable and stable dynamics in the face of disturbances, faults, and sustained oscillations. The DC-side power system stabilizer (DC-PSS) is a supplementary controller that relies on optimal placement for maximized effectiveness. Observers can estimate the state of relevant system variables for the feedback controller without system-wide communication. This paper proposes an optimally-placed observer-based augmented DC-PSS for enhanced voltage stability in MTDC networks. The design procedure assumes no knowledge of the structure and parameters of the inner controllers of the terminal converters. We present a mathematical model and discuss the observer and control design procedures, and simulation results show the benefits and potential drawbacks of the proposed approach. Our observer-based DC-PSS relies on system-wide DC-bus voltage estimates from a single measurement, making it less vulnerable to communication delays and cyberattacks. Our work contributes to the field of supplementary controllers in MTDC networks and provides insights into future research directions toward stable and reliable DC power systems.
The increasing integration of variable renewable energy resources through power electronics has brought about substantial changes in the structure and dynamics of modern power systems. In response to these transformations, there has been a surge in the development of tools and algorithms leveraging real-time computational power to enhance system operation and stability. Data-driven methods have emerged as practical approaches for extracting reliable representations from non-linear system data, enabling the identification of dynamics and system parameters essential for analysing stability and ensuring reliable operation. This study provides a comprehensive review of recent contributions in the literature concerning the application of data-driven identification, analysis, and control methods in various aspects of power system operation. Specifically, the focus is on frequency support, power oscillation detection, and damping, which play crucial roles in maintaining grid stability. By discussing the challenges posed by parametric uncertainties, load and source variability, and reduced system inertia, this review sheds light on the opportunities for future research endeavours.
The evolving High Voltage Direct Current (HVDC) technology integrated into the modern power grids can help improve operation stability and damp undesired low-frequency oscillations in the system. This paper presents a Power Oscillation Damping (POD) strategy for power systems with a hybrid (LCC-VSC) HVDC link. The work consists of a centralized supervision algorithm that monitors the dynamics of several system variables and sets the appropriate gains to the POD controller from a lookup table (LUT) generated offline via simulation-based Particle Swarm optimization analysis. The mathematical modeling for the test system with an embedded HVDC link is presented, and the optimal tuning problem is defined using performance-oriented objective functions. Details for the detection and scheduling algorithm, LUT construction, and controller structure are provided. The nonlinear simulation model is implemented in MATLAB, and the results support the effectiveness of the proposed approach.
Long-term transmission network expansion planning aims to determine where, when and which types of equipment should be installed over a period of time, in order to meet the electric market needs with certain specifications of quality in services at the lowest possible cost. Until now, several methods have been proposed to solve the Static Transmission Network Expansion Planning (STNEP) problem, considering a multi-voltage approach using the DC load flow, however, these solutions may not be feasible when the AC model is used for the operational problem. In this paper a multi-stage model based on the mathematical formulation of the AC load flow is solved, considering a multi-voltage approach, power losses and reactive power compensation. The AC multi-stage transmission network expansion planing problem with multi-voltage approach (MTNEP-MV) was solved by the hybrid meta-heuristic, Differential Evolution (DE) and Continuous Population-Based Incremental Learning (PBILc) algorithm. To evaluate the proposed mathematical formulation Garver 6-bus system was used. The results show that raising the transmission system voltage and considering the MTNEP-MV problem, less transmission lines are required, and also power losses and reactive power compensation needs, are reduced.
Electricity markets provide valuable data for regulators, operators, and investors. The use of machine learning methods for electricity market data could provide new insights about the market, and this information could be used for decision-making. This paper proposes a tool based on multi-output regression method using support vector machines (SVR) for LMP forecasting. The input corresponds to the active power load of each bus, in this case obtained through Monte Carlo simulations, in order to forecast LMPs. The LMPs provide market signals for investors and regulators. The results showed the high performance of the proposed model, since the average prediction error for fitting and testing datasets of the proposed method on the dataset was less than 1%. This provides insights into the application of machine learning method for electricity markets given the context of uncertainty and volatility for either real-time and ahead markets.
The increased use of distributed energy resources, especially electrical energy storage systems (EESS), has led to greater flexibility and complexity in power grids, which has led to new challenges in the operation of these systems, with particular emphasis on frequency regulation. To this end, the transmission system operator in Great Britain has designed a control scheme known as Enhanced Frequency Response (EFR) that is especially attractive for its implementation in EESS. This paper proposes a Type-2 fuzzy control system that enables the provision of EFR service from a battery energy storage system in order to improve the state-of-charge (SoC) management while providing EFR service from operating scenarios during working and off-duty days. The performance of the proposed controller is compared with a conventional FLC and PID controllers with similar features. The results showed that in all scenarios, but especially under large frequency deviations, the proposed controller presents a better SoC management in comparison without neglecting the EFR service provision.
Coherency identification is one of the key steps to carrying out different control system strategies to avoid a partial or complete blackout of a power system. However, the oscillatory trends and the non-linear dynamic behaviour of the system measurements in the first seconds of the transient period often mislead the appropriate knowledge of the actual coherent groups, making wide-area coherency monitoring a challenging task. Inspired by swarm behavior in nature, we propose a modified Particle Swarm Optimization (PSO) approach based on centroids codification to identify coherency within a short observation window. A user-defined inter-group function is proposed and compared with conventional intra-group functions to examine the quality of the compacting and separating features of the final clusters. To demonstrate the effectiveness of our technique, we clustered the highly nonlinear dynamic responses of the generators on the 39-bus New England system. A comparison with other clustering methods was carried out to highlight the strength of the proposed algorithm.
The increasing installation of aggregated renewable generation based Full Rated Converters (FRC) in current power systems is modifying their dynamic characteristics. This paper analyses the influence of large scale inclusion of non-synchronous generation through back-to-back Voltage Source Converters’(VSC) connection on power systems, by presenting the dynamic changes on inter-area oscillations in different penetration level cases. The aggregated model of VSC units is assumed. The Small Signal Stability Analysis (SSSA) is used to show thedynamic behaviour and presents the performance of the power systems related to the domain frequency modes in a test grid system. From the analysis, it is shown that the mode shapes and participation factors are displaced according to the penetration levels. Eigenvalue sensitivity analysis according to the inertia isalso applied, showing the impact of the large penetration of nonsynchronousgeneration.
The use of high power electronics in the large scale integration of wind power in the transmission and distribution systems can affect the system inertia response and the ability to recover frequency stability after large disturbances. Different approaches have been presented to show the system dynamic behaviour, and to quantify the wind power impact on the system inertial and frequency response. This paper gives a short overview of studies performed regarding the system inertia issues under high penetrations of wind power. Also, it presents the results of a case study to show how the system inertia can be affected by high penetrations of wind power.
The current and massive deployment of non-synchronous generation is degrading the inertial response in power systems. The addition of an extra control loop, the so-called synthetic inertia, can contribute in the improvement of the frequency response, through an additional power injection. In this paper, the active damping method is used to enhance both, the closed-loop current control and the synthetic inertia control loop. A full aggregated model of a wind turbine generator (WTG) is integrated in a test system. The results obtained show an increase in the power injected into the grid, thereby improving the frequency response after a frequency disturbance. Moreover, the response of the closed current-control loop and voltage loop are presented, in order to show their interaction with the synthetic inertia control.
Cyber Physical Energy Systems (CPES) development requires the combination of distributed intelligence to fulfill the future complex tasks and reach the increase the energy demands. Electrical Industrial Systems (EIS) are in continuous evolving integrating new technologies allowing to a better performance and increase the efficiency. This paper applies the consensus protocol for Multi-Agent Systems (MAS) to control the speed of multiple induction motors. In this paper, the behaviour of the system under different disturbances and scenarios has been simulated, thus, confirming the suitability and simplicity of this method for coordinating the control actions.
The increasing integration of renewables into the grid based on power electronics converters interfaces is affecting the power systems dynamics, requiring effective monitoring and visualisation to provide appropriate assessment during extreme events. The coherent group identification in power systems is of importance for dynamic studies and transmission capability improvement. This study analyses the coherency based on the mode shapes, the application of the Koopman mode analysis (KMA) and a Prony analysis (PA) on-line variation for the identification of coherent groups in power systems. KMA and PA use the voltage angle measurements obtained from simulation. The clustering of the coherent groups are evaluated in two test systems. The coherency methods are also evaluated taking into account the impact of a large gradual scale inclusion of non-synchronous generation under different penetration level cases. From the comparison and visualisation of the different methods it is possible to observe the impact of the large inclusion of non-synchronous generation on the coherency.
The large scale penetration of non-synchronous generation based power electronics converters interfaces in current power systems is modifying their dynamic characteristics. The observation, monitoring and supervision of the electromechanical oscillation changes due to this integration is a requirement in order to protect the system from undesired events. This paper uses the Prony analysis to estimate the critical modes by using the tie-lines which interconnect the operative areas as measurement points and evaluating the impact of the large gradual scale inclusion of non-synchronous generation on power systems. The modes monitoring involved in the transient dynamic response are shown in the different penetration level cases. From the computed measurements, the frequency and damping variation in the different cases studied on the test system is obtained, which shows the impact of the large inclusion of non-synchronous generation.
The large scale penetration of non-synchronous generation has been causing several impacts on the power systems dynamics. The low-frequency oscillations affect the power exchanged along the transmission lines/corridors. This paper uses the Multi-Prony Analysis mode estimation technique to monitor and suggest the dominant oscillation modes which can be useful for wide-area control purposes. Moreover, the oscillation modes are also monitored under gradual cases of non-synchronous generation integration in the system. The methodology is applied to two different test transmission systems: i) the two area system and, ii) the Nordic 32 system. The results illustrate the similarity and differences in the scenarios proposed.
Due to the increasing use of renewables into the grid connected through power converters, the rotational inertia in power systems has been reducing. Consequently the frequency response requires the activation of the so-called synthetic inertia control. The synthetic inertia control aims to inject an extra power component when the system experiences a frequency disturbance event. In this paper, it is proposed that a distributed dynamic controllers for sharing the synthetic inertia control actions between the various active power converters in the grid for the improvement of the frequency response. It is assumed that a communication structure between the synthetic inertia controllers and the local power converters is involved in the system. The convergence of the control system is reached through a game population theory and the primary frequency control has been improved. The results are validated based on simulation of a two-area test system.
The integration of wind power generation (WPG) have many different impacts on the current power transmission and distribution systems. Most of them are related to their effect on the dynamic behaviour and frequency deviation during system frequency disturbances affecting the system inertia response. Different approaches have been presented to show the dynamic behaviour diminution, and several metrics have been proposed to quantify the impact of the inertia reduction. This scientific paper looks at the background system inertia problem, presenting some of the most significant contributions in observation of power system dynamic under high penetrations of WPG and presents two dynamic measurements. First one measures the damping ratio of the power lines quantifying it in an online fashion. The second one measures the frequency of an electrical power signal. The dynamic measurements are tested in a hypothetical active power signal with the inclusion of wind energy showing the affectivity of the dynamic measurements presented and the impact of wind farms in power systems. Finally, future work and conclusions are given.
The current power systems are facing an important transition due to the integration of non-synchronous generation through back-to-back Full Rated Converters' (FRC). Coherency behaviour under the presence of large inclusion of renewables requires special attention in order to understand the swing oscillations when the inertia is decreasing due to the decoupling. This paper presents the application of the so-called Koopman operator for the identification of coherent groups in power systems with the influence of non-synchronous generation. The method provides a clustering observation tool based on measurement signals allowing to identify the dynamic changes effected through the derived spectral analysis of the Koopman modes. The applied method of coherency identification is evaluated in the Nordic test system through gradually increasing integration and different fault locations.
Hybrid HVDC links incorporate both Line Commutated Converters (LCC) and Voltage Source Converters (VSC) systems, thereby gathering the benefits of both technologies. Supplementary Power Oscillation Damping (POD) controllers can be added to both LCCs and VSCs to help enhance the power system stability against disturbances, such as short circuits. However POD controller tuning can be a delicate process, due to the highly non-linear and complex nature of the involved power system, which might induce adverse interactions leading to a reduced damping. This paper proposes the application of the Simulated Annealing Algorithm (SAA) for tuning the POD controllers parameters, with the purpose of optimizing the performance of POD controllers in the power system. The damping performance is evaluated in case of multiple disturbances in a test power system. The results show the ability of the proposed technique to enhance the performance of the POD controllers under various operating conditions.
Abstract Electrical power systems are continuously upgrading into networks with a higher degree of automation capable of identifying and reacting to different events that may trigger undesirable situations. In power systems with decreasing inertia and damping levels, poorly damped oscillations with sustained or growing amplitudes following a disturbance may eventually lead to instability and provoke a major event such as a blackout. Additionally, with the increasing and considerable share of renewable power generation, unprecedented operational challenges shall be considered when proposing protection schemes against unstable electro-mechanical (e.g. ringdown) oscillations. In an emergency situation, islanding operations enable splitting a power network into separate smaller networks to prevent a total blackout. Due to such changes, identifying the underlying types of oscillatory coherency and the islanding protocols are necessary for a continuously updating process to be incorporated into the existing power system monitoring and control tasks. This paper examines the existing evaluation methods and the islanding protocols as well as proposes an updated operational guideline based on the latest data-analytic technologies.
Power systems operation and planning are facing several short-coming challenges due to the large inclusion of non-synchronous generation and the constant expansion of the electrical network. One of these challenges corresponds to the monitoring and forecasting of power systems Kinetic Energy (KE) to show on-line additional information for the Transmission System Operators (TSOs). In view of this challenge, KE monitoring requires innovative methods to analyse the continuous fluctuations in the system. Moreover, KE forecasting can foresee the status of the strength to overcome further events. In this work, we propose the use of information theory (specifically the concept of information length) as a way to provide useful insight in the power system KE variability and to demonstrate its usage as a starting point in decision making for power systems management. Additionally, a short-period forecasting using a Long Short Term Memory (LSTM) neural network model is proposed to estimate the value of information length in real time. The methodology is applied to a monthly collected data from the Nordic Power System. Results show that our method provides an effective description of the seasonal statistical variability.
Integrating a significant amount of non-synchronous generation into power systems creates new technical challenges for transmission systems. The research and understanding of the impact of the non-synchronous generation through back-to-back Full Rated Converters’ (FRCs) on power system’s coherency is a matter of importance. Coherency behavior under the presence of large inclusion of non-synchronous generation requires more research, in order to understand the forming groups, after a disturbance, when the inertia is decreasing due to the decoupling. This document presents the application of the so-called Koopman Operator for the identification of coherent groups in power systems with the influence of non-synchronous generation. The Koopman Analysis clusters the coherent groups based on the measurements obtained. The visualization of the coherent groups identified allows to observe their dynamic variations according to the penetration level or fault location. The applied method of coherency identification is evaluated in the Nordic test system through gradually increasing integration of non-synchronous generations and different fault scenarios.
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 degradation of the inertial response due to the large penetration of high power converters used for the interconnection of renewables energy sources. The addition of a supplementary synthetic inertia control loop can contribute to the improvement of the inertial response. This paper proposes the application of a novel Fuzzy Adaptive Differential Evolution (FADE) algorithm for the tuning of a fuzzy controller for the improvement of the synthetic inertia control in power systems. The method is validated with two test power systems: (i) an aggregated power system and its purpose is to understand the controller-system behavior, and (ii) a two-area test power system where one of the synchronous machine has been replaced by a full aggregated model of a Wind Turbine Generator (WTG), whereby different limits in the tuning process can be analyzed. Results demonstrate the evolution of the membership functions and the inertial response enhancement in the respective test cases. Moreover, the appropriate tuning of the controller shows that it is possible to substantially reduce the instantaneous frequency deviation.
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 electrical system, the country is considering upgrading its hydro-governors. This effort is part of maintaining the system frequency and reaction within their limits following any disturbance events. To partially compensate for increased frequency fluctuations due to an increased share of renewables on its system, the frequency response of hydro-governors should be improved. This paper proposes an innovative network control system, through a supplementary control, for the improvement of the hydro-governor's action. This supplementary control allows having more flexibility over the control action and improves the primary frequency control, and thereby the overall system frequency response. The proposed supplementary control, based on an evolutionary game theory strategy, uses remote measurements and a hierarchical dynamic adjustment of the control. Additionally, in order to guarantee an optimal response, a Simulated Annealing Algorithm (SAA) is combined with the supplementary control. This paper illustrates the analysis and design of the proposed methodology, and is tested on two power systems models: (i) an aggregated model that represents the frequency response of Sweden, Norway and Finland, and (ii) The Nordic 32 test system.
Future plans for integration of large non-synchronous generation and the expansion of the power system in the Nordic countries are a concern to transmission system operators due to the common interconnections and electricity exchanges among 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 authors propose a novel solution to tackle this problem including wide area measurements to monitor and share the RoCoF in remote areas 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 of the system the impact of delays in the communication channels is also included in the problem formulation.
Existing power systems are both weak and vulnerable when it comes to environmental threats, whether these occur due to natural disasters like earthquakes and hurricanes or extreme weather phenomena like torrential rains and hail. Under these circumstances, urban and rural communities are continuously evolving towards more self-balanced, self-sustainable electrical arrangements. This paper gives a brief overview of the existing energy community models, the technologies involved, and the services, along with some background in order to illustrate how these come about and what the conditions and requirements are to advance such initiatives, from both the private and the public sectors.
This article discusses the problem of minimizing power loss in unbalanced distribution systems through phase-balancing. This problem is represented by a mixed-integer nonlinearprogramming mathematical model, which is solved by applying a discretely encoded Vortex Search Algorithm (DVSA). The numerical results of simulations performed in IEEE 8-, 25-, and 37-node test systems demonstrate the applicability of the proposed methodology when compared with the classical Cuh & Beasley genetic algorithm. In addition, the computation times required by the algorithm to find the optimal solution are in the order of seconds, which makes the proposed DVSA a robust, reliable, and efficient tool. All computational implementations have been developed in the MATLAB® programming environment, and all the results have been evaluated in DigSILENT© software to verify the effectiveness and the proposed three-phase unbalanced power-flow method.
In this paper an Integrated Development Environment (IDE) is proposed for the FPGA Controller design for quadcopters (including specifications, design and implementa-tion). This IDE was developed using the High Level Specification of Embedded Systems Rich Client Platform (HiLeS-RCP). The HiLeS-RCP is a framework for specialized "per product line" IDE construction, which links requirements formalization step that represents the structural modelling using SysML, and the virtual prototyping. In this work the product line corresponds to flight controllers for quadcopters. This specialized IDE allows to manage the complexity of designs and to reduce development time for a modular implementation in Hardware Description Language (HDL).
Renewable energy sources contribute to overcome the problem of environmental pollution and secure the energy independency every country needs, while at the same time the autonomous microgrids can improve the electrification rates of poorer countries. In this article, the modeling process and operation of an autonomous hybrid power system are studied for a hypothetical case study of electrification of a remote village of 100 inhabitants in Kenya. The microgrid consists of photovoltaics, wind turbine, batteries, diesel genset, basic loads of different priorities, water pumping and purification load. The system is modeled in Simulink MATLAB and is simulated in terms of power management. The primary load is categorized in different priorities, while water pumping and purification is used as deferrable load. The "load following" dispatch strategy is adopted. The outputs of the model are the power produced by the various sources and the power consumed by all loads during the simulation time, as well as the produced and consumed energy, information on the battery operation and the dumped power or the power shortage. Both the microgrid's operation and the performance of the dispatch strategy are evaluated considering the level on which the citizens' energy needs are covered and the efficient management of the produced energy. Managing the extra power or tackling the deficit of power in the system are the key issues to be addressed. After all, the model represents reliably the behavior of the microgrid and several improving actions are suggested, based on the results analysis.
Data management is strategically necessary to make decisions, planning and monitoring within the energy sector. Recently, the Engineering Faculty of the Universidad Tecnológica Centroamericana (UNITEC), Honduras launched a tool called the Energy Observatory of Honduras. This tool fills the gap that exists in the access to energy data within the country. This tool provides data from the demand and generation of electricity in a free and easy way. Also, the information relating to the consumption of fossil fuels and firewood as well as the access to real-time data and energy indexes are shown.
Phase balancing is a classical optimization problem in power distribution grids that involve phase swapping of the loads and generators to reduce power loss. The problem is a non-linear integer and, hence, it is usually solved using heuristic algorithms. This paper proposes a mathematical reformulation that transforms the phase-balancing problem in low-voltage distribution networks into a mixed-integer convex quadratic optimization model. To consider both conventional secondary feeders and microgrids, renewable energies and their subsequent stochastic nature are included in the model. The power flow equations are linearized, and the combinatorial part is represented using a Birkhoff polytope B3 that allows the selection of phase swapping in each node. The numerical experiments on the CIGRE low-voltage test system demonstrate the use of the proposed formulation.
Photovoltaic (PV) systems are a clean energy source that allows for power generation integration into electrical networks without destructive environmental effects. PV systems are usually integrated into electrical networks only to provide active power during the day, without taking full advantage of power electronics devices, which can compensate for the reactive power at any moment during their operation. These systems can also generate dynamic reactive power by means of voltage source converters, which are called PV-STATCOM devices. This paper presents a convex formulation for the optimal integration (placement and sizing) of PV-STATCOM devices in electrical distribution systems. The proposed model considers reducing the costs of the annual energy losses and installing PV-STATCOM devices. A convex formulation was obtained to transform the hyperbolic relation between the products of the voltage into a second-order constraint via relaxation. Two simulation cases in the two IEEE test systems (33- and 69-node) with radial and meshed topologies were implemented to demonstrate the effectiveness of the proposed mixed-integer convex model. The results show that PV-STATCOM devices reduce the annual cost of energy losses of electrical networks in a more significant proportion than PV systems alone.
Swarm robotics requires the development of new strategies and algorithm integration, which allow for the improvement of the design and the applications for harvesting or collecting resources. This paper describes the programming and design of Finite State Machines (FSM) bio-inspired algorithms for seeker and resource gathering Pherobots systems, like Anthill Known Location (AKL) aggressiveness and sense of panic. FSM designing allows for the use of control architectures for behaviour-based agents and for measuring the change in system performance. Simulations demonstrate the capability of the algorithms under different environments and scenarios.
Power electronic converter (PEC) is a key element for the successful integration of novel technologies, PEC working as inverter at novel generation technologies are the decisive components to zero-net carbon emissions in the electricity systems. The colossal penetration of IBG tends to produce several issues in the power networks. There is a tendency to agree that the voltage source converters (VSCs) empowered with the so-called grid forming (GFR) control may provide a long-term solution for the inverter-based generation-dominated power systems. This scientific paper presents an investigation (based on numerical simulations) of the effect of the virtual impedance control mode of one grid forming control technique in the power swing of power systems. Numerical time-domain simulations on test systems are used to assess the effect of the virtual impedance (VI) control mode of the synchronverter (SynC) during a power swing. In both cases, the simulation-based investigation has shown evidence of using high and low virtual impedance in both cases, considering constant impedance and proportional over-current limitation. However, this paper concludes that further assessments are required.
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.
Inverter-based generation (IBG) is critical in achieving a dependable and resilient electrical system while meeting the net-zero emission goal. The enormous integration of IBG tends to produce various issues, including reduced rotational inertia and reduced short circuit levels. Several scientific publications agree that the voltage source converters (VSCs) empowered by the so-called grid forming (GFM) control may provide a lasting answer for reaching the future net-zero IBG-dominated power systems. This paper presents a comparative analysis of the dynamic performance between IBR using synchronverter and a traditional synchronous generator (SG), where the specific concern is the transient stability conditions. DIgSILENT PowerFactory has been used for time-domain simulations using a test system, and numerical simulations considering an N-l event prove the significant benefit of GFN converter controls in providing active power during a voltage sag induced by a short circuit condition, allowing the system to endure longer short circuit durations.
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.
As fractional-order models increasingly appear as an option to describe complex systems, they generate a demand for parameter estimation methods in the time and frequency domain. The extended Kalman filter (EKF) is a promising technique in the time domain, but it is sensitive to the initial conditions of the state and error covariance matrices. In the case of integer-order systems, evolutionary algorithms (EAs) can tackle EKF's sensitiveness issues. The algorithm usually uses EAs to optimise the initial conditions for the EK, leading to a better estimate of the system parameters and states. Here, we extend this methodology to fractional-order models to estimate the model's fractional order and parameters. Finally, we demonstrate the effectiveness of this methodology on a simple mechanical model.