Hasil untuk "Distribution or transmission of electric power"

Faisal Irsan Pasaribu, Ira Devi Sara, Tarmizi Tarmizi et al.

The growing use of nonlinear household appliances, such as LED lighting and inverter-based devices, has led to significant power quality problems. This is mainly due to harmonic currents altering the shape of voltage waveforms. Such distortions can lead to increased system losses, transformer overheating, and reduced equipment lifespan. Therefore, this paper proposes an optimized model of a new damped double-tuned filter (DDTF) designed to accommodate dynamic variations in household loads. The particle swarm optimization (PSO) algorithm is used to enhance the design by determining the optimal values for the filter’s constituent parts. Additionally, an artificial neural network (ANN) model is developed to validate and predict filter performance based on experimental data. The DDTF is specifically designed to mitigate dominant harmonics at the 3rd, 5th, and 7th orders. Both simulation and experimental validation were conducted using MATLAB Simulink under realistic household load scenarios. At peak load (2100 W), the unfiltered system exhibited a total harmonic distortion of voltage (THDv) of 155.1%, a total harmonic distortion of current (THDi) of 204.41%, and a power factor of 0.55. After using the new six-stage DDTF at various load levels (from 350 W to 2100 W), the THDv dropped to 7.98%, the THDi fell to 3.57%, and the power factor increased to 0.8089. The ANN-based performance evaluation achieved 94% prediction accuracy, with an error margin of 2% to 6%. These results demonstrate that the designed DDTF is a viable, efficient, and cost-effective approach to mitigating harmonics and enhancing power quality in residential electrical systems.

Nandini K. K., Jayalakshmi N. S., Vinay Kumar Jadoun

Abstract Uncertainty analysis deals with the fluctuations and unpredictability of the electrical power generated from renewable resources (RRs), such as solar PV and wind energy systems. This paper gives an insight into various techniques used for the uncertainty analysis and a probabilistic Monte Carlo Simulation is applied for modelling the uncertainties concerned with RRs and electric vehicle (EV) load in the MATLAB platform. The uncertainty associated with the price sensitivity of EV charging and the state of charge of EVs is taken as a prime factor for analysis in the present work. Despite the fluctuations and unpredictability of electricity generation and consumption, the considered system ensures that the total amount of electricity supplied by solar PV, wind and grid matches the total amount of electricity demanded by EV load. Rao‐1, Rao‐2 and Rao‐3 algorithms are applied in this work to optimize the operation cost of charging stations under uncertain conditions and without any uncertainties. The results obtained without uncertainties by Rao algorithms are compared with the existing particle swarm optimisation method. In the presence of uncertainties, Rao‐1 and Rao‐2 algorithms are compared with Rao‐3 and it is found that the Rao‐3 algorithm performed better.

Wei Wang, Shunfu Lin, Lulu Wang et al.

Abstract The increased penetration of renewable energy sources and the intensification of peak‐valley differences present challenges to peak regulation in the power system. Fulfilling the peak regulation needs of the power system solely through generation‐side resources proves to be challenging. Large‐scale fixed frequency air‐conditioning (FFAC) and inverter air‐conditioning (IAC) are high‐quality flexible load resources. This paper proposes a hierarchical coordinated control strategy of air‐conditioning (AC) loads for peak regulation service. In the first layer of the control strategy, the load aggregator collaborates with multiple AC groups to ensure the completion of peak regulation tasks with specific power‐constrained requirements. In the second layer of the control strategy, the control centre of each group optimizes the temperature adjustment values for each AC load, aiming to reduce incentive costs. Finally, the proposed method is validated through simulations, demonstrating its capability to achieve coordinated control of FFAC and IAC loads under various power‐constrained requirements. Furthermore, the simulation demonstrates the effectiveness of the control strategy in reducing user discomfort and the AC's incentive costs.

Chengzhi Xie, Payman Dehghanian, Abouzar Estebsari

Abstract The ability to withstand and recover from disruptions is essential for seaport energy systems, and in light of the growing push for decarbonization, incorporating clean energy sources has become increasingly imperative to ensure resilience. This paper proposes a resilience enhancement planning strategy for a seaport multi‐energy system that integrates various energy modalities and sources, including heating, cooling, hydrogen, solar, and wind power. The planning strategy aims to ensure the reliable operation of the system during contingency events, such as power outages, equipment failures, or extreme weather incidents. The proposed optimization model is designed as a mixed‐integer nonlinear programming formulation, in which McCormick inequalities and other linearization techniques are utilized to tackle the model nonlinearities. The model allocates fuel cell electric trucks (FCETs), renewable energy sources, hydrogen refueling stations, and remote control switches such that the system resilience is enhanced while incorporating natural‐gas‐powered combined cooling, heating, and power system to minimize the operation and unserved demand costs. The model considers various factors such as the availability of renewable energy sources, the demand for heating, cooling, electricity, and hydrogen, the operation of remote control switches to help system reconfiguration, the travel behaviour of FCETs, and the power output of FCETs via vehicle‐to‐grid interface. The numerical results demonstrate that the proposed strategy can significantly improve the resilience of the seaport multi‐energy system and reduce the risk of service disruptions during contingency scenarios.

Qin Yan, Weicheng Gao, Rui Ma

Mariana Brinati Altomar, João Alberto Passos Filho

Maryam Mohiti, Mohammadreza Mazidi, Mostafa Kermani et al.

Abstract This paper proposes a novel energy and reserve scheduling model for power systems with high penetration of wind turbines (WTs). The objective of the proposed model is to minimize the total operation cost of the system while static and dynamic security is guaranteed by preserving the frequency nadir, RoCoF, and quasi‐steady‐state frequency in the predefined range. Likewise, a supervisory, control, and data acquisition (SCADA) system is developed which allows Vanadium Redox Flow Batteries (VRFBs) to continuously communicate and participate in the primary frequency response. To cope with the uncertainties, adaptive information gap decision theory is used that ensures a target operating cost for the risk‐averse operator of the power system. The proposed scheduling model is applied on a modified IEEE 39 bus test system to verify the impacts of the fast reserve provided by the VRFBs in the dynamic frequency security enhancement of the power system with high penetration of WTs.

Andrés Felipe Cerón Piamba, Andrés Arturo Romero Quete, Guillermo Aponte Mayor

Abstract This article presents an optimization methodology to schedule the replacement of power transformers (PT) into a fleet. The objective is the minimization of the summation of the risk indices of the PT. Each PT risk index is calculated from the estimation of the life used and the strategic importance of the unit. The PT life used is estimated as a relationship of the solid insulation polymerization degree, where aging processes due to oxidation, hydrolysis, and pyrolysis are considered from the calendar date when the unit starts its operation until different future scenarios. For the calculation of the PT strategic importance, financial, security, environmental, and network performance aspects are considered. Then, using the optimization model, together with the CAPEX and the available budget over a planning time, a strategy for optimally replacing the critical units is determined. The model was applied for a group of 102 units, demonstrating its applicability and effectiveness. The developed methodology serves to support the manager of these assets in making decisions in the long term.

Hanqing Huang, Zengping Wang

Abstract The high‐voltage direct current (HVDC) transmission based on modular multilevel converter shows the weak feed characteristic of limited fault current amplitude when connected to the traditional AC power grid, which leads to the risk of sensitivity reduction or even failure of the traditional pilot protection. Here, a modular multi‐level converter (MMC)‐HVDC AC side transmission line protection scheme based on positive sequence fault component current ratio is proposed. The positive sequence fault component current of the MMC‐HVDC side is calculated by using the positive sequence fault component current of the power grid side, and the fault is identified through the significant difference between the ratio of the positive sequence fault component current of the MMC‐HVDC side and the actual positive sequence fault component current of the MMC‐HVDC side in the case of internal and external faults. This method has the advantages of simple principle, low requirement for synchronous data, not affected by capacitive current and strong resistance to high resistance. The simulation results show that the algorithm can correctly partition internal and external faults, and is not affected by fault location, fault type and operation mode of converter station, and has high sensitivity and reliability.

Jinlong Cui, Beibei Gao, Baojun Guo

Abstract As the next generation of green power system, smart grids have gradually enhanced the operation efficiency of power system. Meanwhile, the application of communication and intelligent technologies make the power grid more vulnerable to the emerging cyber‐physical attacks, such as the false data injection attack (FDIA). Particularly, the deception property of the FDIA on the output measurement estimation can fool the current security mechanism without triggering an alarm. Motivated by this problem, this paper aims at developing a novel detection and recovery mechanism against FDIA in smart grid. Based on the established state space grid model derived from the three‐phase sinusoidal voltage equations, an improved principal component analysis (PCA)‐based detection method is proposed. By introducing the mathematical transformation principle method, the detection performance such as detection rate and false positive rate can be improved. To keep the stable running of power system, a genetic optimization algorithm‐based linear quadratic regulator (LQR) defense method is developed. In addition, to improve the response performance to external attacks, an artificial intelligence method named genetic optimization algorithm is introduced to optimize the robust performance of the proposed defense method. Finally, the simulation results on the IEEE 6‐bus and 118‐bus grid system demonstrate the superiority of the proposed genetic algorithm optimization‐based LQR defense method.

Xusong Yang, Lei Liu, Xinyu Gu et al.

Abstract With the rapid increase of wind power penetration, the frequency indicators of power system, encompassing frequency deviation and rate of change of frequency (RoCoF), are prone to exceed the pertinent relay thresholds, thus leading to serious power outages. Wind farms can participate in primary frequency regulation (PFR) to alleviate the above problem. However, wind farms reserve capacity (WFRC) presented by overspeed control and pitch angle control is the important factor for frequency safety especially when large disturbance occurs, and it varies obviously in different conditions. Thus, WFRC should be utilized optimally to avoid insufficient or excessive response of wind farms in PFR. To overcome the challenge, this paper proposes frequency‐trajectory‐oriented control (FTOC) for wind farms based on a two‐fold optimization framework, seeking to obtain the best frequency control performances in PFR through realizing the optimal compromise between frequency results and the consumption of WFRC. First, when the frequency indicators deviate significantly from the normal values, the optimal frequency trajectory is planned periodically according to the local standards and operation conditions, thereby minimizing the total consumption of WFRC on the premise of frequency safety. Second, based on model predictive control and a real‐time power system parameters estimator, the total reference power of wind farms, which helps the frequency track the latest planned trajectory, is optimally distributed among wind generators according to their reserve capacity. In this case, through the optimal frequency trajectory planning and tracking, the new method in this paper not only effectively prevents the frequency results from exceeding the local standards under diverse conditions, but also finds the optimal balance among frequency indicators safety, frequency trajectory smoothness, and the reserve capacity consumption of wind power generators. Finally, the simulation results prove the effectiveness and advancement of FTOC.

Hossein Shayeghi, Alireza Rahnama, Nicu Bizon

Abstract Modern electrical power system design will increase renewable energy sources (RES) dominance. Rotating masses, the main source of inertia in power systems, have been greatly decreased in renewable energy producing systems. Thus, load–frequency equilibrium is an important indicator of these systems' performance and safety. This work introduces a fractional‐order (FO) operator‐based cascade control structure for islanded microgrid (μG) load‐frequency control (LFC). The structure utilizes a tilt–FO derivative with filter (TFODn) in the first level to reduce noise. The second level implements the proportional integral (PI) controller's FO form (FOPI), making it a tilt–FO derivative with a filter cascaded to the FOPI controller (TOFDn‐FOPI). The optimal controller parameters for quick dynamic responses with low frequency fluctuation are determined using a unique cost function and prairie dog optimization (PDO) algorithm. The LFC control loops have frequency deviation‐based responsive loads (RL). Control signal delays, RES output changes, parameter uncertainties, and cyber vandalism are examined. Laboratory‐scale tests also assessed the controller's practicality. The proposed controller outperforms standard and FO type proportional integral derivative (PID) and PD‐PI controllers. The TFODn‐FOPI controller is suitable for complicated closed‐loop systems like islanded μGs due to its faster error clearing, reduced RL capacity, and superior time and frequency domain indicators.

Rohit Vijay, Parul Mathuria

Mahdi Banejad, Mohammad Kazeminejad, Nasser Hosseinzadeh

Fan Xiao, Yongjun Xia, Kanjun Zhang et al.

Abstract In a high proportion of new energy grids or a 100% new energy source of power grid, the dynamic performance of PMSG under fault conditions is very important. However, the current small signal model lacks detailed and deep analysis of a permanent‐magnet synchronous generator (PMSG)‐based wind power generation under LVRT control. Here, a small signal model of a PMSG under pre‐fault, fault and after fault failure recovery stages are established. This paper employs linear analyses to characterize the dynamic performance of a PMSG‐based wind power generation system under LVRT control and practical generator characteristics. In particular, the conflict between frequency regulation and LVRT is discussed based on the constructed model. On this basis, the impact of dc‐link bandwidth on the system performance during failure recovery stage is discussed, and the active damping method is analysed to improve the performance of PMSG during failure and failure recovery stages. Finally, time‐domain simulations are utilized to verify the analyses and models discussed. The research results in this paper are helpful to promote and improve the performance of PMSG during LVRT conditions.

Kalle Rauma, Toni Simolin, Pertti Järventausta et al.

Abstract The adaptive charging algorithms of today divide the available charging capacity of a charging site between the electric vehicles without knowing how much current each vehicle draws in reality. Thus, they are not able to detect deviations between the current set point at the charging station and the real charging current. This leads to a situation where the charging capacity of the charging site is not used optimally. This paper presents an algorithm including a novel feature, Expected Characteristic Expectation and tested under realistic circumstances. It is demonstrated that the proposed algorithm enhances the adaptability of the charging site, increasing the efficiency of the used network capacity up to about 2 kWh per charging point per day in comparison with the previous benchmark algorithm. The algorithm is able to increase the average monetary benefits of the charging operators by up to around 5.8%, that is 0.6 € per charging point per day. No input, such as departure time, is required from the user. The proposed algorithm has been tested with real electric vehicles and charging stations and is compatible with the IEC 61851 charging standard. The charging algorithm is applicable in practice as it is described in this paper.

Weiwang Wang, Xilin Yan, Shengtao Li et al.

Abstract This study reviews the failure of high‐voltage submarine cables used in offshore power transmission and provides highlights of their failure characteristic, mechanisms, key issues and prospects. High‐voltage submarine cables are designed and applied according to the high‐voltage alternating current and high‐voltage direct current requirements. Inevitably, the fault occurs in HV submarine cables that is different from that of an underground cable. External aggression remains the primary cause of faults, such as fishing and anchors. Most faults continue to occur at a shallow depth (300 m). The optical fiber inside the submarine cables plays a substantial role in the temperature and stress‐strain monitoring and diagnosis. However, it is regarded as a weak point for electrical fault. Insulation breakdown is the leading reason for the short fault. The failure mechanism is complicated when associated with marine conditions. Some defects of insulation and extensive voids, water treeing, mechanical stress, partial discharges, overheating, and electrochemical erosion contribute to the insulation breakdown. Several key issues, including anchoring damage, treeing, defects, and thermal‐electric ageing, are proposed. Prospects and new methods related to the cable failure, especially for insulation ageing by treeing and electrothermal effects, are also discussed.

Athira Raju, Elizabeth P Cheriyan, Rijil Ramchand

Abstract A STATCOM that employs a nearly constant switching frequency hysteresis current controlled VSI is presented in this paper. Hysteresis controller enhances the dynamic performance of STATCOM. The switching frequency variations associated with the conventional hysteresis current controller is reduced by using a variable hysteresis boundary. Variable hysteresis boundary is predetermined by the current error, based on the sampled magnitudes of the reference voltage vector. This makes the switching frequency nearly constant and switching vector selection optimal. As a result, a voltage FFT profile similar to that of a space vector modulated STATCOM is obtained. Choosing a space vector based reference voltage vector keeps the current error within the pre‐calculated boundaries and improves the current tracking capability of STATCOM. The systematic method of selecting a switching sequence avoids random switching. Effectiveness of the proposed method for the control of grid‐connected STATCOM is experimentally verified and compared with a voltage‐controlled space vector modulated voltage source inverter based STATCOM. The hardware implementation of the controller for grid‐connected STATCOM is carried out in OPAL‐RT real‐time simulator platform and experimentally validated for a three‐phase balanced load of 5 kVA.

Xiaotian Yuan, Zhengchun Du, Yujun Li et al.

Abstract This paper introduces a novel cascading frequency regulation scheme (CFRS) for VSC‐HVDC to provide strong support for the connected weak AC grid without phase‐locked loop and remote‐communication considering the cost‐effective property. The proposed CFRS utilises a DC voltage synchronisation control to enable the self‐synchronisation of VSC‐HVDC without phase‐locked loop, while the corresponding inertia response can be exerted via utilising the stored HVDC capacitor energy. Meanwhile, the DC voltage acts as the reflection of system frequency, enabling the coordination between two‐end VSC stations without communication. More importantly, to fully utilise the VSC‐HVDC potentials, the CFRS that sequentially activates HVDC capacitor and primary frequency control is implemented so that the energy loss and the detrimental control impacts on the sending‐end systems can be minimised while making sure the requirement of system frequency support. Analytical derivations have been done to evaluate the contribution of the proposed CFRS to system frequency regulation. Furthermore, the effectiveness of the proposed scheme has been well validated in PSCAD/EMTDC under several power system contingencies by fully comparing with existing control schemes. The proposed CFRS stands out by the reduced complexity of the control structure, the robustness for connecting the very weak AC grid and the fast frequency regulation ability with consideration of cost‐effective property.

Houman Heidarabadi, Farzaneh Pourahmadi, Seyed Hamid Hossieni

In the near future power systems, efficient management of uncertainties with considering the system constraints without any simplification will be a challenge for system operators. Considering AC constraints leads to providing more accurate schedule of generating units, which can have a significant impact on the reduction of operating costs. Although numerous studies have been done to convexify AC optimal power flow constraints, most of the models are non‐linear, which can be intractable for large‐scale systems. In this study, a novel linear robust AC model is introduced using a combination of the quadratic convex relaxation (QCR) and the Frank–Wolfe algorithm for linearising the AC constraints. The uncertainties are modelled by applying the robust optimisation with recourse to obtain an optimal schedule for the conventional units in multi‐period real‐time markets. The Benders‐dual algorithm is implemented to solve the optimisation problem. The proposed model was applied to the IEEE 3‐bus, 118‐bus, and 300‐bus systems. The results indicate that the proposed algorithm obtains more precise approximation than the QCR method. In addition, the costs and losses of the proposed model are less than those of the conventional robust DC and stochastic models. Furthermore, because the proposed model is linear, its runtime is rational.