Hasil untuk "Distribution or transmission of electric power"

Philippe Jacquod, Laurent Pagnier, Daniel J. Gauthier

Accurate state estimation is a crucial requirement for the reliable operation and control of electric power systems. Here, we construct a data-driven, numerical method to infer missing power load values in large-scale power grids. Given partial observations of power demands, the method estimates the operational state using a linear regression algorithm, exploiting statistical correlations within synthetic training datasets. We evaluate the performance of the method on three synthetic transmission grid test systems. Numerical experiments demonstrate the high accuracy achieved by the method in reconstructing missing demand values under various operating conditions. We further apply the method to real data for the transmission power grid of Switzerland. Despite the restricted number of observations in this dataset, the method infers missing power loads rather accurately. Furthermore, Newton-Raphson power flow solutions show that deviations between true and inferred values for power loads result in smaller deviations between true and inferred values for flows on power lines. This ensures that the estimated operational state correctly captures potential line contingencies. Overall, our results indicate that simple data-based regression techniques can provide an efficient and reliable alternative for state estimation in modern power grids.

Viet Quoc Pham, Madhusanka Liyanage, N. Deepa et al.

Electricity is one of the mandatory commodities for mankind today. To address challenges and issues in the transmission of electricity through the traditional grid, the concepts of smart grids and demand response have been developed. In such systems, a large amount of data is generated daily from various sources such as power generation (e.g., wind turbines), transmission and distribution (microgrids and fault detectors), load management (smart meters and smart electric appliances). Thanks to recent advancements in big data and computing technologies, Deep Learning (DL) can be leveraged to learn the patterns from the generated data and predict the demand for electricity and peak hours. Motivated by the advantages of deep learning in smart grids, this paper sets to provide a comprehensive survey on the application of DL for intelligent smart grids and demand response. Firstly, we present the fundamental of DL, smart grids, demand response, and the motivation behind the use of DL. Secondly, we review the state-of-the-art applications of DL in smart grids and demand response, including electric load forecasting, state estimation, energy theft detection, energy sharing and trading. Furthermore, we illustrate the practicality of DL via various use cases and projects. Finally, we highlight the challenges presented in existing research works and highlight important issues and potential directions in the use of DL for smart grids and demand response.

Taher M. Ghazal, Sajida Noreen, Raed A. Said et al.

The usage of IoT-based smart meter in electric power consumption shows a significant role in helping the users to manage and control their electric power consumption. It produces smooth communication to build equitable electric power distribution for users and improved management of the entire electric system for providers. Machine learning predicting algorithms have been worked to apply the electric efficiency and response of progressive energy creation, transmission, and consumption. In the proposed model, an IoT-based smart meter uses a support vector machine and deep extreme machine learning techniques for professional energy management. A deep extreme machine learning approach applied to feature-based data provided a better result. Lastly, decision-based fusion applied to both datasets to predict power consumption through smart meters and get better results than previous techniques. The established model smart meter with automatic load control increases the effectiveness of energy management. The proposed EDF-FMLA model achieved 90.70 accuracy for predicting energy consumption with a smart meter which is better than the existing approaches.

Quan Nguyen, Hongyan Li, Pavel Etingov et al.

System operators rely on system flexibility to handle unexpected reliability and resilience events, ranging from excessive resource forecast errors to extreme events like heatwaves, earthquakes, and cyberattacks. This paper provides a production cost modeling (PCM) methodology to quantify contributions to system flexibility and economic benefits by controllable HVdc and multi-terminal HVdc (MTdc) transmission systems. First, the PCM model of a general MTdc grid is developed to be seamlessly added to existing scalable PCM model of an ac power system. Second, a method for modeling extreme operating conditions, including heatwave and wildfire, in PCM is presented. Finally, the planning 2030 Western Electricity Coordinating Council (WECC) system is used as an example to demonstrate the benefits of existing and future dc lines in point-to-point, radial, and meshed configurations. Under extreme system conditions including heatwave and wildfire, it is identified from the PCM simulation results that HVdc and MTdc transmission flexibility can provide substantial economic, reliability, and environmental benefits. These benefits include reductions up to 6.4% total generation cost, 8.6% unserved load, 50.3% renewable curtailment, 75% locational marginal price, and 4.0% CO2 emission amount.

Junjie Zheng, Jing Qu, Zexiang Cai et al.

Abstract The introduction of cloud‐native technology has significantly changed the architecture of applications and the mechanism for the collaborative operation of components in power distribution edge computing terminals (PDECT). To develop an effective quantitative analysis tool for PDECT performance, the composition and characteristics of cloud‐native PDECT are studied, and the modelling and simulation of cloud‐native PDECT are proposed. Subsequently, modelling is implemented through the simulation software CloudSim, achieving the simulation of microservices, containers, declarative configuration, and container orchestration with the consideration of power distribution scenarios. Then, by the proposed simulation scenario module, various elements of the power distribution scenarios can be self‐defined. Finally, by demonstrating the principles and implementation mechanisms of the proposed modelling method and simulation tool, and comparing simulation results for different service time ranges, access devices, resource configurations of PDECT, request occurrence rates, and resource scheduling strategies, the validity and effectiveness of the proposed modelling method and simulation tool are verified.

Lixuan Zhu, Yiping Yu, Ping Ju

Abstract In modern power systems, the uncertainty and volatility of generation and loads greatly increase the balance discrepancy between the power supply and demand, creating major potential security hazards. To limit out‐of‐bound frequencies, an effective frequency control method for power systems with interval uncertain disturbances is proposed. Based on the state space model of the system frequency response with delays, linear matrix inequalities are constructed based on the input‒output finite‐time stability of the system frequency. By searching for the output feedback gain and altering the time delay with the Padé approximation, the feasibility of the linear matrix inequalities is improved, and a frequency controller is designed. The simulation results show that the proposed method can effectively control frequency deviations. When the closed‐loop system is disturbed by uncertain power fluctuations, its frequency will always remain within the allowable range to ensure the secure operation of the power system.

Amir Hossein Rezaei, Milad Beikbabaei, Moein Abedini et al.

Abstract Protection of synchronous generators (SGs) against internal faults, such as stator earth fault (SEF) and turn‐to‐turn fault (TTF), is crucial for ensuring the stability and security of the power system. This paper presents a phase domain model for simulating SEF and TTF in SGs, requiring only nameplate data and avoiding the need for complex geometric data or lengthy simulations typical of FEM models. The stator winding is divided into three sections, allowing for the calculation of magnetic field distribution in both healthy and faulty conditions. The model is capable of simulating short‐circuit turns at various locations within the stator winding with high accuracy and speed. The dynamic response of the generator is also incorporated into the model. The model's accuracy is validated through comparison with results from multiphysics simulation software. Furthermore, this study addresses the limitations of conventional protection methods in detecting TTF and proposes a novel, simple, fast, and accurate protection logic that can be implemented in digital protection relays and is effective across a wide range of TTF scenarios.

Yonggang Li, Binyuan Wu, Jianwen Li et al.

Abstract A multi‐inverter‐fed power system is susceptible to small‐signal instability owing to weak grid influence. This study proposes a black‐box method for small‐signal stability analysis of a multi‐inverter‐fed power system based on Bode diagrams. Not only did it consider the technical confidentiality on the engineering site, but it also took into account the presence of right‐half‐plane (RHP) pole in the aggregated impedance, achieving Nyquist circle acquisition through Bode diagrams. The stability analysis process is thus more accurate, intuitive, and convenient. First, black‐box impedance fitting for a single grid‐connected inverter and impedance aggregation for a multi‐inverter‐fed power system are discussed. Second, the principle of the proposed method is elaborated. Using the Bode diagram, the number of RHP poles of the aggregated impedance and actual number of circles for Nyquist curves are identified. Third, a multi‐inverter‐fed power system is constructed, and the effectiveness of the proposed method is verified using case analysis and hardware‐in‐the‐loop real‐time experiments based on RT‐LAB. Finally, the advantages of the proposed method are revealed by comparing it to the IF method.

Mohammad Golgol, Anamitra Pal, Vijay Vittal et al.

The installation of high-capacity fast chargers for electric vehicles (EVs) is posing a significant risk to the distribution grid as the increased demand from widespread residential EV charging could exceed the technical limits of the distribution system. Addressing this issue is critical, given that current infrastructure upgrades to enhance EV hosting capacity are both costly and time-consuming. Moreover, the inherent uncertainties associated with EV charging parameters make it challenging for power utilities to accurately assess the impact of EVs added to specific locations. To address these knowledge gaps, this study (a) introduces an algorithm to coordinate residential EV charging, and (b) proposes a comprehensive framework that evaluates all transformers within a feeder. The proposed method is applied to a real-world feeder, which includes 120 transformers of varying capacities. The results demonstrate that this approach effectively manages a substantial number of EVs without overloading any of the transformers, while also pinpointing locations that must be prioritized for future upgrades. This framework can serve as a valuable reference for utilities when conducting distribution system evaluations for supporting the growing EV penetration.

Richard Soref, Francesco De Leonardis, Oussama Moutanabbir et al.

The commercially available 4000-Watt continuous-wave Erbium-doped-fiber laser, emitting at the 1567-nanometer wavelength where the atmosphere has high transmission, provides an opportunity for harvesting electric power at remote off the grid locations using a multi-module photovoltaic receiver panel. This paper proposes a 32-element monocrystalline thick-layer Germanium photovoltaic panel for efficient harvesting of a collimated 1.13-meter-diameter beam.The 0.78-meter squared PV panel is constructed from commercial Ge wafers. For incident continuous-wave laser-beam power in the 4000 to 10000 Watt range, our thermal and electrical and infrared simulations predict 660 to 1510 Watts of electrical output at panel temperatures of 350 to 423 Kelvin.

Zachary J. Lythgoe, Thomas F. Long, Michael J. Buchholz et al.

Phasor measurement units (PMUs) provide a high-resolution view of the power system at the locations where they are placed. As such, it is desirable to place them in bulk in low voltage distribution circuits. However, the power consumption of a PMU/micro-PMU is in the order of Watts (W) that results in them requiring an external power supply, which in turn increases the overall cost. This work details the hardware design of a PMU capable of measuring and reporting voltage and current phasors for a single-phase system at an average power consumption of only 30.8 mW -- one to two orders of magnitude lower than existing academic and commercial PMUs. This enables the proposed PMU to run for two weeks using an 11-Wh battery or indefinitely if paired with an inexpensive solar panel. A test-bench developed in accordance with the 2018 IEC/IEEE 60255-118-1 PMU Standard confirms the accuracy of this PMU. Given its low power consumption, the proposed design is expected to accelerate adoption of PMUs in modern distribution grids.

Mehdi Baharizadeh, Mohammad Sadegh Golsorkhi Esfahani, Nader Kazemi

Abstract The active power‐virtual frequency (P‐ω′) and reactive power‐virtual voltage (Q‐V′) droop control scheme has been suggested for coordinated control of distributed energy resources (DERs) in islanded microgrids. While this method mitigates the issue of active and reactive power coupling in the droop controller, its main limitation is power‐sharing error. Due to the local property of the virtual frequency and voltage, significant steady‐state errors occur for both active and reactive power sharing. In this paper, a decentralized method is proposed to eliminate the mentioned errors without utilization of communication links. In the proposed scheme, P‐ω′ and Q‐V′ droops are realized at the microgrid point of common coupling (PCC). By employing the PCC virtual frequency/voltage for the active/reactive power sharing of all DERs, the sharing errors caused by the local property are eliminated. Small signal stability of the proposed scheme is studied, and Hardware‐in‐the‐Loop (HIL) experimental results are presented to validate the proposed method and highlight the improvements compared with the conventional P‐ω′/Q‐V′ scheme. The results verify the efficacy of the proposed method for providing accurate active and reactive power sharing while regulating the frequency and voltage close to the rated values.

Yicen Liu, Chenguang Yang, Yujun Guo et al.

Abstract The grounding electrode line is an important part of the Ultra high voltage direct current (UHVDC) transmission system. It acts as the channel to conduct the unbalanced current and the grounding current.The arcing horn consists of a pair of electrodes installed in parallel at both ends of the insulator string, which provides a discharge channel for the fault current by an air gap to protect the insulators. In this paper, the voltage and current distributions of the arcing horn were studied when the grounding electrode line was struck by lightning. It is found that the current and voltage gradually decrease along the direction from the converter station to the earth electrode. An active arc extinguishing method based on variable resistance for arcing horn was proposed. An electromagnetic transient simulation model of the grounding electrode line is established based on the electrical parameters of a ±800 kV UHVDC transmission system. It is found that the absorbed energy of the arc extinguishing unit needs to be at least 31.2 and 49.6 kJ when the lightning current is 20 and 50kA, respectively. According to the calculation results, the arcing horn with arc extinguishing unit was developed and tested. The test results verifies that the designed arcing horn can meet the requirements of engineering application.

Yuehao Zhao, Zhiyi Li, Ping Ju et al.

Abstract Stochastic wind power prediction errors hurt the normal operation of integrated power and natural gas systems (IPGS). First, the data‐driven stochastic chance‐constrained programming method is applied to deal with wind power prediction errors, and its probability distribution is accurately fitted by variational Bayesian Gaussian mixture model with massive historical data. In addition, the data‐driven chance constraints of tie‐line power and reserve capacity of gas turbine are built. Next, to utilize wind power more reasonably, the operational characteristics and optimal commitment of power‐to‐hydrogen devices are considered and modelled in proposed strategy to reflect the actual situation of IPGS. Then, the original complicated dispatch problem is converted into a tractable second‐order cone programming problem via convex relaxation and quantile‐based analytical reformulation techniques. Finally, the effectiveness of the proposed strategy is validated by numerical experiments based on a modified IEEE 33‐bus system integrated with a 10‐node natural gas system and a micro hydrogen system.

Alfredo Testa, Gary Chang, Paola Verde

Electrical power quality is a vital aspect when designing or assessing the operation of all modern power systems and forms an important part of the ongoing energy transition to more efficient and multi-vector systems. However, the ongoing proliferation and changing functionality of power electronic devices, coupled with new grid operating paradigms, such as renewable energy sources integration, microgrids, low-voltage dc distribution networks, and the large-scale integration of electric vehicles, present unique opportunities and challenges for grid operators the world over and require new assessment methods and fresh perspectives on the role of power quality.

Jesus R. Perez-Cardona, John W. Sutherland, Scott D. Sudhoff

Electric Vehicles (EVs) are considered among one of the ‘clean’ energy technologies in the transportation sector because the vehicles themselves do not generate combustion emissions. However, the substantial environmental footprint associated with the materials needed to create these technologies (extraction, manufacturing, and solid waste at end of life) calls into question their ‘clean’ label. In addition, their increasing demand adds to the existing supply risk (SR) through the requirement of critical materials. To address this, the purpose of this study is to establish a design model for electric traction motors, which are used in EVs, that will address the SR issues early in the design stage. The design model incorporates a genetic algorithm with the following objectives: minimum motor mass, minimum energy consumption, and minimum SR-equivalent. The SR-equivalent objective prioritizes the minimization of materials with high SR. Using the case study of a surface-mounted permanent magnet synchronous motor, results show how each objective is related to each other and to the parameters chosen as variables. Further analysis shows the benefits of minimizing for SR-equivalent of required materials. Future work is needed to improve the design model in terms of other important metrics such as minimizing environmental impact and cost.

Abhijeet Sahu, Katherine Davis, Hao Huang et al.

There is a crucial need to enhance the reliability and resilience of our nation’s critical energy infrastructure. Electric power systems are cyber-physical critical infrastructure with distinct, interacting networks comprising electrical, communications, and interdependency layers. Resilience requires modeling and monitoring all layers for prevention, early detection, and proactive threat assessment. This paper presents the research and design of a novel energy management system (EMS) called Cyber-Physical Resilient Energy Systems (CYPRES) to accomplish this goal. The CYPRES EMS architecture and methods are all cyber-physical to cohesively model and analyze the power system as a cyber-physical system (CPS). Results are illustrated for this proof-of-concept solution utilizing a 2000-bus cyber-physical synthetic electric grid.

Lixuan Zhu, Ping Ju, Yiping Yu

Abstract In modern power systems, the impact of random power sources and loads on power systems is increasing, resulting in threatened system frequency security. However, traditional methods are often not comprehensive in modelling randomness, and there is no analytical method to assess the frequency response of power systems under uncertain power fluctuations. Here, the power fluctuation in a power system is regarded as an interval random quantity. An analytical prediction method of the power system frequency deviation under uncertain power fluctuation is proposed. Through further deduction, the allowable range of power fluctuation under the premise of secure frequency deviation can also be defined, which provides a reference for frequency security and accident prevention in power systems. Numerical simulations with the model of the East China Power Grid demonstrate that the proposed analytical method can delimit the response interval of system frequency deviation well, and the backstepping calculation can also delimit the allowable range of power fluctuation to ensure the secure operation of the system.

Kirti Gupta, Subham Sahoo, Bijaya Ketan Panigrahi et al.

The development of power electronics-based medium voltage direct current (MVDC) networks has revolutionized the marine industry by enabling all-electric ships (AES). This technology facilitates the integration of heterogeneous resources and improves efficiency. The independent shipboard power system (SPS) is controlled by exchanging measurements and control signals over a communication network. However, the reliance on communication channels raises concerns about the potential exploitation of vulnerabilities leading to cyber-attacks that could disrupt the system. In this paper, a notional 12 kV MVDC SPS model with zonal electrical distribution system (ZEDS) architecture is considered as an exemplary model. As the system stability is closely linked to the transient performance, we investigate how to determine the operational status of the system under potential data integrity attacks on the governor and exciter of the power generation modules (PGMs). Further, the impact of these attacks on the stability of rotor speed and the DC link voltage is derived and discussed. The simulation of the system is carried out in MATLAB/Simulink environment.

H. Susanto, N. Lazarides, I. Kourakis

Flat band systems can yield interesting phenomena, such as dispersion suppression of waves with frequency at the band. While linear transport vanishes, the corresponding nonlinear case is still an open question. Here, we study power transmission along nonlinear sawtooth lattices due to waves with the flat band frequency injected at one end. While there is no power transfer for small intensity, there is a threshold amplitude above which a surge of power transmission occurs, i.e., supratransmission, for defocusing nonlinearity. This is due to a nonlinear evanescent wave with the flat band frequency that becomes unstable. We show that dispersion suppression and supratransmission also exist even when the band is nearly flat.