Hasil untuk "Distribution or transmission of electric power"

Markus Reuß, T. Grube, M. Robinius et al.

Abstract Hydrogen could play a key role in future energy systems by enabling the storage of excess electricity from renewable power sources, like solar and wind, and fueling emission-free fuel cell electric vehicles. Nevertheless, the temporal and spatial gap between the fluctuating production in electrolysis plants and the demand at fueling stations necessitates the construction of infrastructures. Different technologies are available for storing and transporting hydrogen in its gaseous or liquid states, or even via liquid organic hydrogen carriers. To select and compare these different infrastructure options on a nationwide scale in Germany for an energy system 2050, we carried out an infrastructure assessment with spatial resolution to analyze the resulting costs and CO2 emissions, as well as the primary energy demand. To do so, methods for designing a spatially-resolved infrastructure are presented. In particular, the setup of a transmission pipeline with gaseous trailer distribution has not been well represented and investigated in the literature so far. The results show that salt caverns, as well as transmission pipelines, are key technologies for future hydrogen infrastructure systems. The distribution should be handled for low penetration of fuel cell vehicles rates with gaseous compressed trailers and replaced by distribution pipelines in areas with high fueling station densities. This ensures the cost-effective supply during the transition to higher fuel cell vehicle fleets.

Eve Tsybina, Viswadeep Lebakula, Piljae Im et al.

Choosing the right HVAC system or the right algorithm of implementing demand response could create significant energy and environmental gains while maintaining resident comfort. However, these choices are closely related to the concept of user comfort, which in turn requires a reasonable fit between user preferences and temperature setpoints. While setting the temperature right is a well-researched question, systems in transition from one setpoint to another are currently not thoroughly addressed in research. But how tolerant the residents really are if a system spends a large share of time outside of the comfort setpoint? This study gives some early insights on how the deviation of temperature from the setpoint affect perceived resident comfort. We use two weeks of data for a smart neighborhood located in Atlanta, GA. We find that the system spends 20% - 50% of time deviating from the setpoint by more than 1°F. However, we do not find that increasing deviations cause resident complaints or increasing overrides.

Chengrui Du, Yuan Gao, Lili Wang et al.

With the large-scale integration of wind power and photovoltaic (PV) into the grid, dealing with their output uncertainties and formulating more reliable scheduling strategies has become a critical challenge for the efficient operation of hydropower-dominated inter-basin hydro-wind-PV complementary systems. To quantify the uncertainty associated with wind and PV power generation, this paper proposes a method for generating wind and PV power output scenarios, combining adaptive diffusion kernel density estimation with Copula theory. Scenario reduction is then carried out using the K-means clustering algorithm. Based on this, a medium- and long-term stochastic expectation model for the inter-basin hydro-wind-PV complementary system is developed. The model is subsequently solved using the Gurobi 11.0.3 optimization solver within the MATLAB environment. A case study is conducted based on a selected inter-basin hydro-wind-PV clean energy base in China. The results demonstrate that the proposed scheduling strategy effectively addresses the unpredictability of wind and solar power, improves the overall utilization of renewable energy sources, and facilitates more efficient water level regulation at each power station. Furthermore, it significantly enhances the overall performance and efficiency of the complementary system.

Hang Chen, Maoyuan Ye, Peng Yang et al.

Power transmission corridor hazard segmentation (PTCHS) aims to separate transmission equipment and surrounding hazards from complex background, conveying great significance to maintaining electric power transmission safety. Recently, the Segment Anything Model (SAM) has emerged as a foundational vision model and pushed the boundaries of segmentation tasks. However, SAM struggles to deal with the target objects in complex transmission corridor scenario, especially those with fine structure. In this paper, we propose ELE-SAM, adapting SAM for the PTCHS task. Technically, we develop a Context-Aware Prompt Adapter to achieve better prompt tokens via incorporating global-local features and focusing more on key regions. Subsequently, to tackle the hazard objects with fine structure in complex background, we design a High-Fidelity Mask Decoder by leveraging multi-granularity mask features and then scaling them to a higher resolution. Moreover, to train ELE-SAM and advance this field, we construct the ELE-40K benchmark, the first large-scale and real-world dataset for PTCHS including 44,094 image-mask pairs. Experimental results for ELE-40K demonstrate the superior performance that ELE-SAM outperforms the baseline model with the average 16.8% mIoU and 20.6% mBIoU performance improvement. Moreover, compared with the state-of-the-art method on HQSeg-44K, the average 2.9% mIoU and 3.8% mBIoU absolute improvements further validate the effectiveness of our method on high-quality generic object segmentation. The source code and dataset are available at https://github.com/Hhaizee/ELE-SAM.

Mona Ghassemi

To achieve net-zero emissions by 2050, all-electric transportation is a promising option. In the U.S., the transportation sector contributes the largest share (29 percent) of greenhouse gas emissions. While electric vehicles are approaching maturity, aviation is only beginning to develop electrified aircraft for commercial flights. More than 75 percent of aviation emissions come from large aircraft, and this impact will worsen with 4-5 percent annual air travel growth. Aircraft electrification has led to two types: more electric aircraft (MEA) and all-electric aircraft (AEA). A MEA replaces subsystems such as hydraulics with electric alternatives, whereas an AEA uses electrically driven subsystems and provides thrust fully from electrochemical energy units (EEUs). For wide-body AEA, thrust demand is about 25 MW plus 1 MW for non-thrust loads, creating major challenges for electric power system (EPS) design. Achieving maximum power density requires minimizing mass and volume. Increasing voltage into the kilovolt range using medium-voltage direct current (MVDC) is a feasible option to enhance power transfer. Consequently, designing an MVDC EPS for wide-body AEA is critical. Because EPS failures could jeopardize passenger safety, reliability and resilience are essential. This chapter presents a load-flow model for DC systems to determine power flows in both normal and single-contingency conditions, followed by analysis of optimal MVDC EPS architectures. A complete EPS for wide-body AEA is introduced, with EEUs and non-propulsion loads located, distances estimated, and flow studies performed. Multiple architectures are evaluated for reliability, power density, power loss, and cost to identify optimal solutions.

Dionysios Moutevelis

Power systems are currently undergoing a rapid paradigm change in their operation. Centralised energy production is being replaced by a number of Distributed Generation (DG) units that are placed at different locations and voltage levels in power networks. These distributed units are mostly based on renewable energy technologies, like wind turbines and photovoltaic cells and are commonly interfaced to the grid via power electronic converters. These sources reduce energy system dependency on conventional generation units based on fossil fuels. At the same time, this shift introduces technical challenges for the safe and reliable operation of electricity network since DG sources do not inherently provide the grid regulation services of conventional, centralised generation units. Moreover, the increased penetration of renewable energy sources and their converter-based interfaces is creating voltage deviation and voltage stability issues in distribution networks. These issues range from overvoltages during hours of peak renewable generation, reverse power flows and sudden voltage drops due to the variable nature of renewable energy production. All of the above jeopardise the reliable operation of the distribution networks that were not originally designed to accommodate for these effects. The objective of this thesis is to propose novel techniques for the accurate assessment of the DG impact on voltage stability in distribution net works and investigate how the control capabilities of converter-based interfaces of DG units can be harnessed to improve stability margins and overall system robustness and performance.

P. Rahdan, E. Zeyen, C. Gallego-Castillo et al.

Distributed solar photovoltaic (PV) systems are projected to be a key contributor to the future energy landscape, but are often poorly represented in energy models due to their distributed nature. Here, we model the European power network with a high spatio-temporal resolution using a simplified model of distribution and transmission networks. Three scenarios, including a sector-coupled scenario with heating, transport, and industry are investigated. The results show that incorporating distributed solar PV leads to total system cost reduction in all scenarios (1.4 % for power sector, 1.9-3.7% for sector-coupled). The role of distributed PV is noteworthy in the sector-coupled scenario and is helped by other distributed technologies including heat pumps and electric vehicle batteries.

Tao Zheng, Ruozhu Zhang, Ying Chen et al.

Abstract The phase‐locked loop (PLL) is a critical control module applied in the control system of renewable energy sources (RESs) to synchronize with the grid voltage. When a fault occurs, the dynamic response process of the PLL will generate a phase locking error, resulting in a mass of harmonic components in the fault current of the PV inverter, which further poses challenges to transformer differential protection. To address the challenges posed by the phase locking error in practical engineering applications, this paper proposes an improved scheme that uses a digital computer algorithm to record and store the pre‐fault voltage and introduces the limiting coefficient. Firstly, the memory voltage is used to eliminate the phase locking error of the PLL, thereby mitigating harmonic distortion in the fault current of the RESs and ensuring the reliability of the transformer differential protection. In addition, the limiting coefficient is introduced to eliminate the effect of the increased amplitude of the fault current caused by the memory voltage. The voltage reference value of the inverter is multiplied by an appropriate limiting coefficient k and then output to the physical system. Finally, the effectiveness of the proposed scheme is verified by MATLAB/Simulink simulation.

Abdul Saleem Shaik, Mihoub Mohammed, Al Hatmi Humeid Abdullah et al.

The present study is centered on the investigation of longitudinal and lateral profiles of Extremely low-frequency Electromagnetic field experiments conducted at three distinct locations in Oman. The investigation encompasses findings obtained from 400kV transmission lines and substations. The analysis of electric and magnetic fields emitted by transmission lines was conducted using an EHP-50F E&H field analyzer sensor set and an environmental meter. The measurements were conducted at 400kV transmission lines or to a distance of the insignificant field at the high-voltage substation, various components such as power transformers, CT (current transformers), PT (potential transformers), circuit breakers, reactors, earth switches, transport couplers, lightning arrestors, and other. This research in Oman marks the initial exploration of various factors pertaining to the Oman Electricity Transmission Company (OETC) and its technical standards, which are founded on optimal practices. These factors encompass the interphase spacing, the spacing between conductors within a bundle of twin conductors, the configuration of phases on a tower, the crosssectional area of conductors, and similar considerations. The proposed study aims to support the Sultanate of Oman's objective of establishing a high-quality smart transmission grid by 2030. This system will facilitate the efficient, reliable, and secure transfer and distribution of power, while also offering economic benefits. This research aims to cater to the needs of students and engineers by offering a highly practical approach that utilizes appropriate equipment. This article presents a systematic approach to the implementation of a smart transmission grid, incorporating the aforementioned attributes.

Majid Majidi, Masood Parvania

Abstract The high adoption of electric vehicles (EVs) and the rising need for charging power in recent years calls for advancing charging service infrastructures and assessing the readiness of the power system to cope with such infrastructures. This paper proposes a novel model for the integrated operation of dynamic wireless charging (DWC) and power distribution systems offering charging service to in‐motion EVs. The proposed model benefits from a hierarchical design, where DWC controllers capture the traffic flows of in‐motion EVs on different routes and translate them into estimations of charging power requests on power distribution system nodes. The charging power requests are then communicated with a central controller that monitors the distribution system operation by enforcing an optimal power flow model. This controller coordinates the operation of distributed energy resources to leverage charging power delivery to in‐motion EVs and mitigate stress on the distribution system operation. The proposed model is tested on a test distribution system connected to multiple DWC systems in Salt Lake City, and the findings demonstrate its efficiency in quantifying the traffic flow of in‐motion EVs and its translation to charging power requests while highlighting the role of distributed energy resources in alleviating stress on the distribution system operation.

Yang Liu, Huanjin Yao, Zengjie Chen et al.

Abstract This paper proposes an improved expanding interior algorithm (EIA) to estimate the region of attraction (ROA) of power systems with wind power generation based on sum of squares (SOS) programming. An ordinary differential equation (ODE) model is derived for the doubly‐fed induction generator‐based wind turbine (DFIGWT), which is named as an enhanced synchronous‐generator‐mimicking (ESGM) model. The ESGM model bridges the gap between the requirement of an ODE model in ROA estimation and the conventional differential‐algebraic equation (DAE) model of the DFIGWT system. The ESGM model is able to accurately reflect the low frequency dynamics of the DFIGWT. Moreover, an improved EIA is designed to estimate the ROA based on SOS programming, which has higher efficiency than the existing ROA estimation algorithms based on SOS programming. It is able to adaptively search for the Lyapunov function and obtain an optimal estimation of the ROA in an iterative process. The accuracy and efficiency of this algorithm are verified in three test systems composed of DFIGWTs and synchronous generators (SGs). The morphological changes in the ROA of the test systems caused by the penetration of DFIGWT are examined.

Jesus Silva-Rodriguez, Elias Raffoul, Xingpeng Li

The rising integration of variable renewable energy sources (RES), like solar and wind power, introduces considerable uncertainty in grid operations and energy management. Effective forecasting models are essential for grid operators to anticipate the net load - the difference between consumer electrical demand and renewable power generation. This paper proposes a deep learning (DL) model based on long short-term memory (LSTM) networks for net load forecasting in renewable-based microgrids, considering both solar and wind power. The model's architecture is detailed, and its performance is evaluated using a residential microgrid test case based on a typical meteorological year (TMY) dataset. The results demonstrate the effectiveness of the proposed LSTM-based DL model in predicting the net load, showcasing its potential for enhancing energy management in renewable-based microgrids.

Xinliang Dai, Yi Guo, Yuning Jiang et al.

This paper proposes a real-time distributed operational architecture to efficiently coordinate intergrated transmission and distribution systems (ITD). At the distribution system level, the distribution system operator (DSO) computes the aggregated flexibility of all controllable devices by power-energy envelopes and provides them to the transmission system operators. At the transmission system level, a distributed nonlinear MPC approach is proposed to coordinate the economic dispatch of multiple TSOs, considering the aggregated flexibility of all distribution systems. The subproblems of the proposed approach are associated with different TSOs and individual time periods. In addition, the aggregated flexibility of controllable devices in distribution networks is encapsulated, re-calculated, and communicated through the power-energy envelopes, facilitating a reduction in computational complexity and eliminating redundant information exchanges between TSOs and DSOs, thereby enhancing privacy and security. The framework's effectiveness and applicability in real-world scenarios are validated through simulated operational scenarios on a summer day in Germany, highlighting its robustness in the face of significant prediction mismatches due to severe weather conditions.

Siyi Wang, Yulong Gao, Sandra Hirche

Designing networked control systems that are reliable and resilient against adversarial threats, is essential for ensuring the security of cyber-physical systems. This paper addresses the communication-control co-design problem for networked control systems under denial-of-service (DoS) attacks. In the wireless channel, a transmission power scheduler periodically determines the power level for sensory data transmission. Yet DoS attacks render data packets unavailable by disrupting the communication channel. This paper co-designs the control and power scheduling laws in the presence of DoS attacks and aims to minimize the sum of regulation control performance and transmission power consumption. Both finite- and infinite-horizon discounted cost criteria are addressed, respectively. By delving into the information structure between the controller and the power scheduler under attack, the original co-design problem is divided into two subproblems that can be solved individually without compromising optimality. The optimal control is shown to be certainty equivalent, and the optimal transmission power scheduling is solved using a dynamic programming approach. Moreover, in the infinite-horizon scenario, we analyze the performance of the designed scheduling policy and develop an upper bound of the total costs. Finally, a numerical example is provided to demonstrate the theoretical results.

S. Bustamante, M. Mañana, A. Arroyo et al.

Power transformers are the most important assets of electric power substations. The reliability in the operation of electric power transmission and distribution is due to the correct operation and maintenance of power transformers. The parameters that are most used to assess the health status of power transformers are dissolved gas analysis (DGA), oil quality analysis (OQA) and content of furfuraldehydes (FFA) in oil. The parameter that currently allows for simple online monitoring in an energized transformer is the DGA. Although most of the DGA continues to be done in the laboratory, the trend is online DGA monitoring, since it allows for detection or diagnosis of the faults throughout the life of the power transformers. This study presents a review of the main DGA monitors, single- or multi-gas, their most important specifications, accuracy, repeatability and measurement range, the types of installation, valve or closed loop, and number of analogue inputs and outputs. This review shows the differences between the main existing DGA monitors and aims to help in the selection of the most suitable DGA monitoring approach according to the needs of each case.

Chunyu Ai, Shan He, Weiqing Wang et al.

Abstract As a complex non‐linear system, the chaotic oscillation of power system seriously threatens the safe and stable operation of power grids. In this paper, a finite time adaptive synchronization control method is proposed to mitigate the problem of chaotic oscillation in the power system. The proposed method can realize chaos control and parameter identification by completely synchronizing the fractional‐order chaotic power system with the stable fractional‐order power system to identify parameters within a finite time. The fractional Lyapunov stability theory is used for numerical simulation. Theoretical and simulation results show that this method can effectively stabilize the system in a finite time. It is proved that compared with the adaptive synchronous control method, the control method is simpler in design, shorter in action time, and more meaningful in engineering practice.

Can Wang, Can Deng, Xuewei Pan

Abstract In a hybrid AC/DC microgrid (MG), the interlinking converter (IC) plays an important role in power flow regulation between subgrids. However, line impedance will cause deviations in the power transmitted by the IC if a communication device is not used. To realize accurate power delivery between subgrids without communication, an IC control method based on line impedance compensation is proposed. A harmonic signal is injected into the IC in this method using converters of distributed generation, which are connected to an AC bus. The specified frequency of the signal indicating the voltage of the AC bus can be acquired by an IC using a filter and phase‐locked‐loop (PLL) so that the IC can obtain line impedance by local information and then compensate for voltage drop to realize accurate power transmission. The entire implementation of this method uses no communication. Moreover, when multiple ICs run in parallel, this method can also be conducted easily and effectively to realize accurate power flow between subgrids and power sharing among ICs in proportion to the ICs’ rated capacity. This strategy is verified by simulation and hardware‐in‐the‐loop tests.

Ziqi Wang, Sizu Hou, Baikui Li et al.

Abstract The battery swapping mode is a promising way for electric vehicles (EVs) to participate in power grid frequency regulation. However, the operation mechanism and the uncertainty management in the process still lack research. Aiming at this issue, this paper proposes a day‐ahead bidding strategy for the battery swapping and charging system (BSCS) providing regulation reserve capacity in the ancillary service market. Firstly, a new BSCS‐based regulation model is established. Then, an ambiguity set based on Kullback–Leibler (KL) divergence is used to manage the uncertainty of regulation signals and battery swapping demands. Furthermore, a boundary expectation approach is proposed to turn the problem into robust optimization. Finally, after using the extreme scenario method (ESM) to generate extreme scenarios, a duality‐free column‐and‐constraint generation (C&CG) algorithm is employed to solve the problem. The case studies demonstrate that BSCS can provide economical and robust reserve capacity bidding plans in the day‐ahead market with the proposed strategy. At the same time, the BSCS‐based regulation service is simulated with the battery development trend in the future, and suggestions are given.

Tao Zhang, Jianhua Yang, Kaiyuan Jin et al.

Abstract With the increasing penetration of distributed photovoltaic generation (DPVG) in the rural distribution network, some problems such as abandoning solar energy and increasing voltage fluctuation have become more and more prominent. In order to promote local or nearby power consumption of the photovoltaic (PV) generation in the distribution network, the profit strategy is given with an optimal electricity price based on blockchain technology (BCT) by considering the topology, the load fluctuation of the distribution network and the reputation value of agricultural park consumers. The electricity price in the blockchain (BC) transaction is used as an intermediate variable to establish the revenue model for the PV generation, the agricultural park consumers and the distribution network. The power trading mechanism of the PV generation is constructed in the decentralized management agency of the BC. The maximum overall comprehensive income of the PV generation and the park consumers is used as the objective function, and the Stackelberg game theory is applied to prove the existence of the optimal game strategy in the transaction. The local power consumption method of the PV generation is simulated with the optimal electricity price in the IEEE 33‐node distribution network. The problem of abandoning solar energy is effectively relieved within an appropriate voltage limitation, and the comprehensive benefit of the PV generation and the park consumers is raised in the distribution network.

Xinyi Jing, Meng Song, Ciwei Gao et al.

Abstract In the transactive energy market (TEM), prosumers are assumed to be rational. However, prosumers’ trading behaviours are affected by many factors (e.g. social relations, personal preferences, and habits). Their trading demands vary in benefits, comfort levels, and environmental consciousness, which show bounded rationality. Accordingly, this paper introduces the mental accounting theory to develop a trading decision‐making method by characterizing prosumers’ actual trading behaviours. It quantified prosumers’ motivations and psychological changes by the risk attitude and subjective value models in the process of multi‐account management. The updating rules of trading decisions and multi‐round bidding market mechanism are also designed to improve the social welfare and market efficiency. Case studies demonstrate that the proposed method can make prosumers trade in TEM under their actual intentions and bounded‐rationality. And the market mechanism can help to increase social welfare and market efficiency.