Hasil untuk "Distribution or transmission of electric power"

Mitsuyoshi Enomoto, Keima Wakatsuki, Kenichiro Sano

Multi-terminal high-voltage dc (HVDC) transmission system is a promising approach to connect offshore wind power plants (WPPs) to onshore ac grids. However, there is no standardized protection method against DC faults. As one of its protection methods, mechanical dc circuit breakers (DCCBs) have the potential to improve supply reliability against dc faults while avoiding a cost increase. Nevertheless, due to their relatively slower operation, the blocking of half-bridge-based modular multilevel converter (HBMMC) is often required. In offshore ac collecting system, where the HBMMC maintains the grid voltage, such converter blocking can destabilize the grid voltage and lead to shutdowns of offshore WPPs. Large scale shutdowns of offshore WPPs may have a negative impact on onshore ac grids. Therefore, this article proposes a protection method that enables the continuous operation of offshore WPPs while using mechanical DCCBs. The proposed method focuses on the backbone HVDC configuration connecting multiple onshore and offshore terminals, and applies different fault clearing methods across the terminals. At onshore terminals which form a loop configuration, mechanical DCCBs selectively isolate the faulted section. At offshore terminals which form a radial configuration, reconfiguration is employed to reroute power transmission from the faulted line to the healthy line. These operations are coordinated based on the fault ride-through (FRT) capability of offshore WPPs and realizes their continuous operation. The proposed method is verified by an experiment using the scaled-down three-terminal HVDC system.

Hadi Norouzi

Jayant Sharma, CK Sundarabalan, C Balasundar

Kenta Koiwa, Tomonori Tashiro, Tomoya Ishii et al.

Wind power plants (WPPs) have been rapidly installed worldwide as an alternative source to thermal power plants. Nevertheless, since the outputs of WPPs constantly fluctuates due to variations in wind speed, WPPs expose power systems to power quality degradation, such as frequency fluctuation. This paper develops an optimal control method of energy storage systems (ESSs) that utilizes WPP output prediction to mitigate WPP output fluctuation. In the proposed method, an output reference of ESS can be obtained as the solution of an optimization problem. Specifically, the proposed method regulates the state of charge of ESS within its appropriate range by minimizing a cost function. At the same time, the minimization of ESS output and multiple grid codes related to the mitigation of WPP output fluctuation are considered as constraints. As a result, the proposed method enables us to mitigate the output fluctuation of WPP sufficiently by an ESS with small rated power. The effectiveness of the proposed method is demonstrated through comparative analysis with conventional methods via scenario simulations.

Gopal Lal Rajora, Miguel A. Sanz‐Bobi, Lina Bertling Tjernberg et al.

Abstract Power system protection and asset management present persistent technical challenges, particularly in the context of the smart grid and renewable energy sectors. This paper aims to address these challenges by providing a comprehensive assessment of machine learning applications for effective asset management in power systems. The study focuses on the increasing demand for energy production while maintaining environmental sustainability and efficiency. By harnessing the power of modern technologies such as artificial intelligence (AI), machine learning (ML), and deep learning (DL), this research explores how ML techniques can be leveraged as powerful tools for the power industry. By showcasing practical applications and success stories, this paper demonstrates the growing acceptance of machine learning as a significant technology for current and future business needs in the power sector. Additionally, the study examines the barriers and difficulties of large‐scale ML deployment in practical settings while exploring potential opportunities for these tactics. Through this overview, insights into the transformative potential of ML in shaping the future of power system asset management are provided.

Mohamed Zellagui, Nasreddine Belbachir, Adel Lasmari et al.

Abstract Distributed generators have grown in significance for the technical and financial operation of electric power systems in recent years. The integration of these generators into the electrical distribution network (EDN) has experienced rapid growth, primarily driven by advancements in renewable energy sources (RESs), particularly photovoltaic distributed generators (PVDGs). With the increasing implementation of solar energy as a RES, designing the optimal integration of PVDGs into medium voltage direct current (MVDC) networks is crucial to comprehensively analyzing technical and economic factors. To address this issue, a new multiple objective function (MOF) is proposed, which combines various techno‐economic parameters such as total active power loss (APL), voltage deviation (VD), and the investment cost of PVDGs (ICPVDG) installed in the test system. The objective is to minimize the MOF simultaneously to achieve the optimal incorporation of PVDGs. This study aims to solve the allocation problems related to the location and size of PVDG units in the modified MVDC test systems IEEE 27 and 33‐bus. Simulation results demonstrate the superior accuracy and effectiveness of the equilibrium optimization algorithm (EOA) in achieving the minimum MOF. The utilization of multiple PVDG units reduces overall active power losses and improves voltage profiles across all buses.

Minjie Wei, Mi wen, Yi Zhang

Abstract Spatial power load forecasting is crucial for power grid planning, generation planning, dispatching, efficient power utilization, and sustainable development. The integration of new energy sources and electric vehicles has significantly altered grid loads, increasing the complexity of spatial load forecasting. However, existing techniques fail to fully consider the temporal and spatial correlation characteristics of data, leading to challenges in data identification and summarization. This reduces load forecasting accuracy and prolongs prediction time. To address these issues, a spatial electric load forecasting method based on improved scale limited dynamic time warping (LDTW) and graph convolutional network (GCN) are proposed. Firstly, the improved scale LDTW is used to improve the clustering effect of K‐Mediods++, refine the type of load data, and make the subsequent model training more targeted. Secondly, the interconnections and distances of substations in a real network structure is used to build a graph model to capture the power load distribution. Finally, based on the clustering results and the graph model, GCN‐LSTM is used to construct the spatio‐temporal forecasting algorithm. The proposed algorithm is tested using load data from a region in Shanghai and compared with other advanced algorithms. Results show that the algorithm achieves higher prediction accuracy and efficiency.

Sayed Mahdi Koloushani, Seyed Abbas Taher

Abstract This paper introduces a virtual consensus‐based wide area differential protection method through cooperative control concepts and graph theory. Using multi‐agent systems eliminates the need for a direct telecommunication connection between the protective relays to implement the proposed differential protection. In addition, applying telecommunication subgraphs facilitates the establishment of numerous differential protection areas. Collaboration between protected areas is facilitated by common agents, establishing a wide‐area cooperative protection network. The capability of the network operator to define various protection areas and the collaboration between these areas ensure the versatility of the proposed method for various protection purposes. The present paper primarily represents the application of the proposed protection system as a wide‐area supervisor protection for distance relays. Performance evaluations on an IEEE 39‐bus test system illustrate the method's effectiveness in various scenarios. The results show enhanced power system stability and resilience, particularly when traditional methods struggle to detect power swings with high impedance variation rates.

Mostafa Jabari, Amin Rad, Morteza Azimi Nasab et al.

Abstract The escalating global population and energy demands underscore the critical role of renewable energy sources, particularly solar power, in mitigating environmental degradation caused by traditional fossil fuels. This paper emphasizes the advantages of solar energy, especially photovoltaic (PV) systems, which have become pivotal in hybrid energy systems. However, accurate modelling and identification of PV cell parameters pose challenges, prompting the adoption of meta‐heuristic optimization algorithms. This work explores the limitations of existing algorithms and introduces a novel approach, the bio‐dynamics grasshopper optimization algorithm (BDGOA). The BDGOA addresses deficiencies in both exploration and exploitation phases, exhibiting exceptional convergence speed and efficiency. The algorithm's simplicity, achieved through the implementation of an elimination phase and controlled search space, enhances its performance without intricate calculations. The study evaluates the BDGOA by applying it to identify unknown parameters of five solar modules. The algorithm's effectiveness is demonstrated through the extraction of parameters for RTC France, PWP201, SM55, KC200GT, and SW255 models, validated against experimental data under diverse conditions. The paper concludes with insights into the impact of radiation and temperature on module parameters. The subsequent sections of the paper delve into the intricacies of the PV cell and module model, articulate the formulation of the proposed algorithm, present simulations, and analyse the obtained results. The BDGOA emerges as a promising solution, overcoming the limitations of existing algorithms and contributing significantly to the advancement of accurate and efficient PV cell parameter identification, thereby propelling progress towards a sustainable energy future.

Bin Zou, YuLi, Nan Yang et al.

Qasem Asadi, Hamid Falaghi, Ali Ashoornezhad et al.

With the increasing demand for electricity demand, power distribution utilities must provide an efficient and appropriate Service Restoration (SR) strategy to restore customers as soon as possible after power outages to increase the network resiliency and reliability. The heuristic SR algorithm presented in this article is a bi-stage algorithm that initially re-energizes some loads quickly by remote-controlled switches in the first stage and then proceeds to restore the rest of the network in the second stage. Beside solving the restoration problem in a bi-stage algorithm, determining the optimal Switching Sequences (SSs) and applying the Expected Energy Not Supplied (EENS) as objective function included in this research. Also, taking into account the time of occurrence of the failure and the daily load curve, the position of the maintenance team, load transfer capability and the traffic conditions of the network has increased the attractiveness and practicality of the proposed method. The heuristic SR algorithm was applied on a standard IEEE 69-bus system in various scenarios. The results indicated a significant difference in the solutions of the problem and the ENS in different scenarios. Finally, it was found that using this heuristic method would lead to optimal, accurate, and applicable solutions for SR in distribution networks.

Joana Alves Ribeiro, Fernando J. G. Pinheiro, Maria Alexandra Pais et al.

Abstract New geomagnetically induced current (GIC) computations for mainland Portugal include the entire power network, with network parameters and topology provided by the transmission grid operator for all the high voltage lines (150, 220, and 400 kV). The first 3D conductivity model for the west region of the Iberian Peninsula, based on 31 broadband magnetotelluric soundings, is used in calculations, revealing the effect of different crustal domains in GIC distribution. Geomagnetic field variations are taken from Coimbra or San Fernando magnetic observatories, according to the Nearest Neighbor method, and used together with surface impedance values predicted from the new conductivity model to calculate the induced electric field on a regular grid. The global distribution of GICs over the power network is characterized based on results derived for the eight most significant storms registered in the Iberia during solar cycle 24. Substations susceptible to the highest GICs are found near the transition between the granitic geotectonic unit of Central Iberian Zone and the Lusitanian Basin. A prototype of a Hall effect sensor has been installed at a substation and is active since the end of August 2021. In order to validate our GIC model, recent measurements are compared with simulations. GIC computation is prone to uncertainties from various sources, possibly contributing with different weights to the final error in computed values. Here, we evaluate the contribution of substation earthing resistance and nonuniqueness of the conductivity model to the final GIC uncertainties.

Mohamed Abdeen, Mohammed Hamouda Ali, Ahmed Mohammed Attiya Soliman et al.

Abstract The interaction between the wind farm and the series‐compensated transmission line may lead to the sub‐synchronous oscillation (SSO) phenomenon which affects the system stability and equipment safety. Among the presented methods for damping the SSO phenomenon, the supplementary damping controller (SDC) is the most prevalent method because of its low cost, effectiveness, and simplicity. In all previous studies, one input control signal is fed to the SDC for mitigating the SSO. Here, two input control signals (active power and reactive power deviation) are applied to the SDC for enhancing the system stability and damping the SSO quickly. The ability of the proposed method for damping the SSO has not been investigated before. The proposed SDC is embedded into the q‐axis of the rotor‐side converter (RSC) inner current loop. The modified IEEE first benchmark model (FBM) is used to analyze the performance of the proposed method under different compensation levels, variable wind speeds, and sub‐synchronous control interaction (SSCI). Small‐signal stability using the eigenvalue approach is carried out, where the impact of the proposed method on sub‐synchronous mode, and super‐synchronous mode is investigated. The results successfully prove the superiority of the proposed method for damping the SSO under various operating conditions compared to some previous methods, where the least overshoot and faster convergence have been achieved by the proposed method in all studied cases.

Navid Ghaffarzadeh, Ali Bamshad

Nowadays, microgrids are expanding due to their numerous benefits. However, the control and protection of microgrids is a serious challenge. All the implemented plans for the protection of microgrids have drawbacks. This study presents a bi-level multi-agent system (MAS) approach to microgrids protection. The first level is responsible for microgrid lines protection. Firstly, it calculates the pilot impedance of each line. For line’s internal faults, pilot impedance is a limited number, but for line’s external faults, it will be infinite. so, the line’s internal fault is detected by evaluation of pilot impedance with a predetermined value. The second level is responsible for Distributed Generation (DGs) protection. Firstly, it decomposes the DGs output signals by Discrete Wavelet Transform (DWT). Then, it multiplies the summations of the first and second level’s details of each signal together as CC index. CC is zero in normal grid conditions and has a negative peak with a sharp negative rate in external faults, and will experience a positive peak with a sharp positive rate for internal faults and changes with a very slow rate in case of grid’s natural transitions. So, the agent detects the fault by evaluating the CC. The simulation results in a 5-bus microgrid indicate the proposed scheme protects the microgrid with a reliability of 100% with considering all microgrid’s uncertainties.

Zhanpeng Chen, Yan Hu, Nengling Tai et al.

Abstract The complex energy conversion and the volatility of renewable energy/load bring great challenges to the operation of the park‐level integrated energy system (PIES). To overcome this challenge, this paper proposes a multi‐timescale flexible dispatching method to fully exploit the flexibility of PIES in the energy cascade utilization mode. The cascade utilization model for energy flow is firstly established to analyse the coupling and complementary of heterogeneous energy. On this basis, the supply‐demand general equations of multi‐energy flexibility are proposed, which accurately quantify the ability to cope with uncertainty through mutual flexibility. Through coordinated complementation and mutual exchange of multi‐grade flexibility, the system realizes the suppression of random power fluctuations. The scheduling model includes day‐ahead dispatch and intraday multi‐time scale dispatch, which can satisfy the adjustment speed requirements of different energy. Numerical results demonstrate that the proposed method effectively enhances the flexibility and economy of system operation. The flexible demand for energy of all grades can be satisfied. Compared with the flexible dispatch in the triple energy supply structure, the operating cost is reduced by 9.07%.

Wenkai Liu, Meng Zhan

Abstract A variety of power electronic equipment in AC/DC distribution networks causes oscillations with unknown origin. A self‐sustained low‐frequency oscillation appeared recently in a practical AC/DC distribution network in Tongli, Jiangsu Province, China. In this paper, the accident is introduced, and the oscillation phenomenon has been successfully reproduced by theoretical modelling. Based on the small signal model, the oscillation is well analysed and an additional controller is designed to suppress this low‐frequency oscillation. The reason of the oscillation is related to the power and control parameters of buck converter; the system is critically stable within the linear system stability theory, namely, the leading eigenvalues of the small‐signal system are on the imaginary axis. Meanwhile, a novel inhomogeneity phenomenon for oscillation amplitudes on different voltage‐level DC buses, which are not proportional to their steady‐state voltages, is found. This paper provides a new case study of self‐sustained oscillations coming from a practical AC/DC distribution network and is of great significance for our understanding of oscillations in electric power engineering.

Di Wu, Xu Ma, Tao Fu et al.

This paper presents a novel dispatch and evaluation framework for battery energy storage systems (BESSs) to minimize a load servicing entity’s coincident demand during system peak hours. The framework consists of i) a two-step BESS dispatch process that accounts for uncertainties in forecasting system peak and using limited battery cycle life, and ii) procedures to design control parameters, determine BESS duration, and estimate the corresponding net benefits. In the proposed dispatch, a rule-based triggering mechanism is executed to determine whether to dispatch a BESS on an operating day by comparing the peak-day probability with a predetermined threshold. Once the dispatch is triggered, a model predictive control is carried out to maximize the expected reduction in peak demand. By exercising this two-step dispatch method with different thresholds, one can explore the trade-off between peak demand reduction effectiveness and loss of battery life, and thereby identify the optimal thresholds to maximize cumulative economic benefits. Case studies are conducted using the data provided by utilities in North Carolina. Simulation results are presented to demonstrate the effectiveness of the proposed method.

Lei Sun, Zhichao Yang, Mingming Li et al.

Abstract A bi‐level load restoration optimisation strategy is proposed for the transmission system with wind farm‐energy storage combined systems (WESs), taking the variant length of time steps into account. The upper level model is proposed to maximise weighted restored loads, and formulated as a mixed‐integer linear programming model. After solving the upper model, the optimal load pickup and transmission line restoration scheme can be obtained and delivered to the lower level model. The lower level model adopts a non‐linear model to minimise the length of the current time step, which is delivered to the upper lever model. By iteratively solving the upper and lower level models, the optimal load pickup and transmission line restoration scheme as well as the optimal length of current time step can be obtained. To minimise the gap between the scheduled generation of the WES and its actual power generation, a real‐time energy storage (ES) dispatch strategy is proposed taking maximum charging‐discharging cycles of the ES into account. The entire load restoration strategy can be obtained by iteratively solving the proposed model with updated operational conditions of power systems. Finally, two test systems are employed to verify the validity and correctness of the proposed model.

Zhanlong Zhang, Yiqiao Li, Chengfeng Gao et al.

Abstract The Tower grounding grids are important power facilities for transmission line grounding protection. The accurate measurement of grounding resistance provides data support for the safe operation of the grounding grids. The existing measurement methods for grounding resistance are mainly based on the 0.618 method, which has two disadvantages: (1) The distance between the voltage electrode and the measuring point should not be less than 2.5× the length of the scattered grounding electrode; (2) the long measuring wires ensure the measurement accuracy of the 0.618 method, but the long‐distance between the electrodes and measuring point makes it difficult to carry out in the complex environment. To accurately solve the problems, this paper proposes a novel measurement method of grounding resistance with shorter measuring wire based on Green's theorem. Combined with the physical model of the actual tower grounding grid, this paper establishes the potential equations in local space around the grounding grid and analyses the distribution of the equipotential surface. The results show that the proposed novel method of measuring tower grounding resistance can conveniently measure the grounding resistance, which greatly shortens the length of the measuring wire and has better adaptability for towers in a complex environment.

Nikhil Pathak, Zechun Hu

Abstract Typically offshore wind farms are connected to the onshore AC grid networks using voltage source converter based MT‐HVDC networks. This article aims to formulating optimal power flow (OPF) problem of MT‐HVDC system connected large offshore wind farms using mixed‐integer semi‐definite programming approach. Both constant power and droop control modes of voltage source converter converters are considered in OPF formulation. Main objective of OPF is to minimize DC power losses and simultaneously optimizing droop gains of the converters. OPF problem is solved using SDP relaxation; while its exactness is discussed using graphical properties. It is found that MT‐HVDC system exhibit acyclic graph property which guarantees that SDP relaxation would give either rank‐1 or ‐2 solutions. For rank‐2 solutions, an iterative rank reduction algorithm is introduced to achieve rank‐1 solutions from which global optimal solutions could be recovered easily. The comparative analysis is also performed with previously employed optimization methods used to solve the OPF problem. Furthermore, steady state solutions obtained from the proposed OPF formulation are also cross‐verified using dynamic simulation studies of offshore wind farms connected MT‐HVDC networks.