Hasil untuk "Distribution or transmission of electric power"

Anamika Yadav, Abhinav Kumar Nirala, Aleena Swetapadma

Shuai Zhang, Wei Zhang, Song Wang et al.

Yanzhao Wang, Haiqiong Li, Jiangogn Zhang et al.

Oscar Danilo Montoya, Walter Gil-González

Zhaoliang Xing, Hao Ge, Fanqiu Zeng et al.

In the current design and verification processes of insulation structures for high-voltage oil-immersed capacitors, there is a heavy reliance on electric field simulation calculations using idealized models that lack empirical validation of spatial electric fields. This study employs the Kerr electro-optic effect to establish a non-contact optical remote sensing system for measuring the spatial electric field distribution in the insulating liquid dielectric (benzyltoluene) between the capacitor’s element and the case under various temperatures and main insulation distances. The findings reveal that the measured spatial electric field stress can be up to 15% higher than the simulated values. The electric field stress measured in the Y1 direction (up toward the capacitor top) is comparable to that measured in the Y2 direction (down toward the capacitor end). Furthermore, when varying the main insulation distance, the electric field stress consistently shows a negative correlation with increasing measurement distance. Specifically, at a main insulation distance of 1.5 mm, the electric field stress is 1.81 times that at 5.5 mm. As the temperature rises, the spatial electric field stress increases gradually, and the electric field distribution becomes more uneven at higher temperatures. At 80 °C, the field stress is approximately 1.57 times that at 20 °C, with the measured field stress at 80 °C being 19% higher than the simulated value. Finally, this paper undertakes a comprehensive theoretical analysis and experimental validation to elucidate the discrepancies between simulated and measured spatial electric fields. Leveraging these insights, it proposes advanced optimization strategies for the insulation structures of capacitor elements. The outcomes of this study furnish substantial technical and theoretical support, significantly enhancing the design, verification, and optimization processes for insulation in oil-immersed capacitors.

Bin Zou, YuLi, Nan Yang et al.

Qi Qi, Haobo Guo, Xueying Yang et al.

Abstract The movement towards electrification is entailing deep changes in power systems. On the demand side, the adoption of electric heating (EH) has grown rapidly in recent years. To eliminate the voltage fluctuations caused by the random switching‐on/‐off behaviors of EHs in some application scenes with special‐power‐line in low voltage distribution networks (LVDNs), a swarm‐intelligence‐based coordinated control approach of EHs for voltage stabilization with zero communication burden while guaranteeing the users’ thermal comforts is researched. A novel bird‐perch‐on‐branch (BPB) ‐based swarm intelligence theory is proposed, which reveals the mapping relation between local observations and global states. On this theoretical basis, a multi‐agent reinforcement learning (MARL) framework is developed for the coordinated dispatch of EHs, where the deep‐Q‐network (DQN) algorithm is adopted to learn and generate the optimal control policy for each EH. The implementation of the proposed MADQN‐BPB approach is described based on the principle of centralized‐training and decentralized‐execution. Comparative control performances of MADQN‐BPB with a commercially available approach, and the global optimal solution are evaluated. Simulation results verify the capability of MADQN‐BPB in voltage stabilization with zero communication burden. Its control performance is close to that of the global optimal solution, and is scalable to the variations of environment.

Ruijing Zhu

Abstract Recently, distributed generators (DGs) have been widely integrated into distribution network, so that the distribution network is gradually transforming into an active distribution network (ADN). Due to the influence of meteorological conditions, the output of DGs has high uncertainty. At the same time, considering the increasing variety of loads in ADNs, the uncertainty of load demand of user side is also increasing. In order to fully consider the uncertainty of measurement and quantitatively evaluate the operational status, this paper proposes a steady‐state analysis method for ADNs under uncertain conditions. Firstly, this paper proposes a steady‐state analysis method including power flow analysis model and evaluation indicators for the operation status from the perspectives of node and network. Secondly, the uncertainty factors are elaborated from three aspects: sources, impact on evaluation index and impact on scheduling. The evaluation indicators considering uncertain conditions, the impact on system security and scheduling of network are further discussed. Finally, through the simulation analysis of the modified IEEE 33‐node test system, the effectiveness of the proposed method is verified.

As’ad Zakaria, Chengyan Duan, Sasa Z. Djokic

Abstract The ongoing electrification of road transportation sector, which is expected to continue to strongly increase over the next years, will result in the connection of a significant number of electric vehicle (EV) chargers in LV and MV distribution networks, particularly in residential applications with on‐board (“slow”) EV chargers. In order to evaluate loading limits of existing distribution networks for the maximum number of EV chargers that can be safely connected (commonly denoted as a network EV “hosting capacity”, HC), this paper introduces a general approach to determine one commonly used network design parameter (after‐diversity maximum demand, ADMD) and one new parameter (maximum daily energy demand, MDED), which are both obtained from the load profiles of maximum per‐hour demands for uncontrolled residential EV charging. The presented approach uses actual EV charging data from the UK as the inputs in Monte Carlo simulations to generate daily EV charging profiles for arbitrary numbers of EVs, enabling to identify related ADMD, MDED and per‐hour maximum demand values, as well as their seasonal variations. The assessed ADMD, MDED and hourly maximum EV charging demands for uncontrolled EV charging are then combined with available UK residential daily load profiles before the EVs are connected (“pre‐EV demands”), where their combined coincidental and noncoincidental maximum demands are evaluated against the static thermal rating (STR) and dynamic thermal rating (DTR) loading limits of network components (transformers and overhead lines), taking into account relevant weather/ambient conditions. This is denoted as a network HC for uncontrolled EV charging. Finally, evaluating the resulting per‐hour maximum demand values against the STR and DTR loading limits and MDED values allows to select one particular scheduling method for controlled EV charging, which gives the absolute maximum number of EVs that can be safely connected in the considered network, that is, maximum network HC for fully controlled EV charging. The presented approach is illustrated on the example of the IEEE 33‐bus test network (modelled using typical UK network components), for the pre‐EV residential demands taken from the recordings at a UK MV substation, and for ambient data taken from a UK Met Office weather station. Obtained results allow to evaluate the range of network EV HC values for uncontrolled and controlled EV charging, that is, lower and upper HC limits, which can be correlated with the commonly used allocations of the firm and non‐firm network HC, respectively.

Nien‐Che Yang, Song‐Ting Zeng

Abstract This study proposes a direct ZBUS three‐phase four‐wire power flow method to accurately analyse the neutral line and multiple grounding characteristics. In particular, the proposed grounding impedance building‐based solution method was used to analyse the neutral grounding impedance in power flow studies based on the slack bus grounding impedance. The accuracy of the proposed method was verified using a neutral‐to‐earth voltage test system. IEEE 13‐bus and 123‐bus test systems were used to compare the advantages and disadvantages of the proposed method. Compared to the current injection full Newton and forward–backward sweep methods, the proposed method achieves a significant reduction in iteration numbers of up to 76.92% and 77.78%, respectively. For different grounding scenarios, stable convergence characteristics were exhibited by the proposed method after six to seven iterations.

Faeze Mohajer, Hossein Kazemi Kargar, Ahmad Salemnia et al.

Photovoltaic (PV) power plants include several parallel and series units. PV uncertainty due to scheduled or forced outages of these units affects the coordination of overcurrent relays (OCRs) and may violate the optimization constraint. This paper proposes a novel hybrid method to solve the selectivity problem of overcurrent relays due to photovoltaic power plant uncertainty. The proposed technique exploits K-medoids and interval linear programming (ILP) to provide setting groups (SGs). The recommended method not only maintains relay coordination for all PV generation scenarios, but also optimizes their operating time. In addition, this method can also be applied to the uncertainties caused by the synchronous distribution generation (DG) unit, which is verified in the studied networks. This research has been tested on the IEEE 8-bus and IEEE 30-bus distribution systems and the superiority of the proposed method in solving the selectivity problem and relay trip time optimization is demonstrated by the simulation results.

Paweł Albrechtowicz

Ravindra Kumar, Manoj Tripathy

Tao Zheng, Haoyu Tian, Lingkun Meng

Abstract Shunt reactor with auxiliary windings (SRAW) can compensate inductive reactive power for long‐distance transmission lines and supply steady power for low‐voltage devices on offshore platforms. The operation characteristics of SRAW can be commonly described by the air‐core transformer equivalent model. However, this model can only make an approximate simulation of the external characteristics of SRAW, and cannot reflect the actual electrical features inside the SRAW. To solve this problem, the authors propose a three‐segment magnetic circuit equivalent model (TMCEM) of SRAW based on the magnetic circuit decomposition method. This model can accurately describe the coupling relationship inside SRAW and can be used for the analysis of internal fault characteristics. Furthermore, through the fault analysis utilizing TMCEM, a novel protection scheme of SRAW based on virtual magnetizing differential current is proposed for the detection of the inner‐turn fault in SRAW. This protection scheme has high sensitivity and can effectively identify the inner‐turn faults without measuring voltages. By testing the physical model of SRAW, the effectiveness of the TMCEM and the proposed protection scheme against inner‐turn fault has been confirmed.

Zhongxue Chang, Chenhao Zhang, Bowen Chen et al.

Abstract The existing relay protections for line‐commutated converter (LCC)‐ultra high voltage DC (UHVDC) transmission lines are insufficient in protection sensitivity and operation speed. The travelling wavefront fault distance information can be used to improve protection performance, which has been used in protection of voltage source converter ‐high voltage DC (HVDC) transmission lines. The adaptability of travelling wavefront protection in LCC‐UHVDC transmission line is analyzed in this paper. First, the conditions that need to be met for the travelling wavefront protections to be able to effectively recognize faults are analyzed. Eight applicability conditions of wavefront protection are revealed from the perspective of travelling wavefront generation and practical application requirements. Then the degree of match between the applicability conditions and the conditions of LCC‐UHVDC system is analyzed as a basis for assessing the adaptability of travelling wavefront protection in the LCC‐UHVDC system. It is pointed out that the index coefficient‐based wavefront protections are not available for LCC‐UHVDC transmission lines since the hardware sampling rate of protection device is insufficient, while first peak time of transient voltage (FPTV)‐based wavefront protection is available for LCC‐UHVDC transmission lines if it has enough anti‐noise ability. Finally, an enhanced anti‐noise algorithm is proposed for the FPTV‐based travelling wavefront protection. The adaptability of the travelling wavefront protection is verified by hardware‐in‐the‐loop test and filed recording experimental data.

Ali Maroufi, Mohammadamin Mobtahej, Mazaher Karimi et al.

Abstract Technically, residential energy management systems are fundamental sectors in the smart grids for implementing demand response programs in the layer of households for managing energy consumption and reducing energy bills. The paper proposes a novel energy management scheme that takes production and usage into account based on a heuristic searching operation. In addition to modelling the grid, renewable energy sources, batteries, and electric vehicles, various kinds of electrical and thermal devices have been examined, including air conditioners, water heaters, vacuum cleaners etc. A method is developed for solving the objective constraint issue in a smart home in order to reduce energy consumption and determine feasible operation states among the various loads. Moreover, this paper proposes a grey wolf optimization method for solving the issue over a longer simulation period. Various cases were examined to evaluate the effectiveness of this suggested robust optimization algorithm. The outcomes show that the suggested model could not only reduce energy costs significantly but has also shown good performance for energy management purposes.

Chengzhi Wei, Chunming Tu, An Wen et al.

Abstract The fault of the tie line between the photovoltaic (PV) station and the grid is a serious fault for the PV station. It will cause the PV station to operate into an unintentional island. The uncontrolled Island voltage and frequency will inevitably lead to the disconnection of the inverter in the station. This situation will bring great losses to PV operators and impact to the power grid. In order to deal with the tie line fault, this paper analyzes the operation characteristics of PV stations in case of tie line fault firstly. Then a tie line fault ride‐through method based on cooperative strategy of small capacity energy storage (ES), relay protection and PV inverters is proposed. The islanding switching control strategies of PV and ES are designed respectively. The cooperative strategy of protection, PV controller and ES controller is formulated as well. The real‐time digital simulator (RTDS) closed‐loop test platform including line protection device, ES controller and PV controller is built to verify the effectiveness of the proposed method.

Waleed Alabri, Dilan Jayaweera

Abstract Increased integration of photovoltaics (PVs) systems and charging stations for electric vehicles (EVs) has led to a substantial increase in the level of voltage unbalance beyond the acceptable limit. Ordinary voltage regulation devices such as on‐load tap changers (OLTCs) and distribution static synchronous compensator (DSTATCOM) are sometimes incapable of adequately addressing this issue without proper coordination with PVs and EVs. This paper presents a novel real‐time optimal coordination scheme to determine the tap position of OLTC, the amount of reactive power to be exchanged by DSTATCOM and a PV inverter, and the phase connection of EVs. The proposed scheme aims to maintain the voltage magnitude and voltage unbalance within the statutory limit while minimising the power losses in an active unbalanced power distribution system. Advanced and hybrid particle swarm optimisation (AHPSO) algorithm is also developed to solve the optimisation problem, and its robustness in comparison with other techniques is verified. The impact of uncoordinated voltage control and proposed control on voltage unbalance and power losses are investigated. Time‐series simulations confirm the significance and scalability of the developed coordination control scheme on IEEE 37‐node and IEEE 123‐node test feeders with real data and different PV penetration levels.

Hasan Ebrahimi, Saeed Rezaeian‐Marjani, Sadjad Galvani et al.

Abstract Renewable energies have a significant portion in supplying energy demands in modern distribution networks. Due to the wide use of power electronic devices, these networks may have power quality problems. The unpredictable nature of renewable energies, besides the effect of non‐linear loads brings out serious planning and operating challenges for distribution systems. Basicly, harmonic distortion is a severe problem for both electric efficiency and power energy customers. This study proposes an optimal scheduling strategy for wind turbine's integrated distribution networks with non‐linear loads using a multi‐objective individualized instruction mechanism teaching‐learning‐based optimization algorithm and the best solution is selected via the TOPSIS technique. In the proposed strategy, energy storage systems are optimally scheduled besides wind turbines, and reactive power compensators. Also, to use the distribution network more efficiently, an optimal network reconfiguration is applied. The wind turbine's output and load demands have probabilistic nature. The proposed scheme reduces the total harmonic distortion as well as total costs. The efficacy of the proposed management scheme is investigated using the IEEE standard 33 bus distribution network. Also, the performance of the multi‐objective individualized instruction mechanism teaching‐learning‐based optimization algorithm is compared with the multi‐objective particle swarm optimization algorithm.

Mehdi Veisi, Farid Adabi, Abdollah Kavousi‐Fard et al.

Abstract This article proposes a novel comprehensive multi‐layer power management system (PMS) along with its smart distribution network (SDN) constraints as bi‐level optimization to address the participation of multi‐microgrids (MMGs) in day‐ahead energy and ancillary services markets. In the first layer of the proposed model, optimal programming of MMG‐connected SDN is considered, in which Microgrids (MGs) participation in the markets is performed to bidirectionally coordinate sources and active loads along with the operator of MGs. In the second layer, the bidirectional coordination of operators of MGs and SDN, that is PMS, is executed in which energy loss, voltage security, and expected energy not‐supplied (EENS) are minimized as weighted sum functions. The problem of the difference between costs and revenues of MGs in markets is minimized subject to constraints of linearized AC‐power flow, reliability, security, and flexibility of the MGs. To obtain a single‐level model, the Karush–Kuhn–Tucker method is applied, and a hybrid stochastic‐robust programming is implemented to model uncertainties associated with the load, renewable power, energy price, mobile storage energy demand, and network equipment accessibility. The contributions of this paper include the simultaneous modelling of several economic indicators, multi‐layer energy management modelling, and stochastic mixed modelling of uncertainties. The efficiency of this method is validated by simultaneously evaluating the optimum condition of technical and economic indices of several SDNs and MGs. Flexibility of 0.022 MW is obtained for the proposed scheme, which is close to zero (100% flexibility). The voltage security index is increased to 22 by the mentioned scheme, which is close to its normal value, that is, 24. The voltage deviation is below 0.07 p.u. Energy losses are reduced by about 30% compared with that in power flow studies, and the EENS reaches roughly 3 MWh, that is, close to zero (100% reliability).