Iet Generation Transmission & Distribution最新文献

The aggregation models of renewable energy power stations are difficult to apply to the stability research of the fault inside the station or the oscillation analysis between the station and the grid-side system, and the high dimensional characteristics of their detailed model will pose an enormous challenge to the simulation efficiency. To alleviate the contradiction between accuracy and efficiency, this paper proposes a state-variable-preserving method to efficiently model inverter-based resources and a node tearing method to realize parallel simulation of the renewable energy power station consisting of inverter-based resources. The state-variable-preserving model uses discrete state space expression to eliminate the internal nodes on the basis of preserving the original variables of the generation unit and reduces the solving scale of the generation station. The node tearing method reduces the solving complexity of the associated variables, which is more consistent with the topology characteristic that different power generation clusters are interconnected by the same bus. In the case study, the results of numerical accuracy analysis and numerical stability analysis of a photovoltaic power plant verify the reliability of the proposed method, and its simulation efficiency is verified by changing the scale of the photovoltaic power plant.

According to the constraints of frequency safety indices, evaluating the inertia and primary frequency regulation demand, rationally utilizing the energy reserve provided by wind turbines and energy storage devices to ensure the safety of the system frequency response, is the key to improve the stability of large-scale new energy power systems. First, frequency response characteristics and frequency regulation safety indicators required by new energy generation systems were analyzed. Second, the frequency dynamic response model of the system with wind power and energy storage was established, and the extreme value time for the virtual inertia response of the system was calculated. Using the extreme time at which the frequency drop is maximum, the virtual inertia time constant of the wind-storage system was evaluated. Additionally, the system inertia and the primary frequency regulation demand were obtained considering the frequency safety indices, and a novel coordinated control strategy for wind power and energy storage to provide the required frequency support was proposed. Finally, a grid-connected wind-storage simulation system was built to verify the superiority of the proposed control strategy. The obtained results indicate that the proposed control scheme flexibly meets the system frequency safety requirements.

Aiming at the problem of increased complexity in broadband oscillations caused by the introduction of virtual synchronous generator (VSG) control to grid-forming and grid-following grid-connected converters interacting with inductive weak grids, positive and negative sequence impedance of such converters is established under small perturbations in phase angle and voltage using harmonic linearization. The impact of various control links on the broadband impedance characteristics associated with different control strategies is then analysed. It is observed that the grid-forming converter equipped with VSG demonstrates lower impedance magnitude and inductive behaviour in the medium-to-high frequency range, thus emulating the external behaviour of a synchronous generator more accurately. Furthermore, the analysis based on the maximum peak Nyquist stability criterion reveals that voltage control and current-type VSG lack phase margin, leading to potential oscillation risks within their respective dominant frequency bands. Finally, the validity of the broadband oscillation mechanism analysis is confirmed through hardware-in-loop experiments and impedance sweep analyses.

The inherent intermittency and fluctuation of renewable energy generation introduce uncertainty in electricity carbon emission intensity, posing challenges to the low-carbon and economic scheduling of integrated energy systems. To this end, this paper proposes an optimization model for integrated electricity-heat-gas energy system operation considering uncertain indirect carbon emission intensity. First, considering the tiered carbon trading mechanism, an optimization framework for a park-level model is developed. Then, polyhedral uncertainty sets are introduced to capture the uncertainties in renewable energy generation and carbon emission intensity, offering a flexible and intuitive approach to handling diverse uncertainty types. These uncertainty sets are integrated into the optimization problem to enhance robustness. Finally, the uncertainty set-based stochastic optimization method is introduced to improve the model's robustness, addressing both cost minimization and carbon reduction under uncertain conditions. Case studies using data from a Mediterranean-region hospital demonstrate the model's effectiveness in addressing uncertainties at park-level systems and providing robust solutions that balance cost efficiency and environmental impact.

The emergence of multi-agent systems and significant integration of distributed energy sources (DESs) are transforming distribution networks. This necessitates a decentralized management strategy for unbalanced operation in multi-agent distribution systems (MADSs) due to the autonomous nature and potential for unbalanced injection of single-phase DESs. Accordingly, this paper proposes a novel approach for decentralized management of unbalanced operation in MADSs. The approach leverages a customized alternating direction method of multipliers to facilitate decentralized decision-making, while incorporating transactive energy signals aligned with the alternating direction method of multiplier framework to enable independent agent operation. In this scheme, independent agents would optimize their operating costs considering the announced transactive signals, which model the power prices and power loss in the grid. The decentralized structure enables agents to apply stochastic and condition value at risk methods to address the uncertainty and associated risk in scheduling resources. Furthermore, without violating the privacy concerns of agents, the developed transactive-based scheme facilitates minimizing the asymmetrical condition, caused by the unbalanced integration of DESs, in the power request at the connection point of MADSs and transmission networks. Finally, the proposed methodology is simulated on 37-bus and 123-bus test-systems to study its effectiveness in managing the MADSs with unbalanced integration of DESs.

Renewable energy sources are getting integrated into the electrical power network since many years. The characteristics of these sources are completely different from traditional synchronous generators. This is posing challenges for power engineers from system protection and control perspective. Cases of maloperations of protective relays have been a focus of research across industries and universities. India has been growing in deploying distributed energy resources. Most of the maloperations reported relate to transmission line protection. Studies on maloperation of directional element are not duly addressed from Indian grid perspective. Few cases from India have been chosen for research. Fault data from Type-4 and Type-3 wind plant and solar park has been analysed and compared with literature reports. The objective of this paper is to document the behaviour of directional elements for a distributed energy resource connected system in India. In addition, aim is to understand the gaps from existing research to the behaviours of the current directional protections. This would help in identifying mechanisms to ascertain directionality for similar systems in the future. The conclusion from the paper is that the detection of fault direction must be completed before the time inverter control kicks in to operation in any algorithm.

The previous knowledge of the admittance matrix represents an important issue in power system analysis, specifically regarding load flow, voltage stability, and protection setting. Some parameter estimation techniques in technical literature determine the admittance matrix of electric power grids, leading to notable advances in measurement and monitoring. This paper proposes a robust approach to determine the admittance matrix using deep learning techniques. Throughout the paper, results demonstrate that the proposed approach handles Gaussian and non-Gaussian noise reliably, outperforming other works in the technical literature. This paper also evaluates the proposed method in several scenarios, including different numbers of samples and varying noise level, as well as loads with non-linear variations. The proposed method has low computational complexity because it considers only a few features while estimating admittance parameters. Results demonstrate that the proposed approach sustains accuracy and robustness, even when subjected to high noise levels in the measurements. This paper evaluates the proposed approach by estimating the parameters of the IEEE 14-bus and 57-bus systems and presents the performance of all parameters for the 14-bus system.

The study optimizes the placement of electric vehicle charging stations (EVCSs), photovoltaic power plants (PVPPs), wind turbine power plants (WTPPs), battery energy storage system (BESS), and capacitor bank (CB), considering AC and DC chargers for the EVCSs by using the wave search algorithm (WSA), particle swarm optimization (PSO) algorithm, artificial bee colony (ABC) algorithm, and salp swarm algorithm (SSA). The objective is to minimize the sum of the cost of electric energy supplied by the grid and the total costs from the added electric components for a 15-year project, including investment cost, operation, and maintenance (O&M) cost. Finally, WSA can reach a smaller total cost than others. The hybrid system with all the components costs 21.83% less than the base system for a 15-year project life cycle. The total revenue and investment and O&M costs are about $15.3 million and $11.3 million. So, the total profit is about $4 million, equivalent to 35.38%. Furthermore, the smallest voltage is increased from about 0.91 to 0.96 pu, and the highest branch current is reduced from about 387 to 329 A, meeting 45.54% of the total consumption in the system. Thus, the integration of the EVCSs, PVPPs, WTPPs, BESS, and CB into distribution power networks can bring a very high profit.

The proliferation in electric vehicle (EV) adoption has necessitated the rapid development of EV charging stations (EVCSs). Given their susceptibility to lightning strikes, it is crucial to guarantee the dependability and security of these stations. This research investigates the impact of lightning on EVCSs, focusing on the critical role of grounding systems. By simulating various lightning strike scenarios, the study examines the influence of factors such as grounding configuration, cable shielding, and lightning current characteristics on the induced overvoltages within EVCS components. The findings contribute to the development of robust lightning protection strategies for EVCSs, enhancing their resilience and ensuring the safe operation of EVs.

The increasing deployment of offshore wind farms necessitates robust and stable high-voltage direct current networks. Achieving optimal stability, especially in damping oscillations on the DC side, remains a significant challenge. This study focuses on mitigating post-fault converter de-blocking oscillations, a critical issue exacerbated by complex interactions between AC and DC systems, converter dynamics, and system faults. These behavior are governed by nonlinear system dynamics, making traditional control methods less effective in ensuring stability. A comprehensive analysis of DC side oscillations and their interaction with converter dynamics is developed to understand the key factors influencing system stability. The research investigates a DC voltage regulation damping approach, identified as the most effective solution in the literature. Comprehensive parametric sensitivity analysis evaluates system behavior under diverse operational conditions. Addressing current damping method limitations during converter de-blocking, this work proposes an innovative control approach integrating fuzzy logic control and proportional–integral controllers. This approach enhances DC voltage regulation and incorporates a modified circulating current suppression control in the inner loop. The coordinated fuzzy logic control and proportional–integral controller dynamically adjusts to nonlinear system dynamics in real-time, providing a robust framework for improved post-fault recovery. It aims to achieve faster recovery times and reduced overshoot compared to conventional methods. The proposed controller's efficacy is validated through comparative analysis with existing approaches. Electromagnetic transient) simulations using the real-time digital simulator platform demonstrate the controller's performance under realistic operating conditions.