Iet Generation Transmission & Distribution最新文献

Z. Yin, R. Zhu, S. Cui, et al., “Optimisation Scheduling of Integrated Electricity-Heat-Oxygen Energy Systems Considering Demand Response and Carbon Trading Based on IGDT,” IET Generation, Transmission & Distribution 19, no. 1 (2025): e70126.

In the ‘Funding/Acknowledgements’ section, the text ‘Tibet Agriculture and Animal Husbandry College (YJS2025-42)’ was incorrect. This should have read: ‘Graduate Education Innovation Program Funding Project of Tibet Agriculture and Animal Husbandry University (YJS2025-42).’

We apologize for this error.

Switching operations in power transmission lines can cause travelling waves on the lines, generating transient overvoltages. The magnitude of these overvoltages depends on the power system voltage magnitude at the closing time and the trapped charge on the line. Surge arresters protect the energy equipment inside substations against the line overvoltages. The number of surge arrester operations is counted by the surge arrester counter. This article focuses on evaluating surge arrester performance in the transmission line switching. For this purpose, a 400 kV power transmission line in Iran is simulated using EMTP-RV software. Then, the probability of operation of the surge arrester counter is obtained using statistical switching. Comparing the recorded practical results by the surge arrester counter with the simulation results demonstrated that accurate simulation of the surge arrester performance requires modelling the corona in transmission lines. In addition, the impact of the transmission line structure on the performance of surge arresters is investigated. The simulation results indicate that if corona is taken into account in the modelling, the probability of counting by the surge arrester counter decreases from 98.6% to 4%. This result aligns with what has been observed in practice.

RETRACTION: S. Pirouzi, “Network-constrained Unit Commitment-based Virtual Power Plant Model in the Day-ahead Market According to Energy Management Strategy,” IET Gener. Transm. Distrib, no. 17, (2023): 4958–4974, https://doi.org/10.1049/gtd2.13008.

The above article, published online on 9^th October 2023 in Wiley Online Library (wileyonlinelibrary.com), has been retracted by agreement between the journal's Editors-in-Chief; Christian Rehtanz and Federico Milano; the Institution of Engineering and Technology; and John Wiley & Sons Ltd.

The retraction has been agreed due to concerns raised by a third party regarding the presence of a paragraph with multiple irrelevant citations in this article. When the author was asked to clarify these concerns, they did not address them adequately. Furthermore, the paragraph that contains multiple irrelevant citations, is a textual reproduction from multiple other manuscripts published by different author groups. Accordingly, we cannot vouch for the integrity or reliability of the content and have taken the decision to retract the article. The author has been informed of the decision to retract the article, and they disagree with the retraction.

The large-scale access of renewable power generation, the prosperity of the carbon market and distributed power generation trading market, and the influx of capital into the power market have created a context in which micro-frid (MGs) can be seen as a key technology for promoting renewable energy consumption. In this context, it is likely that multiple MGs will participate in the market. In light of the inherent unpredictability of wind power and other clean energy sources within each MG, a multi MG s electricity-carbon joint optimization operation method that considers robust market clearing is proposed. This method ensures the economic viability of the multi- MG s alliance while adhering to the principles of low-carbon operations and security. The constructed model comprises two layers. The upper layer establishes a robust clearing model of the upper-level electricity-carbon joint market with optimal accruals and benefits based on the marginal pricing theory. The lower layer considers the coupling of electricity-carbon joint trading, establishes a multi- MG s low-carbon joint optimization model based on the Nash negotiation theory, and proposes an electricity-carbon revenue allocation method based on the contribution degree of the interaction products to realize the reasonable allocation of the revenue of each MG. In conclusion, the accelerated-adaptive alternating direction multiplier method (AA-ADMM) is put forth as a means of solving the model. The results of the illustrative example serve to corroborate the efficacy of the methodology proposed in this paper.

Power systems must address increasingly severe environmental challenges through an efficient low-carbon transition. However, most current studies considered different single technology to achieve this transition. Research on the interactive mechanisms between different carbon reduction measures remains limited. This paper proposes a capacity expansion planning model for a low-carbon power system that integrates multiple technologies, incorporating two complementary types of carbon reduction measures. Specifically, the technologies are categorized into two categories: direct CO₂ reduction measures (e.g., carbon capture and storage) and indirect CO₂ reduction measures (e.g., flexibility retrofit, energy storage system and wind expansion). Furthermore, a distributionally robust optimization method is developed to address the uncertainty of wind power. The column and constraint generation algorithm is employed to solve the model and derive the optimal planning scheme. Case studies based on the modified IEEE 24-bus system and the IEEE 118-bus system indicate that the proposed method significantly reduces both the system cost and carbon emissions. Additionally, the planning results demonstrate effective synergy between direct and indirect carbon reduction measures.

Voltage Source Converter-based Energy Storage System (VSC-ESS) integration face technological obstacles like active power oscillations during the frequency regulation process for power system frequency management. Such problems are more prominent in parallel VSC-ESS. To address this, this paper introduces a transient electromagnetic power compensation control strategy for parallel VSC-ESS to suppress the overshooting and oscillations during the frequency response. First, a comprehensive investigation of the state-space equations and transfer functions for parallelled VSC-ESS elucidates the influence of key control parameters on both system stability and frequency response characteristics. Then, in order to improve the dynamic response performance, an adaptive inertia control approach is devised. Simulation and experimental results verify the effectiveness and feasibility of the proposed control.

The rapid advancement of smart distribution systems, driven by the integration of distributed energy resources, intelligent switching devices and communication-based control, has considerably increased the complexity of reliability assessment. Traditional evaluation methods, relying on predefined fault cases, iterative simulations, or heuristic techniques, often suffer from scalability challenges and computational burden. To address these limitations, this study presents a generalized, non-iterative analytical framework grounded in graph-theoretic principles. Building upon Lemma 1, which restates the classical reachability property of graph theory, where the n-th power of the adjacency matrix represents node connectivity, the method systematically identifies isolated nodes under diverse network topologies. Building upon this foundation, a fast distribution reliability calculator is developed and linked to each load point, enabling efficient calculation of reliability indices without extensive simulations. Unlike conventional approaches, the proposed framework inherently incorporates realistic modelling of key system elements, such as disconnectors, circuit breakers, remotely operated switches and distributed generation units. Its effectiveness is demonstrated on two networks, including Bus 6 of the 65-bus Roy Billinton test system and a real 778-node feeder located in Khorasan Razavi Province, Iran, where the results confirm superior accuracy and computational efficiency. Overall, the method offers a scalable and robust solution for evaluating the reliability and resilience of modern distribution networks.

Multiterminal offshore high-voltage direct current systems provide a suitable option for efficient and reliable power transfer to shore for future offshore generation. To limit loss of power transmission, protection systems based on DC circuit breakers (DCCBs) are envisioned. In case of grid-following wind turbine generators (WTG), DCCBs require large series reactors to avoid blocking of the offshore converter and subsequent shutdown of the offshore wind farm. By contrast, the potential of grid-forming WTG to ride through converter blocking during DC-side faults has not been investigated yet. Therefore, this paper compares four variations of WTG and HVDC converter control through detailed electromagnetic transient simulations of DC-side fault scenarios. It highlights that grid-forming WTG keep the offshore system in stable operation during temporary blocking of the offshore converter. Moreover, the paper shows that protection requirements can be reduced through the use of smaller DC series reactors. During temporary blocking, DC and offshore AC-fault-ride-through requirements are met but the AC power transfer to the onshore system is interrupted. Therefore, the temporary blocking time has to be chosen to adhere to current grid codes, with the active power return being dependent on the WTG. Already short blocking times of 10 ms can significantly reduce the inductance. However, that requires the fast deblocking to be in accordance with the internal protection mechanisms of the converter.

The growing penetration of renewable energy sources has played a significant role in power markets, necessitating the need to address the stochasticity arising from these sources. This paper introduces a distributionally robust chance-constrained market design to internalise uncertainty and strike a balance between economic efficiency and operational reliability. Three different moment-based ambiguity sets are leveraged to account for wind power uncertainty. We demonstrate that the proposed economic dispatch model under various uncertainty assumptions can be transformed into a second-order cone programming problem. Therefore, the uncertainty-contained electricity prices are accurately derived. In addition, we prove that the suggested pricing mechanism constitutes a robust competitive equilibrium under certain conditions. Finally, the effectiveness of the proposed approach is assessed on the Pennsylvania–New Jersey–Maryland Interconnection 5-bus system and the Institute of Electrical and Electronics Engineers 118-bus test system.

This study introduces a forecasting-driven framework for solving the hybrid dynamic economic emission dispatch (HDEED) problem with uncertain wind and solar generation. Unlike conventional approaches that rely on probabilistic models, this research uses data-driven forecasting techniques to predict the output powers of wind and PV plants and uses them in the multi-objective optimisation algorithm to minimise costs and emissions. An arithmetic optimiser with a sine cosine assisted driving training-based optimisation algorithm (AOASC-DTBO) is presented to solve various single and multi-objective HDEED problems based on fuzzy decision-making and the Pareto dominance concept. The proposed dispatching algorithm is validated using 10-unit, 40-unit and 7-unit IEEE 57 bus systems. The results revealed that the AOASC-DTBO algorithm achieved 8.73% and 4.95% lower fuel costs when compared with the PSO and DTBO algorithms, respectively. In addition, the emissions were 6.47% and 2.25% lower than the BMO and DTBO algorithms, respectively. The work highlights the importance of integrating renewable energy sources (RES) into power systems to achieve cost savings and reduced emissions, while also emphasising the need for efficient dispatch algorithms to ensure grid stability and reliability. The results demonstrate that integrating RES into the power system can yield substantial economic and environmental benefits, achieving cost savings of up to $6,908.034 and reducing emissions by 13,233.691 tonnes per day.