IET Energy Systems Integration最新文献

In recent decades, global power grids have evolved with a rapid and extensive development of power electronic converters (PEC), including renewable energy systems (RES), high-voltage DC (HVDC) transmission, flexible AC transmission system (FACTS), energy storages, and microgrids. The distinct characteristics of power electronic devices traditional synchronous generators, especially their rapid control speed, wide-band performance and lack of inertia response and spinning reserve, are altering grid dynamics, and inducing new stability challenges. Continuation of such trends could further exacerbate the risk to the stability of power grids because of factors such as low inertias, lack of spinning reserve to quickly nullify active power mismatch between demand and supply.

Therefore, scientific investigations on novel dynamic modelling and stability analysis methods, data-driven monitoring and situation awareness on grid inertia-power-frequency evolution, grid dynamic frequency forecast methodologies in consideration of novel PEC control schemes, and advanced PEC grid integration control schemes to minimise frequency management risks become increasingly crucial for the secured operations of power systems with high PEC penetrations. In this Special Issue, namely ‘Dynamic Analysis, Control, and Situation Awareness of Power Systems with High Penetrations of Power Electronic Converters’, we have presented eight original papers of sufficient quality and innovation. The 10 eventually accepted papers can be clustered into three two categories, namely novel control design, stability and fault analysis.

Zhu et al. present a supercapacitor-based coordinated synthetic inertia (SCSI) scheme for a voltage source converter-based HVDC (VSC-HVDC) integrated offshore wind farm (OWF). The proposed SCSI allows the OWF to provide a designated inertial response to an onshore grid. The results show that the proposed SCSI scheme can provide required inertial support from WTG-installed supercapacitors to the onshore grid through the VSC-HVDC link, significantly improving the onshore frequency stability (https://doi.org/10.1049/esi2.12137).

Ghamari et al. design a Lyapunov-based adaptive backstepping control approach for a power Buck converter, as an advanced version of the Backstepping method utilising Lyapunov stability function to reach a higher stability and a better disturbance rejection behaviour in the practical applications. In addition, to compensate for disturbances with wider ranges such as supply voltage variation, parametric variation and noise, this paper applies a metaheuristic algorithm in the control scheme called grey wolf optimisation algorithm of a nature-inspired algorithm with faster decision-making dynamics along with more accuracy over different optimisation algorithms (https://doi.org/10.1049/esi2.12098).

Arunagiri et al. present a new technique based on active damped dual loop αβ-frame curr

Having correct distribution network topology information is essential for system state estimation, line loss analysis, electricity theft detection and fault location. At present, with continuous deployment of smart sensors, a large amount of monitoring data is collected, which enables refined management for distribution network. A data-driven low voltage (LV) distribution network topology identification method is proposed, which realises transformer-customer pairing and customer phase identification for distribution network with relatively balanced power supplies. Firstly, an integrated similarity coefficient of voltage curve is proposed, which can reflect the neighbourhood relationship within stations while increase the distinction between stations; the K-Nearest Neighbour (KNN) algorithm is used to propagate the service transformer labels to complete transformer-customer association. Then, the influence of power fluctuation on voltage curve is analysed and a dynamic sliding window model is adopted to search for voltage segments with significantly difference among three phase feeders to formulate a voltage time series to identify customer phase. Finally, the results are corrected and verified based on the principle of network power balance. The proposed algorithm is tested in two different real substations in China and Europe and shows high accuracy and robustness especially in distribution network with relatively balanced power supplies.

Grid-connected voltage source converters (VSCs) have been broadly applied in modern power system. However, instability issues may be triggered by the integration of grid-connected VSCs, jeopardising the operation of the power grid. Conventional stability analysis methods can be utilised to derive system stability margins under nominal conditions. Whereas grid-connected VSCs inevitably operate under multiparameter uncertainty, which may result in overly optimistic or even incorrect estimations of stability margins, thereby posing potential risks to system operation. To address this issue, an interval small-signal stability analysis approach is proposed to investigate the system stability under multiparameter uncertainty. First, the interval state-space model of the grid-connected VSC system is constructed based on interval symbolic linearisation. Furthermore, the interval eigenvalue decomposition is introduced to calculate the interval eigenvalue distribution of the interval state-space model. Eventually, the upper bounds of the real part of the dominant interval eigenvalues are utilised for deriving interval stable parameter regions. Results of Monte Carlo analysis and time-domain simulations of the grid-connected VSC system are utilised to verify the effectiveness of the proposed interval stability analysis method.

The trend of global energy systems towards carbon neutrality has led to an escalating interdependency between electricity, hydrogen fuel, and transportation networks. However, the means of surmounting the many challenges confronting the optimal coupling and coordination of electric power, hydrogen fuel, and transportation systems are not sufficiently understood to guide modern infrastructure planning operations. The present work addresses this issue by surveying the extant literature, relevant government policies, and future development trends to evaluate the present state of technology available for coordinating these systems and then determine the most pressing issues that remain to be addressed to facilitate future trends. On the one hand, the users of transportation networks represent flexible consumers of electric power and hydrogen fuel for those connected via devices such as electric vehicles and hydrogen fuel cell vehicles through charging stations and hydrogen refuelling stations. On the other hand, power grids can mitigate the negative effect of random charging behaviours on grid security through time-of-use electricity pricing, while excess renewable energy outputs can be applied to generate hydrogen fuel. The findings of this overview offer support for infrastructure planning and operations. Finally, the most urgent issues requiring further research are summarised.