IET Energy Systems Integration最新文献

The presented work operated a PIPO Current fed front end converter-based solid-state transformer (SST) for maximum power point tracking (MPPT) and voltage boost operation in medium power range PV applications. The proposed system employed the perturb and observe (P&O)-based MPPT technique and upheld the ZVS and ZCS operations of all primary side switches and secondary side rectifier diodes, respectively. The proposed system introduced a new fundamental extractor titled ‘Pre-filter double fundamental signal extractor (DFSE) based multi-layered DFSE (p-DFSE-MDFSE)’ and utilised it in the grid controller for synchronisation and harmonics mitigation operation. The primary goal was to achieve a compact size, reduced weight and cheaper magnetic component-based front-end converter of SST on the PV array side and a fast, secure and trustworthy mitigation control of current harmonics on the utility grid side. The proposed system was inspected on the OPAL-RT (RT-LABv2021.3.2.307) platform for various grid anomalies, and its conduct was found to be well within the IEEE 519 norms.

Effective use of the energy stored within thermal energy storage systems requires mathematical models that faithfully represent the dynamics of interest. Although three-dimensional or two-dimensional models may provide an accurate representation of the thermal store, these are computationally intensive and may not be suitable for control system design or to simulate complex networks. Following this line, a low-order one-dimensional model of a latent heat thermal store is presented. The model is based on energy balance, the specific heat–temperature curve of the storage medium, and the dynamic calculation of the heat transfer coefficient. The simplicity afforded by the model facilitates its implementation in any programming language, guaranteeing its compatibility with commercial software to simulate complex systems. The model was implemented in MATLAB/Simulink and verified against experimental data of the real unit and simulation results obtained with a two-dimensional model. Simulation results for charging and discharging operations obtained with the one-dimensional model exhibit a root mean square error of ≤0.53 °C and a mean square error of ≤0.32 °C when compared with experimental results of the output temperature of the heat transfer fluid. These outcomes are deemed acceptable considering the low order of the one-dimensional model.

The ‘Electric energy substitution’ project in rural areas of northern China aims to replace coal-fired heating with electric heating. However, this could potentially lead to congestion problems on the local distribution networks (DNs) due to an increase in heating loads. Instead of expanding the lines, flexible resources such as microgrids (MGs) and heat pumps (HPs) could provide auxiliary services in a more cost-effective manner. A bi-level optimisation model that coordinates DNs, MGs, and HP clusters is proposed to address this issue. In the lower level, MGs and HP clusters provide auxiliary services through competitive bidding to maximise their own income over multiple periods, considering a series of technical operational constraints and comfort constraints. In the upper level, DNs clear the market based on the bidding information to minimise its operational costs while guaranteeing network constraints. The bi-level optimisation model is formulated as a multi-agent matrix game problem, and the Win or Learn Fast-Policy Hill-climbing algorithm is used to achieve fast market equilibrium in a decentralised manner. Simulation results demonstrate that the proposed method can improve the revenue of MGs by up to 2.6 times compared to the single period matrix game method, and reduce the convergence time by up to 81.3% compared to the multi-agent Q-learning method.

The distribution system is undergoing a transformation into a platform that integrates multiple energy sources, including electricity, gas, and heat, to facilitate point-to-point energy transmission. However, the existing tree radiation structure of the distribution system is inadequate to meet the demand. To address this, this paper proposes the networking structure and operation mode of the honeycomb integrated energy distribution system (HIEDS). Firstly, the paper outlines the network structure of HIEDS, which includes flexible interconnection modes between micro-networks and key equipment, such as the integrated energy stations. Secondly, two typical operation modes of HIEDS with the objectives of operation economy and load balancing are proposed, respectively. Finally, the operation characteristics of HIEDS in different scenarios are analysed through case studies, and HIEDS is compared with other typical interconnection structures of micro-energy networks further. The results demonstrate that HIEDS provides a more flexible energy supply mode, which can improve the operation economy and reliability of the distribution system. This study will provide a theoretical basis for optimising the structure and operation mode of future integrated energy distribution systems.

The current state of the art on emerging and efficient techniques for condition monitoring of permanent magnet (PM) alternating-current (AC) machines deployed in electric vehicle (EV) applications is presented. The discussion includes the most common and specific types of faults in PM motors, such as rotor demagnetisation and stator inter-turn faults, respectively. Fault indicators, such as voltage (v_s) and current (i_s) signals and machine signatures based on motor back electromotive force (EMF) (E_B) and magnetic flux (ϕ), are taken into account as a measuring quantity in diagnosing motor faults. Other signatures, including thermal analysis, acoustic noise, and vibrations, are also illustrated as some of the emerging techniques in estimating the performance of EV motors while under operations. In addition, various fault modelling methods, condition monitoring techniques, and comprehensive approaches applied in diagnosing the effect of machine faults during its incipient stages are illustrated. Since most of the fault diagnostic techniques discussed here include only machine-based quantities as fault indices/indicators, the provided solutions are therefore found to be more reliable and accurate for diagnosing the motor faults. This comprehensive review study is inclusive of the existing fault diagnostic techniques, which are currently employed in industrial and commercial practices, in addition to the new methodologies proposed by the authors. All the given condition monitoring schemes therefore seem significantly vital in estimating the state of health of PM AC machines while under operation in all-electric transportation systems.

The use of natural gas pipeline networks to transmit hydrogen energy is an important form of hydrogen energy utilisation. The coupling of hydrogen-enriched natural gas pipeline network and power grid involves the energy conversion of electricity-hydrogen-electricity, so the assessment is crucial because the system is complex, and the hazards to the system can be identified. This paper proposes a risk assessment method for gas-electric coupling of hydrogen-enriched natural gas pipeline networks and a three-stage risk assessment model to assess the life cycle risk of natural gas pipelines; a material energy-based risk transfer model considering gas-electric coupling is proposed to describe the risk transfer process of hydrogen-enriched natural gas between the gas network and the grid. By comparing and analysing the risk of natural gas blending ratio to the pipeline and the risk of pipeline pressure to the pipeline, the validity of the model is verified, which provides safety support for the connection of the natural gas pipeline system to the grid and ensures the efficient use of hydrogen energy.

The increasing integration of variable renewable energy resources through power electronics has brought about substantial changes in the structure and dynamics of modern power systems. In response to these transformations, there has been a surge in the development of tools and algorithms leveraging real-time computational power to enhance system operation and stability. Data-driven methods have emerged as practical approaches for extracting reliable representations from non-linear system data, enabling the identification of dynamics and system parameters essential for analysing stability and ensuring reliable operation. This study provides a comprehensive review of recent contributions in the literature concerning the application of data-driven identification, analysis, and control methods in various aspects of power system operation. Specifically, the focus is on frequency support, power oscillation detection, and damping, which play crucial roles in maintaining grid stability. By discussing the challenges posed by parametric uncertainties, load and source variability, and reduced system inertia, this review sheds light on the opportunities for future research endeavours.

Air conditioning loads (ACLs) represent an increasing proportion of power system loads, offering significant potential for optimised scheduling and active participation in demand response (DR) programs. While many studies have focused on ON/OFF control schemes that satisfy system requirements, few have addressed quantifying the life loss of ACLs from the user perspective. To address this gap, a quantitative model of ACL life loss is established and an optimal scheduling model is developed for ACLs participating in DR that incorporates the cost of life loss. The relationship between life loss and refrigeration power is a complex non-linear high-order fractional function that cannot be solved by commercial solvers. Therefore, a bi-objective multi-weight optimisation algorithm is proposed with a complex non-linear fraction based on the Dinkelbach algorithm and its feasibility through mathematical examples is verified. Finally, a numerical example based on the IEEE 39-bus test system is provided to demonstrate the feasibility of the model and the effectiveness of the proposed solution method.