• Energy Research

In the context of strong electromagnetic interference environments, the measurement accuracy of the capacitance parameters of transmission lines under power frequency measurement methods is not high. In this paper, a capacitance parameter anti-interference measurement method for transmission lines based on harmonic components is proposed to overcome the impact of power frequency interference. When applying this method, it is first necessary to open-circuit the end of the line under test. Subsequently, apply voltage to the head end of the tested line through a step-up transformer. Due to the saturation of the transformer during no-load conditions, a large number of harmonics are generated, primarily third harmonic. The third harmonic components of voltage and current on the tested transmission line are extracted using the Fourier transform. The proposed method addresses the influence of line distribution effects by establishing a distributed parameter model for long-distance transmission lines. The relevant transmission matrix for the zero-sequence distributed parameters is obtained by combining Laplace transform and similarity transform to solve the transmission line equations. Using synchronous measurement data from the third harmonic components of voltage and current at both ends of the transmission line, combined with the transmission matrix, this method accurately measures the zero-sequence capacitance parameters. The PSCAD/EMTDC simulation results and field test outcomes have demonstrated the feasibility and accuracy of the proposed method for measuring line capacitance parameters under strong electromagnetic interference.

In order to coordinate the economic desire of microgrid (MG) owners and the stability operation requirement of the distribution system operator (DSO), a multi-market participation framework is proposed to stimulate the energy transaction potential of MGs through distributed and centralized ways. Firstly, an MG equipped with storage can contribute to the stability improvement at special nodes of the distribution grid where the uncertain factors (such as intermittent renewable sources and electric vehicles) exist. The DSO is thus interested in encouraging specified MGs to provide voltage stability services by creating a distribution grid service market (DGSM), where the dynamic production-price auction is used to capture the competition of the distributed MGs. Moreover, an aggregator, serving as a broker and controller for MGs, is considered to participate in the day-ahead wholesale market. A Stackelberg game is modeled accordingly to solve the price and quantity package allocation between aggregator and MGs. Finally, the modified IEEE-33 bus distribution test system is used to demonstrate the applicability and effectiveness of the proposed multi-market mechanism. The results under this framework improve both MGs and utility.

In order to improve the dynamic stability of multi-area microgrid (MG) clusters in the autonomous mode, this study proposes a novel fuzzy-based dynamic inertia control strategy for supercapacitors in multi-area autonomous MG clusters. By virtue of the integral manifold theory, the interactive influence of inertia on dynamic stability for multi-area MG clusters is explored in detail. The energy function of multi-area MG clusters is constructed to further analyze the inertia constant. Based on the analysis of the mechanism, a control strategy for the fuzzy-based dynamic inertia control of supercapacitors for multi-area MG clusters is further proposed. For each sub-microgrid (sub-MG), the gain of the fuzzy-based dynamic inertia control is self-tuned dynamically, with system events being triggered, so as to flexibly and robustly enhance the dynamic performance of the multi-area MG clusters in the autonomous mode. To verify the effectiveness of the proposed control scheme, a three-area photovoltaic (PV)-based MG cluster is designed and simulated on the MATLAB/Simulink platform. Moreover, a comparison between the dynamic fuzzy-based inertial control method and an additional droop control method is finally presented to validate the advantages of the fuzzy-based dynamic inertial control approach.

In order to achieve peak carbon and carbon neutrality targets, a high number of distributed power sources have been connected to distribution networks. How to realize the planning of a distribution network containing integrated energy under the condition of carbon capture and complete the exceedance test of the distribution network under the condition of accessing a large number of distributed generators has become an urgent problem. To solve the above problem while promoting sustainable development, this work proposes an active distribution network risk-planning model based on multisource data from carbon capture and the Power Internet of Things. The model calculates the semi-invariants of each order of the node state vectors and branch circuit current vectors and then utilizes Gram–Charlier-level expansion to obtain the exceeding probability density function and the probability distribution functions of the node voltages and line powers in the distribution network. Combined with multisource data, an active distribution network with an integrated energy system designed for carbon capture was modeled. According to the risk scenario of the distribution network, the nonconvex constraints in the model were simplified by second-order cone relaxation, and the optimal planning scheme of the distribution network was solved by combining the Gurobi solver with the risk index as the first-level objective and the economic benefit as the second-level objective. The simulation results of a coupled network consisting of a 39-node distribution network and an 11-node transportation network verified the effectiveness of the proposed model.

Direct current (DC) residential distribution systems (RDS) consisting of DC living homes will be a significant integral part of future green transmission. Meanwhile, the increasing number of distributed resources and intelligent devices will change the power flow between the main grid and the demand side. The utilization of distributed generation (DG) requires an economic operation, stability, and an environmentally friendly approach in the whole DC system. This paper not only presents an optimization schedule and transactive energy (TE) approach through a centralized energy management system (CEMS), but also a control approach to implement and ensure DG output voltages to various DC buses in a DC RDS. Based on data collection, prediction and a certain objectives, the expert system in a CEMS can work out the optimization schedule, after this, the voltage droop control for steady voltage is aligned with the command of the unit power schedule. In this work, a DC RDS is used as a case study to demonstrate the process, the RDS is associated with unit economic models, and a cost minimization objective is proposed that is to be achieved based on the real-time electrical price. The results show that the proposed framework and methods will help the targeted DC residential system to reduce the total cost and reach stability and efficiency.

This paper addresses frequency deviation and tie-line power fluctuation in the islanded multi-area microgrid clusters (MMGCs). In the islanded MMGCs, the uncertain and varying nature of energy provided by renewable energy resources makes the issues of frequency and tie-line power more difficulty and complexity than the traditional power system. In response to these issues, a decentralized robust smoothing control strategy with the coordination of generators and energy storage system (ESS) is designed. First, taken into account the tie-line power change between sub-microgrids, the storing/releasing energy of energy storage system and the dynamic complexity of renewable energy, the detailed state space dynamic model is presented. Then, the architecture of the decentralized robust smoothing control strategy in MMGCs, which contains generator control loop and energy storage control loop, is proposed. Based on the architecture of robust smoothing control strategy, the microgrid smoothing control (MSC) in generator control loop and energy storage smoothing control (ESSC) in energy storage control loop are designed. In the MSC, by using linear matrix inequality LMI) technique, the rolling optimization mixed $H_{2}/H_{\infty }$ control with regional pole placement is proposed for regulating the generator power. Third, considering the overcharging and discharging of supercapacitors, the fuzzy-based self-adaptive energy storage smoothing controller (ESSC) of the supercapacitor is proposed to improve the low inertia of islanded MMGCs while smooth tie-line power fluctuation and frequency deviation. Finally, the robustness and performance of decentralized robust smoothing control is validated in the presence of various disturbances. The results are compared with other controller. Simulation results show the effectiveness and robustness of the proposed controller.

Numerous studies on wind power forecasting show that random errors found in the prediction results cause uncertainty in wind power prediction and cannot be solved effectively using conventional point prediction methods. In contrast, interval prediction is gaining increasing attention as an effective approach as it can describe the uncertainty of wind power. A wind power interval forecasting approach is proposed in this article. First, the original wind power series is decomposed into a series of subseries using variational mode decomposition (VMD); second, the prediction model is established through kernel extreme learning machine (KELM). Three indices are taken into account in a novel objective function, and the improved artificial bee colony algorithm (IABC) is used to search for the best wind power intervals. Finally, when compared with other competitive methods, the simulation results show that the proposed approach has much better performance.

In response to the limitations of existing parameter measurement methods for four-circuit transmission lines of the same voltage—namely, the failure to account for earth resistance and the complexity of methods that hinder live-line measurements—this paper proposes a more accurate method for measuring the distribution parameters of such transmission lines, incorporating earth resistance. The paper derives the transmission equations, including earth resistance, from the standard transmission line equations for three-phase power lines. The symmetrical component method is employed to decouple the parameters, allowing the earth resistance, which is difficult to measure directly, to be expressed as a combination of positive and zero-sequence parameters that are easier to measure. Additionally, the phase-mode transformation matrix for the four-circuit line parameters is derived, enabling the diagonalization of the twelve-order parameter matrix for the four-circuit lines. This transformation matrix can then be applied to the voltage and current signals measured at both ends of the line, facilitating the determination of the voltage and current magnitudes. At each magnitude, the relationship between voltage and current conforms to the transmission equations of a single-circuit line. The proposed method is compared with traditional methods and improved traditional methods using PSCAD/EMTDC software (version 4.6.2). Furthermore, an adaptability analysis of the proposed method is conducted, considering variations in line length and theoretical initial values. The results demonstrate that the proposed method is suitable for measuring the distribution parameters of four-circuit transmission lines of the same voltage across a range of voltage levels and line lengths.