Showing papers in "International Journal of Electrical Power & Energy Systems in 2023"

TL;DR: In this article , a similar-weighted spatial-temporal graph is constructed to reflect the coupling relationship between loads of each bus and has a certain interpretability, and the spatial aggregation features are generated to realize the enhancement of full-domain node features.

TL;DR: In this article , a linear AC unit commitment (ACUC) model is proposed to address the high computational burden of nonlinear ACUC model in large-scale systems, which achieves a high-accuracy solution that is close to the solution of the exact unit commitment, while it keeps the problem from getting into a huge computational burden.

TL;DR: In this paper , the impact of integration of inverter-based renewable energy sources (RESs) on grid frequency response through eigenvalue analysis of low-inertia power grids is assessed.

TL;DR: In this paper , an extension of MPC charge control structure for lithium-ion batteries based on one of the most commonly used equivalent circuit models (ECMs) is proposed. But, the battery's nonlinear state of charge (SOC) - open circuit voltage (OCV) relationship prevents the direct application of standard MPC design process.

TL;DR: In this paper , an optimal scheduling model based on CCHP and carbon capture device is proposed, which takes into account the demand response of cooling, heating and electricity load and ladder-type carbon trading mechanism.

TL;DR: Aiming at the global environmental pressure and energy crisis, an optimal configuration method of a multi-energy microgrids system is proposed in the context of the electricity market as mentioned in this paper , where the upper-level regional energy supply is centrally coordinated and planned, and the lower-level multihop micro-grids are independent and autonomous.

TL;DR: Wang et al. as mentioned in this paper proposed a probabilistic forecasting method for hourly load time series based on an improved temporal fusion transformer (ITFT) model to achieve more accurate and thorough forecasting results.

TL;DR: In this article , a three-level game-theoretic intelligent structure is proposed to evaluate individual and collaborative strategies of electricity manufacturers, considering network and physical constraints, and the results verify the proposed model influence electric players to find effective collaborative strategies under different conditions and environments.

TL;DR: In this article , a hybrid version of the You Only Look Once (YOLO) using ResNet-18 classifier was proposed for power system inspection based on real images of failed components recorded by UAVs.

TL;DR: In this article , the TOT model parameter estimation problem is reformulated from a system identification perspective by exploring the finite-time estimators (FTEs) that accurately identify and estimate the top-oil temperature (TOT) model parameters for the streaming data from real-time working transformers without any laboratory experiments and DoE.

TL;DR: In this paper , an improved decoupled power control method was proposed based on the feedforward compensation method, which can realize more accurate decouple active and reactive power regulation, and its design is simple, and thus is easy to implement in practice.

TL;DR: In this paper , an optimal real-time pricing (ORTP) approach for the aggregation of distributed energy resources within energy communities is proposed, where the interaction between a community-owned profit-maximizing aggregator and the users (consumers with electricity generation and storage potential, known as "prosumagers" and electric vehicles) is formulated as a stochastic bilevel disjunctive program.

TL;DR: In this paper , a data-driven framework for risk-constrained coordinated bidding strategy for a wind integrated power system that participates in the electricity balancing market is proposed, where a price uncertainty predictor consisting of ridge regression, non-pooling convolutional neural network, and linear quantile regression is first modeled to evaluate the day-ahead electricity price uncertainty.

TL;DR: In this paper , a distributed solar hybrid combined cooling, heating, and power (CCHP) system is constructed by installing photovoltaic/thermal (PV/T) panels in the CCHP system.

TL;DR: In this paper , a stochastic-robust approach is used to develop a novel day-ahead scheduling model for prosumers integrated in energy communities based on a Stochastic-Robust approach, where the heterogeneity of the unknown parameters is effectively addressed by using different uncertainty models.

TL;DR: In this paper , a grid-connected integrated energy system (IES) is proposed, which considers the complementarity of geothermal energy and solar energy and takes heat storage into account, and a multi-objective optimization model was established aiming at integrating operation cost, exergic efficiency and pollution gas emission penalty cost.

TL;DR: In this paper , an optimal bidding strategy model of a virtual power plant (VPP) in the day-ahead market (DAM) that contains energy, reserve, and regulation markets is constructed.

TL;DR: In this article , the authors presented a control scheme based on event-triggered control (ETC) to minimize frequency deviation in each area, and demonstrated in single-area, multi-area power system, and with integrated wind power, according to real wind speed dynamics.

TL;DR: In this paper , a two-stage optimization technique is proposed to determine the charging and discharging schedule for EVs participating in a vehicle-to-grid (V2G) programme at an office building.

TL;DR: In this paper , a new management methodology to find the optimum operation of a grid-connected microgrid system, which is modeled as an optimization approach and aims to minimize total cost, is presented.

TL;DR: In this article , the authors proposed a two-step optimal scheduling method based on power classification, where the Monte Carlo method is used to estimate the expectation and variance of the objective function, and a certain number of samples are obtained through sampling.

TL;DR: In this paper , a non-unit protection scheme based on waveform similarity and wavelet transform modulus maximum (WTMM) theories was proposed for the VSC-HVDC transmission line.

TL;DR: Wang et al. as discussed by the authors developed a quantitative assessment framework, which includes the identification of vulnerable lines and the development of a novel resilience assessment index (REAI), to improve the resilience of a power system against such events.

TL;DR: In this paper , a complementary use of Deep Learning (DL)-based and Dissipating Energy Flow (DEF)-based methods are proposed to localize forced oscillation source(s) using data from Phasor Measurement Units (PMUs), by tracing the forced oscillations source (s) on the branch level in the power system network.

TL;DR: In this paper , the authors improved the uncertainty model of wind power by fitting three typical characteristics: kernel density estimation (KDE), non-parametric Copula model, and the forecast error boundary constraints.

TL;DR: In this paper , the role of battery energy storage systems in mitigating the voltage and frequency stability issues in weak grids was investigated using a binary grey wolf optimization approach to define the locations and sizes of BESSs.

TL;DR: In this paper , the proportional integral derivative-based controller with second order derivative term (PIDD2) for the automatic voltage regulator (AVR) of synchronous generator is presented.

TL;DR: In this article , a double-layer automatic generation control (AGC) frequency regulation control method that considers the operating economic cost and the consistency of the state of charge (SOC) of the energy storage is proposed.

TL;DR: In this article , the authors present the place and role of Data Science (DS) and Machine Learning (ML) on edge, fog, and cloud levels of vertical IIoT concepts of power plants.

TL;DR: In this paper , a day-ahead, intraday, multi-time scale economic scheduling method based on light robust optimization and model predictive control (MPC) is proposed.