Different from power prediction for a single wind farm, the regional is to predict total of multiple farms located in specific region. The involves more data that implicate abundant information on spatiotemporal correlations and nonlinearity. So addressing massive extracting representative features became crucial issues construct an effective model. This article proposes quantile regression (QR) algorithm perform short-term nonparametric probabilistic power, incorporating advantages hybrid...

Probabilistic wind generation forecast results are crucial for power system operational dispatch. In this paper, a nonparametric approach short-term probabilistic based on the sparse Bayesian classification (SBC) and Dempster–Shafer theory (DST) is proposed. This composed of following four steps. 1) A spot performed support vector machine (SVM). 2) The range SVM error discretized into multiple intervals, conditional probability each interval estimated by classifier. 3) DST applied to combine...

With the increasing penetration of distributed generators (DGs) and growing demand for reliable power sources, it has become imperative to promptly identify anomalies in active distribution networks (ADNs). Additionally, anomaly identification is also crucial assisting targeting maintenance handle failures after action relay protections. This study presents a highly accurate rapidly responsive approach identifying ADNs. The proposed method uses three layers intricately interconnected...

Recent research has demonstrated that the rotor angle stability of a power system can be assessed by identifying sign system's maximal Lyapunov exponent (MLE). A positive (negative) MLE implies unstable (stable) dynamics. However, because may fluctuate between and negative values for long time after severe disturbance, determining is difficult when observing or without knowing its further fluctuation trend. In this paper, new approach online assessment proposed to address problem. The...

In this paper, new formulations of the power flow and continuation that allow for electro-thermal coupling in transmission lines have been proposed. The capture overhead lines' effects by treating their series resistances as temperature dependent variables. They generate results can differ from conventional markedly, particularly problems centring on line impedances. paper demonstrates applying to transfer limit calculation. Generally, limits are defined either encountering a line's thermal...

This article presents a model predictive control (MPC) based multitime scale co-optimized dispatch for integrated electricity and natural gas system (IEGS) considering the bidirectional interactions renewable uncertainties. In proposed model, optimal is extended into three substages optimization problems of day-ahead, intraday, real-time to coordinate economy accuracy operations. The different strategy designed in each dispatching stage according operating characteristics multienergy coupled...

To effectively deal with the challenge of optimal dispatch caused by uncertainties such as renewable energy in active distribution network, a day-ahead strategy for network based on improved deep reinforcement learning is proposed. First, problem modeled multistage stochastic programming model. Multistage models attempt to capture dynamics unfolding over time, so that interaction between decision making and uncertainty represented more accurately realistically, can be adjusted dynamically...

Wind generation forecast approaches are typically based on fixed model structures, which might fit well with existing data but fall short in forecasting out-of-sample data. The reason lies that predetermined models cannot always capture the actual dynamic features of wind farms, resulting unavoidable errors. In this paper, a novel ultra-short-term approach multivariate empirical modeling is proposed. time series and explanatory variables applied for attractor reconstruction according to...

The estimation of the conditional failure rate (CFR) an overhead transmission line (OTL) is essential for power system operational reliability assessment. It hard to predict CFR precisely, although great efforts have been made improve accuracy. One significant difficulty lack available outage samples, due which law large numbers no longer applicable and convincing statistical result can be obtained. To address this problem, in paper, a novel imprecise probabilistic approach proposed estimate...

Different from individual wind power forecast and regional (RWPF), one of the most significant research articles for alleviating negative influence on systems aims to estimate generation multiple farms in specific region, which is a valuable complement forecast. This article proposes nonparametric probabilistic method RWPF, quantile regression neural network (QRNN), enhancing abilities nonlinear mapping massive data dealing. On this basis, deep proposed improve performance QRNN. In approach,...

In conventional contingency analysis (CA), the overloading of transmission lines is identified by violation current or power flow rather than temperature rise. Thus, transient thermal behavior usually neglected, which may cause underestimation transfer capability and lead to misoperations. this paper, a new CA method that considers overhead proposed, where heat balance based (THB-PF) model established estimate dynamics after contingencies. The THB-PF represented algebraic differential...

A novel multi-dimensional scenario forecast approach which can capture the dynamic temporal-spatial interdependence relation among outputs of multiple wind farms is proposed. In proposed approach, support vector machine (SVM) applied for spot power generation. The probability density function (PDF) SVM error predicted by sparse Bayesian learning (SBL), and result corrected according to expectation obtained. copula estimated using a Gaussian copula-based conditional correlation matrix...

Different from power prediction for a single wind farm, the regional is to predict total of multiple farms located in same region. Normally, abundant information on spatiotemporal correlations and nonlinearity implicated farms, thus selecting most representative explanatory variables becomes one crucial issues construct an effective model. This paper proposes quantile regression (SQR) algorithm perform short-term nonparametric probabilistic power, incorporating advantages hybrid neural...

The increasing high penetration of wind power will further increase the uncertainty in systems, and three key issues should be addressed: 1) determining maximum accommodation level without sacrificing system reliability; 2) quantifying potential risk when generation realization is beyond prescribed sets; 3) how to reduce loss. Motivated by these, a risk-based two-stage robust unit commitment (RUC) model proposed analyze admissibility power. In this model, electricity storage (ESS) utilized...

The traditional hierarchical scheduling and operational model of transmission distribution networks has failed to fully utilize the adjustable resources entire grid, consequently limiting integration renewable energy. To excavate potential (T&D) coordination in enhancing level energy assimilation efficiency, this paper, grid network framework synergetic unit commitment (TDS-UC) considering dynamic characteristics electricity-gas-heat integrated system is proposed. developed paper allows for...

Sustainable energy development requires environment-friendly energy-generating methods. Pricing system constraints influence the efficient use of resources. Real-Time (RTP) is theoretically superior to previous pricing systems for allowing demand response (DR) activities. The DR approach has been useful correcting supply–demand imbalances as technology evolved. There are several determining and controlling DR. However, most these solutions unable control rising or forecast prices future time...

Abstract With the increasing proportion of distributed energy resources, optimisation in active distribution network becomes highly complex and challenging. To protect user privacy perform efficient calculations, this paper proposes an online between operator. overcome constraint non‐linearity, a new linear power flow model is adopted, which can be updated online. In addition, to solve time‐coupled conundrum storage, Lyapunov drift plus penalty method employed transform long‐time scale...

Because of the extensive application phaser measurement unit (PMU) in power system, traditional system state estimation has been undergoing an essential change. In this paper, estimator is assumed to be functioning normally absence PMU data. Then under given placement paper wants explore substantial contribution estimation. First, it discusses difference between and SCADA explain effect on Then, supposing right value obtained from PMU, extracts simpleness with data only, proposes reduced...

This paper presents a prediction error-based power forecasting (PEBF) method for Photovoltaic (PV) system, using Photovoltaics Utility Scale Applications (PVUSA) model based grey box neural network (GBNN). First, the differential equation PVUSA is transformed into network. In proposed PEBF scheme, set to train whenever difference between predicted and output powers increases from certain threshold defined on system dynamics requirements. The unique design of takes far less training time than...