This paper makes use of the idea prediction intervals (PIs) to capture uncertainty associated with wind power generation in systems. Since forecasting errors cannot be appropriately modeled using distribution probability functions, here we employ a powerful nonparametric approach called lower upper bound estimation (LUBE) method construct PIs. The proposed LUBE uses new framework based on combination PIs overcome performance instability neural networks (NNs) used method. Also, fuzzy-based...

This paper addresses the optimal operation and scheduling of reconfigurable microgrids incorporating dynamic line rating limitations during islanded grid-connected mode operations. The incorporation overhead feeders can potentially improve system security when providing economical technical benefits for microgrid. proposed framework takes into account a realistic formulation to minimize total microgrid costs in both multiperiod modes. Also, stochastic based on unscented transform is model...

Power grid resilience, reliability, and sustainability can be improved significantly by decomposing the large grids into networked microgrids (NMGs). However, optimal energy management problem preserving security in NMGs are more complicated challenging. This paper aims to propose a secured stochastic framework for based on modified blockchain approach, utilizing directed acyclic graph (DAG). Using decentralized transparent technology will help have higher lower risks within network, thus...

In this article, an accurate secured framework to detect and stop data integrity attacks in wireless sensor networks microgrids is proposed. An intelligent anomaly detection method based on prediction intervals (PIs) introduced distinguish malicious with different severities during a operation. The proposed constructed the lower upper bound estimation provide optimal feasible PIs over smart meter readings at electric consumers. It also makes use of combinatorial concept solve instability...

This paper develops an effective two-stage stochastic post-hurricane recovery framework to improve networked microgrid resilience using mobile emergency resources (MERs) and a proposed reconfiguration strategy. In the first stage, network actively alters local power flow path provides opportunities for restoring critical loads, thus reducing energy not supplied electric consumers. The optimal schedule determined in stage problem is also used determine islanded loads that need MERs...

This paper develops an effective model for microgrid optimal scheduling with dynamic network reconfiguration. Network reconfiguration can effectively alter local power flow and thus provide opportunity to reduce distribution losses during grid-connected operation (supporting economic objectives) potential load curtailments the islanded reliability objectives). The proposed is decomposed into a master problem subproblem. A novel highly accurate linear model, ability of line switching,...

This paper aims to investigate the optimal scheduling of stochastic reconfigurable hybrid ac-dc microgrid (MG) in presence renewable energies and also considering dynamic line rating (DLR) constraint. DLR is a practical limitation that can potentially affect ampacity lines, particularly islanded mode when lines reach their maximum capacity lack main generation source at point interconnection with utility. In order prevent overloading reconfiguration technique developed change topology...

Power grid resilience, reliability, and sustainability can be improved by decomposing the large-scale grids into Networked Microgrids (NMGs). However, different MGs may have roles policies. Hence, in comparison with conventional networks, optimal energy management, as well reconfiguration of NMGs is more completed challenging. This article develops a three-layer cloud-fog computing architecture for management reconfigurable considering dynamic thermal line rating (DLR) constraint. DLR...

AbstractAccurate load-forecasting problem is a significant and vital issue, especially in the new competitive electricity market. The models that are employed for forecasting purposes would determine how reliable last forecasted results are. Therefore, this paper proposes hybrid correction method based on autoregressive integrated moving average (ARIMA) model, support vector regression (SVR) cuckoo search algorithm (CSA) to achieve more model. proposed gets use of autocorrelation function...

The high relying of electric vehicles on either in-vehicle or between-vehicle communications can cause big issues in the system. This paper is going to mainly address cyberattack and propose a secured reliable intelligent framework avoid hackers from penetration into vehicles. proposed model constructed based an improved support vector machine for anomaly detection controller area network bus protocol. In order improve capabilities fast malicious attack avoidance, new optimization algorithm...

Industrial Internet of Things (IIoT) is an architecture that facilitates the feasibility distributed control modernized industrial systems mainly through and cloud computing. This article proposes optimal scheduling framework for real-time operation smart microgrids in IIoT environment using average consensus-based algorithm. The introduced suggests a fog layer as complementary to reduce latency provide local computation data storage proposed industry. Security system against probable...

This paper proposes a prediction interval-based model for modeling the uncertainties of tidal current prediction. The proposed constructs optimal intervals (PIs) based on support vector regression (SVR) and nonparametric method called lower upper bound estimation (LUBE) method. In order to increase stability SVRs that are used in LUBE method, idea combined is employed. As optimization tool, flower pollination algorithm along with two-phase modification presented optimize SVR parameters....

This paper proposes an accurate hybrid method based on support vector regression (SVR) and autoregressive integrated moving average (ARIMA) to predict the tidal current speed direction. In proposed model, ARIMA model captures linear component of current, remained residual components are modeled by SVR. order capture maximum components, appropriate is determined Akaike information criterion. Autocorrelation partial autocorrelation functions used verify stationary or nonstationary...

Intentional islanding can be considered as the last action to prevent power grids from severe blackouts. In this strategy, endangered network is deliberately decomposed into self-sustained islands improve grid resilience, reliability, and security. way, paper develops a novel optimal intentional solution deal with deliberate physical attacks on system. The proposed employs modified multi-layer constrained clustering method based graphs via subspace analysis Grassmann manifolds clustering....

In this study, the operating benefits of considering thermal recovery and hydrogen production in economic model a grid-parallel proton exchange membrane fuel cell power plant (PEM-FCPP) are investigated. Also study considers simultaneous effect distribution feeder reconfiguration (DFR) on management PEM-FCPPs stochastic environment. regard, new method based probabilistic approach called point estimate (PEM) is proposed to consider uncertainty associated with load demand prediction error as...

This paper proposes a univariate prognostic approach based on wavelet transform and support vector regression (SVR) to predict the tidal current speed direction with high accuracy. The proposed model decomposes data into some subharmonic components. details approximation components are later fed several SVR models attend prediction process. In order increase robustness of model, idea combined is used each signal by SVRs. median operator further determine aggregated forecast data. Due...

In this paper, a new hybrid method based on teacher learning algorithm (TLA) and artificial neural network (ANN) is proposed to develop an accurate model investigate short-term load forecasting more precisely. contrast the other evolutionary-based training techniques, utilises both ability of ANNs generate non-linear mapping among different complex data as well powerful TLA for global search exploration. addition, in attempt choose most satisfying features from set input variables, novel...

This study aims to investigate the role of reconfiguration strategy enhance reliability distribution systems. In this regard, idea failure rate reduction approach is employed assess three significant indices including System Average Interruption Frequency Index, Duration Index and Energy Not Supplied. addition, as a result attractiveness importance power loss objective function in system, target also considered problem. The problem then formulated stochastic framework based on 2m + 1 point...