The dependence on advanced information and communication technology increases the vulnerability in smart grids under cyber-attacks. Recent research unobservable false data injection attacks (FDIAs) reveals high risk of secure system operation, since these can bypass current bad detection mechanisms. To mitigate this risk, paper proposes a data-driven learning-based algorithm for detecting FDIAs distribution systems. We use autoencoders efficient dimension reduction feature extraction...

This paper develops a model-free volt-VAR optimization (VVO) algorithm via multi-agent deep reinforcement learning (DRL) in unbalanced distribution systems. method is novel since we cast the VVO problem networks to an intelligent Q-network (DQN) framework, which avoids solving specific model directly when facing time-varying operating conditions We consider statuses/ratios of switchable capacitors, voltage regulators, and smart inverters installed at distributed generators as action...

The integration of uncertain power resources is causing more challenges for traditional load modeling research. Parameter identification impacted by a variety components with time-varying characteristics. This paper develops deep learning-based parameter model composite (CLM) ZIP and induction motor. A multi-modal long short-term memory (M-LSTM) learning method used to estimate all the parameters CLM considering system-wide measurements. It contains structure that makes use different...

With the application and development of combined heat power (CHP) techniques, coupling electrical energy is gradually increasing. State estimation (SE) essential to achieve comprehensive accurate operating status in an integrated electricity-heat system (IEHS). This article proposes a robust SE method based on second-order conic programming (SOCP) for IEHS. Firstly, auxiliary state variables measurements are introduced obtain exact linear measurement equations Then, model weighted least...

Selection of the kernel function by support vector regression (SVR), for purposes load forecasting, is affected power characteristics. The non-ideal SVR with a has low forecasting accuracy and poor generalization ability. A novel method combining stacking proposed in this paper. Base models are constructed based on SVRs different functions, then multiple base merged to obtain model layer via algorithm. Finally, an connected as meta-model layer. fusion composed This trained k-fold cross...

Distribution system state estimation (DSSE), which provides critical information for monitoring and control, is being challenged by multiple sources of uncertainties such as random meter errors, stochastic power output distributed generation (DG), imprecise network parameters. This paper originally proposes a general interval (ISE) model to simultaneously formulate these in unbalanced distribution systems arithmetic. Moreover, this can accommodate partially available measurements DG outputs...

Motivated by increasing penetration of distributed generators (DGs) and fast development micro-phasor measurement units (μPMUs), this paper proposes a novel graph-based faulted line identification algorithm using limited number μPMUs in distribution networks. The core the proposed method is to apply advanced system state estimation (DSSE) techniques integrating μPMU data fault location. We propose DSSE efficiently restrict searching region for source feeder between two adjacent μPMUs. Based...

Grid emergency voltage control (GEVC) is paramount in electric power systems to improve stability and prevent cascading outages blackouts case of contingencies. While most deep reinforcement learning (DRL)-based paradigms perform single agents a static environment, real-world for GEVC are expected cooperate dynamically shifting grid. Moreover, due high uncertainties from combinatory natures various contingencies load consumption, along with the complexity dynamic grid operation, data...

Free-space optical (FSO) communications has recently received significant attention and commercial interest for a variety of applications. In this paper, the outage probabilities both parallel serial relay-aided FSO are analyzed. Initially, new aggregated channel fading model is established, which considers atmospheric attenuation, <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="TeX">${\cal...

Due to the vulnerability of civilian global positioning system (GPS) signals, accuracy phasor measurement units (PMUs) can be greatly compromised by GPS spoofing attacks (GSAs), which introduce phase shifts into true angle measurements. Focusing on simultaneous GSAs for multiple PMU locations, this paper proposes a novel identification and correction algorithm in distribution systems. A sensitivity analysis state estimation residuals single GSA is firstly implemented. An using probing...

Prefix hijacking, a misbehavior in which misconfigured or malicious BGP router originates an IP prefix that the does not own, is becoming increasingly serious security problem on Internet. In this paper, we conduct first comprehensive study incrementally deployable mitigation solutions against hijacking. We propose novel reactive detection-assisted solution based idea of bogus route purging and valid promotion. Our simulations realistic settings show routes at 20 highest-degree ASes reduces...

A new two-terminal fault-location algorithm for series-compensated double-circuit transmission lines based on the distributed parameter line model is proposed. The system considered as fully transposed, and a six-sequence component network introduced to decouple mutual electromagnetic effects between circuits. Two subroutines designated fault that occurs left or right side of series compensator are developed. In each subroutine, voltage device eliminated fact sequence voltages calculated...

Abstract ARIMA model forecasting algorithm is a commonly used time series algorithm, this paper first obtains stable sequence through differential operation, and then from the AR model, as MA even model. Select appropriate for prediction use it adaptive mode design. In field of machine learning, complexity likely to increase, while accuracy improves, models with complex structure usually cause following overfitting problem. order balance reasonably, using indicators AIC (Akaike Information...

The rapid integration of renewable energy sources (RESs) has imposed substantial uncertainty and variability on the operation power markets, which calls for unprecedentedly flexible generation resources such as batteries. In this paper, we develop a novel pricing mechanism day-ahead electricity markets to adeptly accommodate uncertainties stemming from RESs. First, distributionally robust joint chance-constrained (DRJCC) economic dispatch model that incorporates storage systems is presented,...

Volumetric distributed denial-of-service (DDoS) attacks can bring any network to a halt. Because of their nature and high volume, the victim often cannot handle these alone needs help from upstream ISPs. Today's Internet has no automated mechanism for victims ask ISPs in attack handling themselves do not offer such services. We propose SENSS, security service collaborative mitigation volumetric DDoS attacks. SENSS enables an request monitoring filtering on demand, pay services rendered....

This letter proposes a novel and highly efficient distribution system state estimation (DSSE) method with nonlinear measurements from supervisory control data acquisition (SCADA) systems. Conventional DSSE based on the weighted least square (WLS) criterion requires multiple Monte Carlo simulations for overall accuracy evaluation high calculation cost due to iterative process. The proposed uses Taylor series of voltages constructing linear model in interval form then solves this by...

Objective: This study aims to conduct a comprehensive bioinformatic analysis identify pharmacological targets in rectum tissue, rectal cancer and the effects of Salidroside. Methods: Genes associated with cancer, Salidroside were identified using MeSH retrieval from NCBI database screened GeneCards, TCMSP, HERB, ETCM databases. The overlapping genes visualized Venn diagram created on jvenn website. Protein-protein interactions (PPI), Gene Ontology (GO) analysis, Kyoto Encyclopedia Genomes...

With the development of metabolic engineering, increasing requirements for efficient microbial biosynthesis call establishment multi-strain co-culture system. Dynamic regulation population ratios is crucial optimizing bioproduction performance. Optogenetic systems with high universality and flexibility have potential to realize dynamic control proportion. In this study, we utilized an optimized chromatic acclimation sensor/regulator (CcaS/R) system a blue light-activated YF1-FixJ-PhlF as...