Microgrids with distributed generation (DG) provide a resilient solution in the case of major faults distribution system due to natural disasters. This paper proposes novel operational approach by forming multiple microgrids energized DG from radial real-time operations restore critical loads power outage. Specifically, mixed-integer linear program is formulated maximize be picked up while satisfying self-adequacy and operation constraints for formation problem controlling ON/OFF status...

By modeling the uncertainty of spinning reserves provided by energy storage with probabilistic constraints, a new optimal scheduling mode is proposed in this paper for minimizing operating costs an isolated microgrid (MG) using chance-constrained programming. The model transformed into readily solvable mixed integer linear programming formulation general algebraic system (GAMS) via discretized step transformation approach and finally solved applying CPLEX solver. properly setting confidence...

Load modeling has significant impact on power system studies. This paper presents a review load and identification techniques. models can be classified into two broad categories: 1) static 2) dynamic models, while there are types of approaches to identify model parameters: measurement-based component-based. received more attention in recent years because the renewable integration, demand-side management, smart metering devices. However, commonly used outdated, cannot represent emerging...

In this paper, a virtual-impedance-based fault current limiter (VI-FCL) is proposed for islanded microgrids comprised of multiple inverter interfaced distributed generators (DGs). Considering the induced by high penetration renewable energy sources, FCLs are employed to suppress and subsequent oscillation even instability in modern distribution network with microgrids. rather than involving extra hardware equipment, functionality FCL achieved control diagram DG inverters employing additional...

Dissolved gas analysis (DGA) approach is extensively applied to detect incipient faults of power transformers. This paper presents a novel DGA method for transformer fault diagnosis based on integrated adaptive neuro fuzzy inference system (ANFIS) and Dempster-Shafer Theory (DST). Four out seven common conventional methods which are studied compared better consistency accuracy, used develop new ANFIS models. To promote diagnostic performance further make decision process more reliable...

This paper proposes an advanced distribution management system (DMS) that a) monitors each component and performs protection functions using a dynamic state estimation, b) the estimated states are transmitted to DMS where real time model of entire feeder is synthesized, c) uses perform upper level optimization (operations planning) lower (real control) via hierarchical procedure; d) applies proper controls operate at optimal points. The proposed approach for protection, operations planning,...

This article presents a supervised multi-agent safe policy learning (SMAS-PL) method for optimal power management of networked microgrids (MGs) in distribution systems. While unconstrained reinforcement (RL) algorithms are black-box decision models that could fail to satisfy grid operational constraints, our proposed considers AC flow equations and other limits. Accordingly, the training process employs gradient information constraints ensure control functions generate feasible decisions....

To further improve fault diagnosis accuracy, a new hybrid feature selection approach combined with genetic algorithm (GA) and support vector machine (SVM) is presented in this study. Adaptive synthetic technique arctangent transformation method are adopted to the statistical property of training set (IEC TC10 dataset). Five filter methods based on different evaluation metrics employed rank 48 input features derived from dissolved gas analysis (DGA). Then, combination applied aggregate ranks...

In order to coordinate multiple different scheduling objectives from the perspectives of economy, environment, and users, a practical multi‐objective dynamic optimal dispatch model incorporating energy storage user experience is proposed for isolated microgrids. this model, besides microturbine units, employed provide spinning reserve services microgirds; furthermore, perspective demand side management, consumer satisfaction indicator developed measure quality experience. A two‐step solution...

This paper proposes a two-stage energy management system (EMS) for power grids with massive integration of electric vehicles (EVs) and renewable resources. The first stage economic dispatch determines the optimal operating points charging stations battery swapping (BSS) EVs under plug-in modes, respectively. proposed stochastic model predictive control (SMPC) problem in this is characterized through chance-constrained optimization formulation that can effectively capture forecast...

With the increasing integration of uncertain resources, e.g., renewables, electric vehicles, and demand responses, it is imperative to understand characteristics loads for power system analysis control. Challenges load modeling come from a variety components time-varying compositions. In addition, existence outliers in measurements further complicates problem. This paper proposes robust parameter identification technique composite ZIP induction motor models. A batch-model regression form,...

Different electric vehicle (EV) charging algorithms result in different EV load profiles, that if aggregated, influence the power grid operation. The existing demand models are either based on status upon arrival or smart reinforced with particular methods and/or levels. This article proposes a new data-driven approach for modeling. We first introduce mathematical model characterizes flexibility of demand. Advanced simulation procedures then proposed to identify parameters and simulate under...

This paper proposes a new planning model to coordinate the expansion of electric vehicle charging infrastructure (EVCI) and renewables in power grids. Firstly, individual (EV) behaviours are modeled considering EV customers adopting smart services as main method those using fast charging, super battery swapping complementary approach. Next, aggregation associated system economic dispatch built. A novel predictive control (MPC) learning approach is then proposed iteratively learn correlation...

To mitigate the impact of extended power outages from extreme weather events, utilities are trying to improve existing restoration practices by adopting many emerging technologies. The coordination will be more complicated when participants such as EVs expected provide grid services during and customers demanding less impact. In this paper, an integrated formulation for service restoration, crew dispatch, EV dispatch with distributed energy resources (DER) control is proposed. A unified...

Environmental concerns and depletion of traditional energy lead to the booming development renewable distributed generation (RDG) in past decade. However, due intermittent nature sources, what extent RDG could provide capacity power systems becomes a critical issue utility company when implementing long-term system strategic (generation expansion) planning. On other hand, smart-grid frame, popularization different varieties demand-side resources enables operate at more flexible modes ever...

This paper proposes a parameter identification technique for composite ZIP and electronic loads by leveraging the support vector machine (SVM) approach. Since active power reactive of are piecewise functions voltage magnitude, operating modes determined magnitude. To improve accuracy identification, two filters (Hampel Savitzky–Golay) employed to preprocess measurements reduce noise. The data after noise reduction serve as training regression model that is solved SVM Numerical results show...

The proliferation of electric vehicles (EVs) brings environmental benefits and technical challenges to power grids. An identification algorithm which can accurately extract individual EV charging profiles out widely available smart meter measurements has attracted great interests. This paper proposes a non-intrusive framework for profile extraction, is driven by deep generative models (DGM). First, the proposed DGM designed as representation layer embedded into Markov process used model...

In this study, a new control approach for real-time speed synchronisation of multiple induction motors during acceleration and load changes is developed. The strategy to stabilise tracking each motor while synchronising its motion with other motors' motions so that differential errors among converge zero. An adjacent cross-coupling architecture incorporating sliding mode method proposed, the asymptotic convergence zero both have been realised via Lyapunov stability analysis. Performance...