Optimal Fully Electric Vehicle load balancing with an ADMM algorithm in Smartgrids

In this paper we present a system architecture and a suitable control methodology for the load balancing of Fully Electric Vehicles at Charging Station (CS). Within the proposed architecture, control methodologies allow to adapt Distributed Energy Resources (DER) generation profiles and active loads to ensure economic benefits to each actor. The key aspect is the organization in two levels of control: at local level a Load Area Controller (LAC) optimally calculates the FEVs charging sessions, while at higher level a Macro Load Area Aggregator (MLAA) provides DER with energy production profiles, and LACs with energy withdrawal profiles. Proposed control methodologies involve the solution of a Walrasian market equilibrium and the design of a distributed algorithm.Comment: This paper has been accepted for the 21st Mediterranean Conference on Control and Automation, therefore it is subjected to IEEE Copyrights. See IEEE copyright notice at http://www.ieee.org/documents/ieeecopyrightform.pd

Finite element analysis of stress distribution and the effects of geometry in a laser-generated single-stage ceramic tile grout seal using ANSYS

Optimisation of the geometry (curvature of the vitrified enamel layer) of a laser-generated single-stage ceramic tile grout seal has carried out with a finite element (FE) model. The overall load bearing capacities and load-displacement plots of three selected geometries were determined experimentally by the indentation technique. Simultaneously, a FE model was developed utilising the commercial ANSYS package to simulate the indentation. Although the load-displacement plots generated by the FE model consistently displayed stiffer identities than the experimentally obtained results, there was reasonably close agreement between the two sets of results. Stress distribution profiles of the three FE models at failure loads were analysed and correlated so as to draw an implication on the prediction of a catastrophic failure through an analysis of FE-generated stress distribution profiles. It was observed that although increased curvatures of the vitrified enamel layer do enhance the overall load-bearing capacity of the single-stage ceramic tile grout seal and bring about a lower nominal stress, there is a higher build up in stress concentration at the apex that would inevitably reduce the load-bearing capacity of the enamel glaze. Consequently, the optimum geometry of the vitrified enamel layer was determined to be flat

Simulation of Near-Tip Crack Behaviour and Its Correlation to Fatigue Crack Growth with a Modified Strip-Yield Model

A modified strip-yield model has been developed to simulate the plasticity-induced crack closure under the constant amplitude (CA) and a single overload loading conditions. The paper focuses on the simulation of the near tip crack profiles and stress distributions during the fatigue process. Detailed information on near-tip stress and displacement fields at the maximum load (Pmax), the minimum load (Pmin), and the crack opening load (Pop) of a fatigue load cycle have been presented. The correlation of the crack closure to the near-tip material fatigue damage has been investigated and used to rationalize the crack growth behaviour under the CA and a single overload loading conditions.Peer reviewedSubmitted Versio

Submodular Load Clustering with Robust Principal Component Analysis

Traditional load analysis is facing challenges with the new electricity usage patterns due to demand response as well as increasing deployment of distributed generations, including photovoltaics (PV), electric vehicles (EV), and energy storage systems (ESS). At the transmission system, despite of irregular load behaviors at different areas, highly aggregated load shapes still share similar characteristics. Load clustering is to discover such intrinsic patterns and provide useful information to other load applications, such as load forecasting and load modeling. This paper proposes an efficient submodular load clustering method for transmission-level load areas. Robust principal component analysis (R-PCA) firstly decomposes the annual load profiles into low-rank components and sparse components to extract key features. A novel submodular cluster center selection technique is then applied to determine the optimal cluster centers through constructed similarity graph. Following the selection results, load areas are efficiently assigned to different clusters for further load analysis and applications. Numerical results obtained from PJM load demonstrate the effectiveness of the proposed approach.Comment: Accepted by 2019 IEEE PES General Meeting, Atlanta, G

Demand Shaping to Achieve Steady Electricity Consumption with Load Balancing in a Smart Grid

The purpose of this paper is to study conflicting objectives between the grid operator and consumers in a future smart grid. Traditionally, customers in electricity grids have different demand profiles and it is generally assumed that the grid has to match and satisfy the demand profiles of all its users. However, for system operators and electricity producers, it is usually most desirable, convenient and cost effective to keep electricity production at a constant rate. The temporal variability of electricity demand forces power generators, especially load following and peaking plants to constantly manipulate electricity production away from a steady operating point

Load curve data cleansing and imputation via sparsity and low rank

The smart grid vision is to build an intelligent power network with an unprecedented level of situational awareness and controllability over its services and infrastructure. This paper advocates statistical inference methods to robustify power monitoring tasks against the outlier effects owing to faulty readings and malicious attacks, as well as against missing data due to privacy concerns and communication errors. In this context, a novel load cleansing and imputation scheme is developed leveraging the low intrinsic-dimensionality of spatiotemporal load profiles and the sparse nature of "bad data.'' A robust estimator based on principal components pursuit (PCP) is adopted, which effects a twofold sparsity-promoting regularization through an $\ell_1$-norm of the outliers, and the nuclear norm of the nominal load profiles. Upon recasting the non-separable nuclear norm into a form amenable to decentralized optimization, a distributed (D-) PCP algorithm is developed to carry out the imputation and cleansing tasks using networked devices comprising the so-termed advanced metering infrastructure. If D-PCP converges and a qualification inequality is satisfied, the novel distributed estimator provably attains the performance of its centralized PCP counterpart, which has access to all networkwide data. Computer simulations and tests with real load curve data corroborate the convergence and effectiveness of the novel D-PCP algorithm.Comment: 8 figures, submitted to IEEE Transactions on Smart Grid - Special issue on "Optimization methods and algorithms applied to smart grid

Use of generated artificial road profiles in road roughness evaluation

In the evaluation of road roughness and its effects on vehicles response in terms of ride quality, loads induced on pavement, drivers’ comfort, etc., it is very common to generate road profiles based on the equation provided by ISO 8608 standard, according to which it is possible to group road surface profiles into eight different classes. However, real profiles are significantly different from the artificial ones because of the non-stationary feature of the first ones and the not full capability of the ISO 8608 equation to correctly describe the frequency content of real road profiles. In this paper, the international roughness index, the frequency-weighted vertical acceleration awz according to ISO 2631, and the dynamic load index are applied both on artificial and real profiles, highlighting the different results obtained. The analysis carried out in this work has highlighted some limitation of the ISO 8608 approach in the description of performance and conditions of real pavement profiles. Furthermore, the different sensitivity of the various indices to the fitted power spectral density parameters is shown, which should be taken into account when performing analysis using artificial profiles