Offline Configuration Resources about Smart Substation Multi-Dimensional and Multi-Objective Customization and Information Merger

2014 ◽  
Vol 1008-1009 ◽  
pp. 736-741
Author(s):  
Hai Dong Zhang ◽  
Ai Lin Chen ◽  
Ren Hui Dou ◽  
Hui Ren ◽  
Qing Yang ◽  
...  
Keyword(s):  
Large Scale ◽  
Level Control ◽  
Control Center ◽  
Multi Objective ◽  
Good Potential ◽  
Important Means ◽  
Grid Operation ◽  
Scale Grid ◽  
Smart Substation ◽  
Model Customization

Offline Configuration Resources about Smart substation Multi-dimensional and multi-objective customization and information merger is an important means of the development for the large-scale grid operation. In this paper, the method of smart substation model customization and information merger for multi-level control center is proposed. This paper puts forward the scheme、data flow and key technologies of model customization and information merger. The software of model customization and information merger, which can flexibly configure the rule of model reduction and information merger according to different scenarios, is designed and developed. The software is validated in the laboratory, which illustrates that idea of this paper has good potential value.

scholarly journals Multi-Objective Optimization of Integrated Civilian-Military Scheduling of Medical Supplies for Epidemic Prevention and Control

Healthcare ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 126
Author(s):  
Hai-Feng Ling ◽  
Zheng-Lian Su ◽  
Xun-Lin Jiang ◽  
Yu-Jun Zheng
Keyword(s):  
Prevention And Control ◽  
Large Scale ◽  
Medical Services ◽  
The Novel ◽  
Multi Objective ◽  
Medical Supplies ◽  
Problem Instances ◽  
Novel Coronavirus ◽  
And Control ◽  
Minimum Ratio

In a large-scale epidemic, such as the novel coronavirus pneumonia (COVID-19), there is huge demand for a variety of medical supplies, such as medical masks, ventilators, and sickbeds. Resources from civilian medical services are often not sufficient for fully satisfying all of these demands. Resources from military medical services, which are normally reserved for military use, can be an effective supplement to these demands. In this paper, we formulate a problem of integrated civilian-military scheduling of medical supplies for epidemic prevention and control, the aim of which is to simultaneously maximize the overall satisfaction rate of the medical supplies and minimize the total scheduling cost, while keeping a minimum ratio of medical supplies reservation for military use. We propose a multi-objective water wave optimization (WWO) algorithm in order to efficiently solve this problem. Computational results on a set of problem instances constructed based on real COVID-19 data demonstrate the effectiveness of the proposed method.

scholarly journals Reliability Analysis and Repair Activity for the Components of 350 kW Inverters in a Large Scale Grid-Connected Photovoltaic System

Electronics ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 564
Author(s):  
Filippo Spertino ◽  
Angela Amato ◽  
Gabriele Casali ◽  
Alessandro Ciocia ◽  
Gabriele Malgaroli
Keyword(s):  
Reliability Analysis ◽  
Large Scale ◽  
Photovoltaic System ◽  
Component Level ◽  
Ac Power ◽  
Repair Activity ◽  
Industrial Maintenance ◽  
Large Scale Grid ◽  
Ac Converters ◽  
Scale Grid

The reliability of photovoltaic (PV) generators is strongly affected by the performance of Direct Current/Alternating Current (DC/AC) converters, being the major source of PV underperformance. However, generally, their reliability is not investigated at component level: thus, the present work presents a reliability analysis and the repair activity for the components of full bridge DC/AC converters. In the first part of the paper, a reliability analysis using failure rates from literature is carried out for 132 inverters (AC rated power of 350 kW each) with global AC power of 46 MW in a large scale grid-connected PV plant. Then, in the second part of the work, results from literature are compared with data obtained by analyzing industrial maintenance reports in the years 2015–2017. In conclusion, the yearly energy losses involved in the downtime are quantified, as well as their availability.

scholarly journals High-Rate Transition Metal-based Cathode Materials for Battery-Supercapacitor Hybrid Devices

2021 ◽  
Author(s):  
Cong Wang ◽  
Zehao Song ◽  
Pei Shi ◽  
Lin Lv ◽  
Houzhao Wan ◽  
...  
Keyword(s):  
Large Scale ◽  
Rapid Development ◽  
Electronic Devices ◽  
High Rate ◽  
Specific Power ◽  
Energy Storage Devices ◽  
Storage Devices ◽  
Electrochemical Devices ◽  
Hybrid Devices ◽  
Scale Grid

With the rapid development of portable electronic devices, electric vehicles and large-scale grid energy storage devices, it needs to reinforce specific energy and specific power of related electrochemical devices meeting...

scholarly journals A novel encoding for separable large-scale multi-objective problems and its application to the optimisation of housing stock improvements

2020 ◽  
Vol 96 ◽  
pp. 106650
Author(s):  
Alexander E.I. Brownlee ◽  
Jonathan A. Wright ◽  
Miaomiao He ◽  
Timothy Lee ◽  
Paul McMenemy
Keyword(s):  
Large Scale ◽  
Housing Stock ◽  
Multi Objective

A multi-objective sparse evolutionary framework for large-scale weapon target assignment based on a reward strategy

2021 ◽  
Vol 40 (5) ◽  
pp. 10043-10061
Author(s):  
Xiaoping Shi ◽  
Shiqi Zou ◽  
Shenmin Song ◽  
Rui Guo
Keyword(s):  
Large Scale ◽  
The Novel ◽  
Genetic Operators ◽  
Multi Objective ◽  
Target Assignment ◽  
Solution Selection ◽  
Battlefield Environment ◽  
Sparse Problems ◽  
Novel Model ◽  
Error Parameter

 The asset-based weapon target assignment (ABWTA) problem is one of the important branches of the weapon target assignment (WTA) problem. Due to the current large-scale battlefield environment, the ABWTA problem is a multi-objective optimization problem (MOP) with strong constraints, large-scale and sparse properties. The novel model of the ABWTA problem with the operation error parameter is established. An evolutionary algorithm for large-scale sparse problems (SparseEA) is introduced as the main framework for solving large-scale sparse ABWTA problem. The proposed framework (SparseEA-ABWTA) mainly addresses the issue that problem-specific initialization method and genetic operators with a reward strategy can generate solutions efficiently considering the sparsity of variables and an improved non-dominated solution selection method is presented to handle the constraints. Under the premise of constructing large-scale cases by the specific case generator, two numerical experiments on four outstanding multi-objective evolutionary algorithms (MOEAs) show Runtime of SparseEA-ABWTA is faster nearly 50% than others under the same convergence and the gap between MOEAs improved by the mechanism of SparseEA-ABWTA and SparseEA-ABWTA is reduced to nearly 20% in the convergence and distribution.

Multi-objective ant lion optimization algorithm to solve large-scale multi-objective optimal reactive power dispatch problem

2019 ◽  
Vol 38 (1) ◽  
pp. 304-324 ◽  
Author(s):  
Souhil Mouassa ◽  
Tarek Bouktir
Keyword(s):  
Power Systems ◽  
Large Scale ◽  
Reactive Power ◽  
Stability Index ◽  
Active Power ◽  
Power Losses ◽  
Content Type ◽  
Multi Objective ◽  
Ant Lion Optimization ◽  
Active Power Losses

Purpose In the vast majority of published papers, the optimal reactive power dispatch (ORPD) problem is dealt as a single-objective optimization; however, optimization with a single objective is insufficient to achieve better operation performance of power systems. Multi-objective ORPD (MOORPD) aims to minimize simultaneously either the active power losses and voltage stability index, or the active power losses and the voltage deviation. The purpose of this paper is to propose multi-objective ant lion optimization (MOALO) algorithm to solve multi-objective ORPD problem considering large-scale power system in an effort to achieve a good performance with stable and secure operation of electric power systems. Design/methodology/approach A MOALO algorithm is presented and applied to solve the MOORPD problem. Fuzzy set theory was implemented to identify the best compromise solution from the set of the non-dominated solutions. A comparison with enhanced version of multi-objective particle swarm optimization (MOEPSO) algorithm and original (MOPSO) algorithm confirms the solutions. An in-depth analysis on the findings was conducted and the feasibility of solutions were fully verified and discussed. Findings Three test systems – the IEEE 30-bus, IEEE 57-bus and large-scale IEEE 300-bus – were used to examine the efficiency of the proposed algorithm. The findings obtained amply confirmed the superiority of the proposed approach over the multi-objective enhanced PSO and basic version of MOPSO. In addition to that, the algorithm is benefitted from good distributions of the non-dominated solutions and also guarantees the feasibility of solutions. Originality/value The proposed algorithm is applied to solve three versions of ORPD problem, active power losses, voltage deviation and voltage stability index, considering large -scale power system IEEE 300 bus.

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