scholarly journals Design and Analysis of Flexible Multi-Microgrid Interconnection Scheme for Mitigating Power Fluctuation and Optimizing Storage Capacity

Energies ◽  
2019 ◽  
Vol 12 (11) ◽  
pp. 2132 ◽  
Author(s):  
Jianqiao Zhou ◽  
Jianwen Zhang ◽  
Xu Cai ◽  
Gang Shi ◽  
Jiacheng Wang ◽  
...  
Keyword(s):  
Distribution Systems ◽  
Storage Capacity ◽  
Control Strategies ◽  
Unit Cost ◽  
Cost Effective ◽  
Basic Structure ◽  
Energy Integration ◽  
Power Fluctuation ◽  
Data Set ◽  
Power Fluctuations

With the rapid increase of renewable energy integration, more serious power fluctuations are introduced in distribution systems. To mitigate power fluctuations caused by renewables, a microgrid with energy storage systems (ESSs) is an attractive solution. However, existing solutions are still not sufficiently cost-effective for compensating enormous power fluctuations considering the high unit cost of ESS. This paper proposes a new flexible multi-microgrid interconnection scheme to address this problem while optimizing the utilization of ESSs as well. The basic structure and functions of the proposed scheme are illustrated first. With the suitable power allocation method in place to realize fluctuation sharing among microgrids, the effectiveness of this scheme in power smoothing is analyzed mathematically. The corresponding power control strategies of multiple converters integrated into the DC common bus are designed, and the power fluctuation sharing could be achieved by all AC microgrids and DC-side ESS. In addition, a novel ESS sizing method which can deal with discrete data set is introduced. The proposed interconnection scheme is compared with a conventional independent microgrid scheme through real-world case studies. The results demonstrate the effectiveness of the interconnected microgrid scheme in mitigating power fluctuation and optimizing storage capacity, while at the expense of slightly increased capacity requirement for the AC/DC converters and construction cost for DC lines. According to the economic analysis, the proposed scheme is most suitable for areas where the distances between microgrids are short.

scholarly journals Controlling the Spatial Spread of a Xylella Epidemic

2021 ◽  
Vol 83 (4) ◽  
Author(s):  
Sebastian Aniţa ◽  
Vincenzo Capasso ◽  
Simone Scacchi
Keyword(s):  
Spatial Structure ◽  
Numerical Simulations ◽  
Control Strategies ◽  
Xylella Fastidiosa ◽  
Cost Effective ◽  
Olive Tree ◽  
Control Measures ◽  
Weed Biomass ◽  
Spatial Spread ◽  
Olive Trees

AbstractIn a recent paper by one of the authors and collaborators, motivated by the Olive Quick Decline Syndrome (OQDS) outbreak, which has been ongoing in Southern Italy since 2013, a simple epidemiological model describing this epidemic was presented. Beside the bacterium Xylella fastidiosa, the main players considered in the model are its insect vectors, Philaenus spumarius, and the host plants (olive trees and weeds) of the insects and of the bacterium. The model was based on a system of ordinary differential equations, the analysis of which provided interesting results about possible equilibria of the epidemic system and guidelines for its numerical simulations. Although the model presented there was mathematically rather simplified, its analysis has highlighted threshold parameters that could be the target of control strategies within an integrated pest management framework, not requiring the removal of the productive resource represented by the olive trees. Indeed, numerical simulations support the outcomes of the mathematical analysis, according to which the removal of a suitable amount of weed biomass (reservoir of Xylella fastidiosa) from olive orchards and surrounding areas resulted in the most efficient strategy to control the spread of the OQDS. In addition, as expected, the adoption of more resistant olive tree cultivars has been shown to be a good strategy, though less cost-effective, in controlling the pathogen. In this paper for a more realistic description and a clearer interpretation of the proposed control measures, a spatial structure of the epidemic system has been included, but, in order to keep mathematical technicalities to a minimum, only two players have been described in a dynamical way, trees and insects, while the weed biomass is taken to be a given quantity. The control measures have been introduced only on a subregion of the whole habitat, in order to contain costs of intervention. We show that such a practice can lead to the eradication of an epidemic outbreak. Numerical simulations confirm both the results of the previous paper and the theoretical results of the model with a spatial structure, though subject to regional control only.

scholarly journals Optimization of Energy Storage Capacity to Smooth Wind Power Fluctuation

2021 ◽  
Vol 687 (1) ◽  
pp. 012103
Author(s):  
Zenggong Cao ◽  
Chunyi Wang ◽  
Bo Peng ◽  
Yasong Wang ◽  
Peng Du ◽  
...  
Keyword(s):  
Energy Storage ◽  
Wind Power ◽  
Storage Capacity ◽  
Power Fluctuation ◽  
Energy Storage Capacity

CLINICAL OUTCOME AND COST COMPARISON OF CARPAL TUNNEL WOUND CLOSURE WITH MONOCRYL® AND ETHILON®: A PROSPECTIVE STUDY

Hand Surgery ◽  
2013 ◽  
Vol 18 (02) ◽  
pp. 189-192 ◽  
Author(s):  
Anis Dosani ◽  
Sameer K. Khan ◽  
Sheila Gray ◽  
Steve Joseph ◽  
Ian A. Whittaker
Keyword(s):  
Carpal Tunnel ◽  
Wound Closure ◽  
Unit Cost ◽  
Cost Effective ◽  
Cost Comparison ◽  
Absorbable Suture ◽  
Significant Difference ◽  
Group A ◽  
Group B ◽  
A Prospective Study

This prospective non-randomised two-cohort study compares the use of an absorbable suture (Poliglecrapone [Monocryl]: Group A) and a non-absorbable suture (Polyamide [Ethilon]: Group B) in wound closure after elective carpal tunnel decompression. The primary outcome was scar cosmesis as assessed by the Stonybrook Scar Evaluation Scale (SBSES); the financial cost of wound closure was compared as a secondary outocome. All fifty patients completed follow-up. At six weeks, there was no significant difference in the two groups regarding scar tenderness (p = 0.5), although residual swelling was more evident in the absorbable group (p = 0.2). The mean SBSES score at six weeks was 4.72 in Group A, and 4.8 in Group B (p = 0.3). The unit cost per closed wound of Monocryl was three times than Ethilon (p < 0.05). Ethilon is thus cost-effective without compromising the cosmetic outcome, and we recommend using this as the preferred suture for closure of carpal tunnel wounds.

Application of multivariable statistical techniques in plant-wide WWTP control strategies analysis

2007 ◽  
Vol 56 (6) ◽  
pp. 75-83 ◽  
Author(s):  
X. Flores ◽  
J. Comas ◽  
I.R. Roda ◽  
L. Jiménez ◽  
K.V. Gernaey
Keyword(s):  
Cluster Analysis ◽  
Control Strategies ◽  
Treatment Plant ◽  
Principal Component ◽  
Statistical Techniques ◽  
Data Sets ◽  
Data Set ◽  
Casual Relation ◽  
Evaluation Matrix ◽  
Natural Groups

The main objective of this paper is to present the application of selected multivariable statistical techniques in plant-wide wastewater treatment plant (WWTP) control strategies analysis. In this study, cluster analysis (CA), principal component analysis/factor analysis (PCA/FA) and discriminant analysis (DA) are applied to the evaluation matrix data set obtained by simulation of several control strategies applied to the plant-wide IWA Benchmark Simulation Model No 2 (BSM2). These techniques allow i) to determine natural groups or clusters of control strategies with a similar behaviour, ii) to find and interpret hidden, complex and casual relation features in the data set and iii) to identify important discriminant variables within the groups found by the cluster analysis. This study illustrates the usefulness of multivariable statistical techniques for both analysis and interpretation of the complex multicriteria data sets and allows an improved use of information for effective evaluation of control strategies.

Generation of a Complete Profile for Porosity Log While Drilling Complex Lithology by Employing the Artificial Intelligence

2021 ◽  
Author(s):  
Ahmed Al-Sabaa ◽  
Hany Gamal ◽  
Salaheldin Elkatatny
Keyword(s):  
Artificial Intelligence ◽  
Prediction Model ◽  
Real Time ◽  
Storage Capacity ◽  
Data Set ◽  
Drilling Parameters ◽  
Unseen Data ◽  
Rock Porosity ◽  
Data Points ◽  
Logging Tool

Abstract The formation porosity of drilled rock is an important parameter that determines the formation storage capacity. The common industrial technique for rock porosity acquisition is through the downhole logging tool. Usually logging while drilling, or wireline porosity logging provides a complete porosity log for the section of interest, however, the operational constraints for the logging tool might preclude the logging job, in addition to the job cost. The objective of this study is to provide an intelligent prediction model to predict the porosity from the drilling parameters. Artificial neural network (ANN) is a tool of artificial intelligence (AI) and it was employed in this study to build the porosity prediction model based on the drilling parameters as the weight on bit (WOB), drill string rotating-speed (RS), drilling torque (T), stand-pipe pressure (SPP), mud pumping rate (Q). The novel contribution of this study is to provide a rock porosity model for complex lithology formations using drilling parameters in real-time. The model was built using 2,700 data points from well (A) with 74:26 training to testing ratio. Many sensitivity analyses were performed to optimize the ANN model. The model was validated using unseen data set (1,000 data points) of Well (B), which is located in the same field and drilled across the same complex lithology. The results showed the high performance for the model either for training and testing or validation processes. The overall accuracy for the model was determined in terms of correlation coefficient (R) and average absolute percentage error (AAPE). Overall, R was higher than 0.91 and AAPE was less than 6.1 % for the model building and validation. Predicting the rock porosity while drilling in real-time will save the logging cost, and besides, will provide a guide for the formation storage capacity and interpretation analysis.

Monitoring, Diagnostics, and Prognostics for Robot Tool Center Accuracy Degradation

2018 ◽  
Author(s):  
Guixiu Qiao ◽  
Brian A. Weiss
Keyword(s):  
Health Management ◽  
Control Strategies ◽  
Test Methods ◽  
Component Level ◽  
Data Set ◽  
Root Cause ◽  
Robot Systems ◽  
Robot Performance ◽  
And Control ◽  
Constituent Elements

Over time, robots degrade because of age and wear, leading to decreased reliability and increasing potential for faults and failures; this negatively impacts robot availability. Economic factors motivate facilities and factories to improve maintenance operations to monitor robot degradation and detect faults and failures, especially to eliminate unexpected shutdowns. Since robot systems are complex, with sub-systems and components, it is challenging to determine these constituent elements’ specific influence on the overall system performance. The development of monitoring, diagnostic, and prognostic technologies (collectively known as Prognostics and Health Management (PHM)), can aid manufacturers in maintaining the performance of robot systems by providing intelligence to enhance maintenance and control strategies. This paper presents the strategy of integrating top level and component level PHM to detect robot performance degradation (including robot tool center accuracy degradation), supported by the development of a four-layer sensing and analysis structure. The top level PHM can quickly detect robot tool center accuracy degradation through advanced sensing and test methods developed at the National Institute of Standards and Technology (NIST). The component level PHM supports deep data analysis for root cause diagnostics and prognostics. A reference data set is collected and analyzed using the integration of top level PHM and component level PHM to understand the influence of temperature, speed, and payload on robot’s accuracy degradation.

A Study on Small Scale Associated Gas FLNG Utilizing Small Scale LNG Carriers to Near-By Onshore LNG Plant

2016 ◽  
Author(s):  
X. C. Nguyen ◽  
Komla Miheaye ◽  
Mun-gyu Kim ◽  
Howard Newman ◽  
Dong-hoon Yoo ◽  
...  
Keyword(s):  
Short Range ◽  
Storage Capacity ◽  
Effective Means ◽  
Production Capacity ◽  
Cost Effective ◽  
Oil Fields ◽  
Small Scale ◽  
Associated Gas ◽  
Small Capacity ◽  
Stranded Gas

This study describes a FLNG specifically designed to monetize Associated Gas (AG) of producing oil fields located within convenient distance of an existing LNG Plant or Port with LNG storage facility. Limited production capacity combined with short range small capacity shuttles and limited LNG storage capacity, provide a cost effective means for LNG production. This FLNG is designed to service an existing industry and does not require development of stranded gas discoveries.

scholarly journals Application-Oriented Reactive Power Management in German Distribution Systems Using Decentralized Energy Resources

Energies ◽  
2021 ◽  
Vol 14 (16) ◽  
pp. 4949
Author(s):  
Haonan Wang ◽  
Markus Kraiczy ◽  
Denis Mende ◽  
Sebastian Stöcklein ◽  
Martin Braun
Keyword(s):  
Power Management ◽  
Distribution System ◽  
Distribution Systems ◽  
Reactive Power ◽  
Control Strategies ◽  
Renewable Energy Sources ◽  
Measurement Data ◽  
Power Exchange ◽  
High Investment ◽  
Decentralized Energy

Due to higher penetration of renewable energy sources, grid reinforcements, and the utilization of local voltage control strategies, a significant change in the reactive power behavior as well as an increased demand for additional reactive power flexibility in the German power system can be predicted. In this paper, an application-oriented reactive power management concept is proposed, which allows distribution system operators (DSO) to enable a certain amount of reactive power flexibility at the grid interfaces while supporting voltage imitations in the grid. To evaluate its feasibility, the proposed concept is applied for real medium voltage grids in the south of Germany and is investigated comprehensively in different case studies. The results prove the feasibility and reliability of the proposed concept, which allows the DSO to control the reactive power exchange at grid interfaces without causing undesired local voltage problems. In addition, it can be simply adjusted and widely applied in real distribution grids without requiring high investment costs for complex information and communication infrastructures. As a significant contribution, this study provides an ideal bridging solution for DSOs who are facing reactive power issues but have no detailed and advanced monitoring system for their grid. Moreover, the comprehensive investigations in this study are performed in close cooperation with a German DSO, based on a detailed grid model and real measurement data.

scholarly journals Optimization through Bayesian Classification on the k-Anonymized Data

2012 ◽  
pp. 245-249
Author(s):  
L Mohana Tirumala ◽  
S. Srinivasa Rao
Keyword(s):  
Cost Effective ◽  
Privacy Preserving ◽  
Bayesian Classification ◽  
Data Sets ◽  
Data Set ◽  
Equal Importance ◽  
Cost Effective Approach ◽  
Effective Manner ◽  
Anonymized Data ◽  
Refinement Algorithm

Privacy preserving in Data mining & publishing, plays a major role in today networked world. It is important to preserve the privacy of the vital information corresponding to a data set. This process can be achieved by k-anonymization solution for classification. Along with the privacy preserving using anonymization, yielding the optimized data sets is also of equal importance with a cost effective approach. In this paper Top-Down Refinement algorithm has been proposed which yields optimum results in a cost effective manner. Bayesian Classification has been proposed in this paper to predict class membership probabilities for a data tuple for which the associated class label is unknown.

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