A distribution system outage dispatch by data base method with real-time revision

1989 ◽  
Vol 4 (1) ◽  
pp. 515-523 ◽  
Author(s):  
C.E. Ling ◽  
Y.-W. Huang ◽  
H.L. Chow ◽  
C.L. Huang
Keyword(s):  
Data Base ◽  
Real Time ◽  
Distribution System ◽  
Base Method

scholarly journals Data-Driven Dispatching Rules Mining and Real-Time Decision-Making Methodology in Intelligent Manufacturing Shop Floor with Uncertainty

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4836
Author(s):  
Liping Zhang ◽  
Yifan Hu ◽  
Qiuhua Tang ◽  
Jie Li ◽  
Zhixiong Li
Keyword(s):  
Decision Making ◽  
Data Base ◽  
Real Time ◽  
Manufacturing Industry ◽  
Job Shop ◽  
Data Driven ◽  
Dispatching Rules ◽  
Shop Floor ◽  
Production Data ◽  
Online Decision Making

In modern manufacturing industry, the methods supporting real-time decision-making are the urgent requirement to response the uncertainty and complexity in intelligent production process. In this paper, a novel closed-loop scheduling framework is proposed to achieve real-time decision making by calling the appropriate data-driven dispatching rules at each rescheduling point. This framework contains four parts: offline training, online decision-making, data base and rules base. In the offline training part, the potential and appropriate dispatching rules with managers’ expectations are explored successfully by an improved gene expression program (IGEP) from the historical production data, not just the available or predictable information of the shop floor. In the online decision-making part, the intelligent shop floor will implement the scheduling scheme which is scheduled by the appropriate dispatching rules from rules base and store the production data into the data base. This approach is evaluated in a scenario of the intelligent job shop with random jobs arrival. Numerical experiments demonstrate that the proposed method outperformed the existing well-known single and combination dispatching rules or the discovered dispatching rules via metaheuristic algorithm in term of makespan, total flow time and tardiness.

scholarly journals Comparison of Searching Behaviour of Three Evolutionary Algorithms Applied to Water Distribution System Design Optimization

Water ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 695 ◽  
Author(s):  
Weiwei Bi ◽  
Yihui Xu ◽  
Hongyu Wang
Keyword(s):  
Evolutionary Algorithms ◽  
Real Time ◽  
Distribution System ◽  
Optimization Design ◽  
Distribution Systems ◽  
Water Distribution ◽  
Optimal Solutions ◽  
Great Ability ◽  
Searching Behaviour ◽  
Run Time

Over the past few decades, various evolutionary algorithms (EAs) have been applied to the optimization design of water distribution systems (WDSs). An important research area is to compare the performance of these EAs, thereby offering guidance for the selection of the appropriate EAs for practical implementations. Such comparisons are mainly based on the final solution statistics and, hence, are unable to provide knowledge on how different EAs reach the final optimal solutions and why different EAs performed differently in identifying optimal solutions. To this end, this paper aims to compare the real-time searching behaviour of three widely used EAs, which are genetic algorithms (GAs), the differential evolution (DE) algorithm and the ant colony optimization (ACO). These three EAs are applied to five WDS benchmarking case studies with different scales and complexities, and a set of five metrics are used to measure their run-time searching quality and convergence properties. Results show that the run-time metrics can effectively reveal the underlying searching mechanisms associated with each EA, which significantly goes beyond the knowledge from the traditional end-of-run solution statistics. It is observed that the DE is able to identify better solutions if moderate and large computational budgets are allowed due to its great ability in maintaining the balance between the exploration and exploitation. However, if the computational resources are rather limited or the decision has to be made in a very short time (e.g., real-time WDS operation), the GA can be a good choice as it can always identify better solutions than the DE and ACO at the early searching stages. Based on the results, the ACO performs the worst for the five case study considered. The outcome of this study is the offer of guidance for the algorithm selection based on the available computation resources, as well as knowledge into the EA’s underlying searching behaviours.

scholarly journals Multiresolution Network Temporal and Spatial Scheduling Model of Scenic Spot

2013 ◽  
Vol 2013 ◽  
pp. 1-8
Author(s):  
Peng Ge ◽  
Zhixue Liao ◽  
Chang Liu ◽  
Peiyu Ren ◽  
Zhaoxia Guo
Keyword(s):  
Real Time ◽  
Distribution System ◽  
Low Carbon ◽  
The Real ◽  
Scheduling Model ◽  
Scenic Spot ◽  
Full Capacity ◽  
Develop Economy ◽  
Temporal And Spatial ◽  
Demand And Capacity

Tourism is one of pillar industries of the world economy. Low-carbon tourism will be the mainstream direction of the scenic spots' development, and theωpath of low-carbon tourism development is to develop economy and protect environment simultaneously. However, as the tourists' quantity is increasing, the loads of scenic spots are out of control. And the instantaneous overload in some spots caused the image phenomenon of full capacity of the whole scenic spot. Therefore, realizing the real-time schedule becomes the primary purpose of scenic spot’s management. This paper divides the tourism distribution system into several logically related subsystems and constructs a temporal and spatial multiresolution network scheduling model according to the regularity of scenic spots’ overload phenomenon in time and space. It also defines dynamic distribution probability and equivalent dynamic demand to realize the real-time prediction. We define gravitational function between fields and takes it as the utility of schedule, after resolving the transportation model of each resolution, it achieves hierarchical balance between demand and capacity of the system. The last part of the paper analyzes the time complexity of constructing a multiresolution distribution system.

scholarly journals A Wireless Sensor Network Model for E-Metering and Fault Identification in Smart Water Distribution Systems

2019 ◽  
Vol 8 (10S) ◽  
pp. 227-232
Keyword(s):  
Wireless Sensor Network ◽  
Real Time ◽  
Sensor Network ◽  
Network Model ◽  
Distribution System ◽  
Water Distribution ◽  
Large Scale ◽  
Water Distribution System ◽  
Wireless Sensor ◽  
Smart Water

Water distribution system is a network that supplies water to all the consumers through different means. Proper means of providing water to houses without compromising in quantity and quality is always a challenge. As it is a huge network keeping track of the utilization is difficult for the utility. Hence through this project we come up with a solution to solve this issue. Current technologies like Low Power Wide Area Networks, LoRa and sensor deployment techniques have been in research and were also tested in few rural areas but issues due to hardware deployment and large scale real time implementation was a challenge hence through this system we aim to create and simulate a real time scenario to test a sensor network model that could be implemented in large scale further. This project aims in building a wireless sensor network model for a smart water distribution system. In this system there is bidirectional communication between the consumer and the utility. Each house has a meter through which the amount of water consumed is sent to the utility board. The data has two fields containing the house ID and the data (water consumed); it is being sent to the data collection unit (DCU) which in-turn sends it to the central server so that the consumption is monitored in real time. All this is simulated using NETSIM and MATLAB.

scholarly journals DC Microgrid Utilizing Artificial Intelligence and Phasor Measurement Unit Assisted Inverter

Energies ◽  
2021 ◽  
Vol 14 (19) ◽  
pp. 6086
Author(s):  
Raziq Yaqub ◽  
Mohamed Ali ◽  
Hassan Ali
Keyword(s):  
Artificial Intelligence ◽  
Real Time ◽  
Distribution System ◽  
Reference Signal ◽  
Phasor Measurement Unit ◽  
Measurement Unit ◽  
Time Data ◽  
Dc Microgrid ◽  
Utility Company ◽  
Phasor Measurement

Community microgrids are set to change the landscape of future energy markets. The technology is being deployed in many cities around the globe. However, a wide-scale deployment faces three major issues: initial synchronization of microgrids with the utility grids, slip management during its operation, and mitigation of distortions produced by the inverter. This paper proposes a Phasor Measurement Unit (PMU) Assisted Inverter (PAI) that addresses these three issues in a single solution. The proposed PAI continually receives real-time data from a Phasor Measurement Unit installed in the distribution system of a utility company and keeps constructing a real-time reference signal for the inverter. To validate the concept, a unique intelligent DC microgrid architecture that employs the proposed Phasor Measurement Unit (PMU) Assisted Inverter (PAI) is also presented, alongside the cloud-based Artificial Intelligence (AI), which harnesses energy from community shared resources, such as batteries and the community’s rooftop solar resources. The results show that the proposed system produces quality output and is 98.5% efficient.

A new approach for real time voltage control using demand response in an automated distribution system

2014 ◽  
Vol 117 ◽  
pp. 157-166 ◽  
Author(s):  
Alireza Zakariazadeh ◽  
Omid Homaee ◽  
Shahram Jadid ◽  
Pierluigi Siano
Keyword(s):  
Real Time ◽  
Demand Response ◽  
Distribution System ◽  
Voltage Control ◽  
New Approach
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