scholarly journals Application Multicriteria Decision Making Method to Determine the Placement of Power Distribution System

2017 ◽  
Vol 3 (2) ◽  
pp. 23
Author(s):  
Gholamreza Jandaghi
Keyword(s):  
Decision Making ◽  
Power Distribution ◽  
Distribution System ◽  
Multicriteria Decision Making ◽  
Power Distribution System ◽  
Multicriteria Decision

scholarly journals Resiliency Metrics for Monitoring and Analysis of Cyber-Power Distribution System with IoTs

2021 ◽  
Author(s):  
Partha S. Sarker ◽  
Sajan K Sadanandan ◽  
Anurag K. Srivastava
Keyword(s):  
Decision Making ◽  
Power Distribution ◽  
Distribution System ◽  
Data Privacy ◽  
Multiple Criteria Decision Making ◽  
Mitigation Strategies ◽  
Power Distribution System ◽  
User Data ◽  
Game Theoretic ◽  
Grid Operation

<div>The electric grid operation is constantly threatened with natural disasters and cyber intrusions. The introduction of Internet of Things (IoTs) based distributed energy resources (DERs) in the distribution system provides opportunities for flexible services to enable efficient, reliable and resilient operation. At the same time, IoT based DERs comes with cyber vulnerabilities and requires cyber-power resiliency analysis of the IoT-integrated distribution system. This work focuses on developing metrics for monitoring resiliency of cyber-power distribution system, while maintaining consumers’ privacy. Here, resiliency refers to the system’s ability to keep providing energy to the critical load even with adverse events. In the developed cyber-power Distribution System Resiliency (DSR) metric, the IoT Trustability Score (ITS) considers the effects of IoTs using a neural network with federated learning. ITS and other factors impacting resiliency are integrated into a single metric using Fuzzy Multiple-Criteria Decision Making (F-MCDM) to compute Primary level Node Resiliency (PNR). Finally, DSR is computed by aggregating PNR of all primary nodes and attributes of distribution level network topology and vulnerabilities utilizing game-theoretic Data Envelopment Analysis (DEA) based optimization. The developed metrics will be valuable for i) monitoring the distribution system resiliency considering a holistic cyber-power model; ii) enabling data privacy by not utilizing the raw user data; and iii) enabling better decision-making to select the best possible mitigation strategies towards resilient distribution system. The developed ITS, PNR, and DSR metrics have been validated using multiple case studies for the IoTs-integrated IEEE 123 node distribution system with satisfactory results.</div>

scholarly journals Resiliency Metrics for Monitoring and Analysis of Cyber-Power Distribution System with IoTs

2021 ◽  
Author(s):  
Partha S. Sarker ◽  
Sajan K Sadanandan ◽  
Anurag K. Srivastava
Keyword(s):  
Decision Making ◽  
Power Distribution ◽  
Distribution System ◽  
Data Privacy ◽  
Multiple Criteria Decision Making ◽  
Mitigation Strategies ◽  
Power Distribution System ◽  
User Data ◽  
Game Theoretic ◽  
Grid Operation

<div>The electric grid operation is constantly threatened with natural disasters and cyber intrusions. The introduction of Internet of Things (IoTs) based distributed energy resources (DERs) in the distribution system provides opportunities for flexible services to enable efficient, reliable and resilient operation. At the same time, IoT based DERs comes with cyber vulnerabilities and requires cyber-power resiliency analysis of the IoT-integrated distribution system. This work focuses on developing metrics for monitoring resiliency of cyber-power distribution system, while maintaining consumers’ privacy. Here, resiliency refers to the system’s ability to keep providing energy to the critical load even with adverse events. In the developed cyber-power Distribution System Resiliency (DSR) metric, the IoT Trustability Score (ITS) considers the effects of IoTs using a neural network with federated learning. ITS and other factors impacting resiliency are integrated into a single metric using Fuzzy Multiple-Criteria Decision Making (F-MCDM) to compute Primary level Node Resiliency (PNR). Finally, DSR is computed by aggregating PNR of all primary nodes and attributes of distribution level network topology and vulnerabilities utilizing game-theoretic Data Envelopment Analysis (DEA) based optimization. The developed metrics will be valuable for i) monitoring the distribution system resiliency considering a holistic cyber-power model; ii) enabling data privacy by not utilizing the raw user data; and iii) enabling better decision-making to select the best possible mitigation strategies towards resilient distribution system. The developed ITS, PNR, and DSR metrics have been validated using multiple case studies for the IoTs-integrated IEEE 123 node distribution system with satisfactory results.</div>

scholarly journals New algorithm for distribution system reconstruction planning based on fuzzy inference and multicriteria decision making

2018 ◽  
Vol 38 (2) ◽  
pp. 232-241 ◽  
Author(s):  
Mirza Šaric ◽  
Jasna Hivziefendić ◽  
Jasmin Kevrić
Keyword(s):  
Decision Making ◽  
Power Distribution ◽  
Distribution System ◽  
Planning Process ◽  
Fuzzy Inference ◽  
Multicriteria Decision Making ◽  
System Reconstruction ◽  
Distribution Network Planning ◽  
Number Of Customers ◽  
Reconstruction Planning

This paper presents a new algorithm for distribution system reconstruction planning based on Mamdani type fuzzy inference and BellmanZadeh multi criteria decision making method. The proposed algorithm takes system attributes as inputs (number of customers served by renewed infrastructure, energy losses, power demand and cost of investment) and returns crisp output values which are used as planning criteria. The aim of this paper is to provide a logical decision making framework which can be used to model, evaluate, and rank projects according to required criteria. The proposed model is flexible and can be extended to include additional planning criteria. The proposed method is tested on a realistic distribution system to demonstrate its relevance. It is expected that this paper will make a contribution toward more effective management of power distribution network planning process and that it will be used by planning engineers in practical problems.

scholarly journals Decision Making in Power Distribution System Reconfiguration by Blended Biased and Unbiased Weightage Method

2019 ◽  
Vol 8 (2) ◽  
pp. 20 ◽  
Author(s):  
Kamble ◽  
Vadirajacharya ◽  
Patil
Keyword(s):  
Decision Making ◽  
Power Distribution ◽  
Distribution System ◽  
Distribution Systems ◽  
Voltage Drop ◽  
Multiple Attribute Decision Making ◽  
Power Distribution System ◽  
Reliability Indices ◽  
Weighted Sum Method ◽  
Multiple Attribute

The term smart grid (SG) has been used by many government bodies and researchers to refer to the new trend in the power industry of modernizing and automating the existing power system. SGs must utilize assets optimally by making use of the information, like equipment capacity, voltage drop, radial network structure, minimizing investment and operating costs, minimizing energy loss and reliability indices, and so on. One way to achieve this is to re-route or reconfigure distribution systems (DSs). Distribution systems are reconfigured to choose a switching combination of branches of the system that optimize certain performance parameters of the power supply, while satisfying some specified constraints. In this paper, a blended biased and unbiased weightage (BBUW) multiple attribute decision-making (MADM) method is proposed for finding the compromised best configuration and compared it with other decision-making methods, such as the weighted sum method (WSM), weighted product method (WPM), and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method. The BBUW method is implemented for two distribution systems, and the result obtained shows a good co-relationship between BBUW and other decision-making methods. Further weights obtained from the BBUW method are used for the WSM, WPM and TOPSIS methods for decision making. Examples of the distribution system are worked out in this paper to demonstrate the validity and effectiveness of the method.

SFCL for Energy Storage Protection in a Power Distribution System

2016 ◽  
Vol 4 (1) ◽  
pp. 15-24
Author(s):  
V. Mohanbabu ◽  
◽  
Sk. Moulali ◽  
Ju Chan Na ◽  
Peng Cheng ◽  
...  
Keyword(s):  
Energy Storage ◽  
Power Distribution ◽  
Distribution System ◽  
Power Distribution System
Sign in / Sign up

Export Citation Format

Share Document