Solutions of Non-smooth Economic Dispatch Problems by Swarm Intelligence

2015 ◽  
pp. 129-146 ◽  
Author(s):  
Seyyed Soheil Sadat Hosseini ◽  
Xin-She Yang ◽  
Amir H. Gandomi ◽  
Alireza Nemati
Keyword(s):  
Swarm Intelligence ◽  
Economic Dispatch

scholarly journals Multi-Area Economic Dispatch Performance Using Swarm Intelligence Technique Considering Voltage Stability

2017 ◽  
Vol 7 (1) ◽  
pp. 1 ◽  
Author(s):  
Mohd Khairuzzaman Mohd Zamani ◽  
Ismail Musirin ◽  
Saiful Izwan Suliman ◽  
Muhammad Murtadha Othman ◽  
Mohd Fadhil Mohd Kamal
Keyword(s):  
Swarm Intelligence ◽  
Voltage Stability ◽  
Economic Dispatch ◽  
Intelligence Technique

A comprehensive review on swarm intelligence methods applied to practical economic load dispatch problem

2020 ◽  
Vol 13 ◽  
Author(s):  
Arun Kumar Sahoo ◽  
Tapas Kumar Panigrahi ◽  
Gopal Krishna Nayak ◽  
Chinmay Kumar Nayak
Keyword(s):  
Swarm Intelligence ◽  
Electricity Market ◽  
Economic Dispatch ◽  
Complex Problem ◽  
Economic Load Dispatch ◽  
Comprehensive Review ◽  
Nature Inspired Algorithm ◽  
Restructuring Process ◽  
Economic Dispatch Problem ◽  
Operational Constraints

Background: In the modern era, a power production industry is to be extremely vibrant and reliable in the electricity market aspect with the introduction of restructuring process. Methods: In the recent past, a power plant with the combination of generating units should pace under economic condition. The optimal economic dispatch is highly essential as deplete of fossil fuel with increase in electric demand. The main objective of Economic Load Dispatch (ELD) problem in the power system is to minimize the generating cost. Results: Economic dispatch scheduled the electric power as per the load demand satisfying all the practical and operational constraints. This paper presents and explores the comprehensive review of swarm intelligence methods applied to solve the economic dispatch problem. Swarm intelligence techniques as a part of nature-inspired algorithm, inspired from the behavior of swarm for the application it in real complex problem. Conclusion: Many swarm intelligence methods were applied to solve the economic dispatch problem effectively with the conventional methods and modifications.

On Evolutionary and Swarm Computation for Solving the Dynamic Economic Dispatch: a Rapid Review

2020 ◽  
Author(s):  
Omar Andres Carmona Cortes ◽  
Daniel Lima Gomes Junior ◽  
Osvaldo Ronald Saavedra
Keyword(s):  
Evolutionary Algorithms ◽  
Swarm Intelligence ◽  
Optimization Problem ◽  
Economic Dispatch ◽  
Rapid Review ◽  
Transmission Losses ◽  
Valve Effect ◽  
Dynamic Economic Dispatch ◽  
Single Objective

The Dynamic Economic Dispatch problem is an essential and challenging optimization problem in the field of power dispatch. Several techniques have been investigated for its optimization, especially metaheuristics. This rapid review focuses on evolutionary and swarm computation, focusing on 22 research publications for solving the single objective DED problem. Through this review, we discuss the techniques that have been used to solve the problem and how they tackled the DED constraints. We analyze the problem's complexity, showing if the problem being solved considers the valve effect, transmission losses, ramp rates, prohibited zones, and reserve spinning requirements. Also, we investigate the number of units used in each case study. Therefore, we believe that this review is relevant for driving researchers interested in using evolutionary algorithms or swarm intelligence to tackle the DED problem in all its complexity and how the proposed algorithms deal with constraints.

Performance Analysis of TBC-ACO Routing Protocol with Existing Routing Protocols of Wireless Sensor Networks

2017 ◽  
Vol 7 (8) ◽  
pp. 169
Author(s):  
A. Radhika ◽  
D. Haritha
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Swarm Intelligence ◽  
Routing Protocol ◽  
Routing Protocols ◽  
Energy Efficient ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Congestion Aware

Wireless Sensor Networks, have witnessed significant amount of improvement in research across various areas like Routing, Security, Localization, Deployment and above all Energy Efficiency. Congestion is a problem of  importance in resource constrained Wireless Sensor Networks, especially for large networks, where the traffic loads exceed the available capacity of the resources . Sensor nodes are prone to failure and the misbehaviour of these faulty nodes creates further congestion. The resulting effect is a degradation in network performance, additional computation and increased energy consumption, which in turn decreases network lifetime. Hence, the data packet routing algorithm should consider congestion as one of the parameters, in addition to the role of the faulty nodes and not merely energy efficient protocols .Nowadays, the main central point of attraction is the concept of Swarm Intelligence based techniques integration in WSN.  Swarm Intelligence based Computational Swarm Intelligence Techniques have improvised WSN in terms of efficiency, Performance, robustness and scalability. The main objective of this research paper is to propose congestion aware , energy efficient, routing approach that utilizes Ant Colony Optimization, in which faulty nodes are isolated by means of the concept of trust further we compare the performance of various existing routing protocols like AODV, DSDV and DSR routing protocols, ACO Based Routing Protocol  with Trust Based Congestion aware ACO Based Routing in terms of End to End Delay, Packet Delivery Rate, Routing Overhead, Throughput and Energy Efficiency. Simulation based results and data analysis shows that overall TBC-ACO is 150% more efficient in terms of overall performance as compared to other existing routing protocols for Wireless Sensor Networks.

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