Transactions on Machine Intelligence

Transactions on Machine Intelligence

Economic Load Spreading by Considering the Presence of Electric Vehicles in Order to Reduce Pollution Particles and To Consider Demand Response

Document Type : Original Article

Authors
F. Badakhshani 1
N. Goudarzi 2
1 Master's student, Electrical Department, Abadeh Branch, Islamic Azad University, Abadeh, Iran
2 Assistant Professor, Department of Nuclear Engineering, Abadeh Branch, Islamic Azad University, Abadeh, Iran
10.47176/TMI.2023.248
Abstract
The development of power networks has expanded the production and consumption of electrical energy into highly competitive areas, including the use of renewable energy.  Solar energy, for example, not only reduces fuel consumption but also lowers the long-term cost of electricity production by requiring only initial capital investment. This research focuses on economic dispatching in the network. The aim of this research is to decrease environmental pollution and energy production costs. The subject being investigated exhibits non-linear properties in many areas, and cannot be viewed as a linear problem. Various tools are utilized in this research to achieve the main objective. One tool utilized in this research is the use of solar production sources and energy storage elements to shift part of the load during peak hours to low-load hours. Electric cars are used as an example. The particle swarm algorithm is employed to optimize the presence hours of electric vehicles and the amount that each power plant unit should produce. However, this research has implemented restrictions for the optimal use of these units. These restrictions will be explained in detail below.
Keywords
Economic Load Spreading
Electric Vehicle
Particle Swarm Algorithm (PSO)
Pollution Reduction
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Transactions on Machine Intelligence
Volume 6, Issue 4
Autumn 2023
Pages 248-265

  • Receive Date 10 May 2023
  • Revise Date 14 November 2023
  • Accept Date 14 December 2023