Title
Modified Particle Swarm Optimization applied to integrated demand response and DG resources scheduling
Abstract
The elastic behavior of the demand consumption jointly used with other available resources such as distributed generation (DG) can play a crucial role for the success of smart grids. The intensive use of Distributed Energy Resources (DER) and the technical and contractual constraints result in large-scale non linear optimization problems that require computational intelligence methods to be solved. This paper proposes a Particle Swarm Optimization (PSO) based methodology to support the minimization of the operation costs of a virtual power player that manages the resources in a distribution network and the network itself. Resources include the DER available in the considered time period and the energy that can be bought from external energy suppliers. Network constraints are considered. The proposed approach uses Gaussian mutation of the strategic parameters and contextual self-parameterization of the maximum and minimum particle velocities. The case study considers a real 937 bus distribution network, with 20310 consumers and 548 distributed generators. The obtained solutions are compared with a deterministic approach and with PSO without mutation and Evolutionary PSO, both using self-parameterization.
Year
DOI
Venue
2013
10.1109/TDC.2014.6863207
IEEE Trans. Smart Grid
Keywords
Field
DocType
smart grids,generators,particle swarm optimization,nonlinear programming,distributed generation,power generation,deterministic approach,optimization,reactive power,gaussian processes
Particle swarm optimization,Mathematical optimization,Computational intelligence,Smart grid,Scheduling (computing),Demand response,Multi-swarm optimization,Control engineering,Distributed generation,Engineering,Deterministic system (philosophy)
Journal
Volume
Issue
Citations 
4
1
14
PageRank 
References 
Authors
0.83
12
5
Name
Order
Citations
PageRank
Pedro Faria113625.00
João P. Soares27215.09
Zita A. Vale339085.67
Hugo Morais425731.41
Tiago M. Sousa519322.35