Modified Particle Swarm Optimization Applied to Integrated Demand Response and DG Resources Scheduling
- 11 January 2013
- journal article
- research article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Smart Grid
- Vol. 4 (1), 606-616
- https://doi.org/10.1109/tsg.2012.2235866
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.Keywords
This publication has 27 references indexed in Scilit:
- Particle swarm optimizationPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2014
- Demand response in electrical energy supply: An optimal real time pricing approachEnergy, 2011
- VPP's multi-level negotiation in smart grids and competitive electricity marketsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2011
- Particle swarm optimization with quantum infusion for system identificationEngineering Applications of Artificial Intelligence, 2010
- Guest editors' introductionEnergy, 2010
- When It Comes to Demand Response, Is FERC Its Own Worst Enemy?The Electricity Journal, 2009
- Optimal generator maintenance scheduling using a modified discrete PSOIET Generation, Transmission & Distribution, 2008
- Evolutionary Algorithms with Particle Swarm MovementsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2006
- Demand-side view of electricity marketsIEEE Transactions on Power Systems, 2003
- A robust three phase power flow algorithm for radial distribution systemsElectric Power Systems Research, 1999