Generation and demand management via Particle Swarm Optimization

This paper presents an implementation of the economic dispatch problem with demand participation representation using the Particle Swarm Optimization (PSO) technique. The problem is formulated in the context of a small grid, whose manager dispatches generation and flexible demand along a time horizon in order to minimize generation costs. Power flow equality constraints and inequality constraints due to operational limits are modeled. Equality constraints are handled by penalty functions and by an enforcement mechanism. Two applications, one using the IEEE 30-bus test system, illustrate the applicability of the optimization technique. The results obtained show that the proposed PSO can provide good dispatch results.

[1]  Jeong Yun Won,et al.  AN IMPROVED PARTICLE SWARM OPTIMIZATION FOR ECONOMIC DISPATCH WITH VALVE-POINT EFFECT , 2006 .

[2]  Carlos A. Coello Coello,et al.  A constraint-handling mechanism for particle swarm optimization , 2004, Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753).

[3]  Patrick D. McDaniel,et al.  Security and Privacy Challenges in the Smart Grid , 2009, IEEE Security & Privacy.

[4]  T. Jayabarathi,et al.  Particle swarm optimization for various types of economic dispatch problems , 2006 .

[5]  D.A. Cohen.  GridAgents™: Intelligent agent applications for integration of distributed energy resources within distribution systems , 2008, 2008 IEEE Power and Energy Society General Meeting - Conversion and Delivery of Electrical Energy in the 21st Century.

[6]  Joong-Rin Shin,et al.  A particle swarm optimization for economic dispatch with nonsmooth cost functions , 2005, IEEE Transactions on Power Systems.

[7]  M. McGranaghan,et al.  Functions of a local controller to coordinate distributed resources in a smart grid , 2008, 2008 IEEE Power and Energy Society General Meeting - Conversion and Delivery of Electrical Energy in the 21st Century.

[8]  Salman Mohagheghi,et al.  Particle Swarm Optimization: Basic Concepts, Variants and Applications in Power Systems , 2008, IEEE Transactions on Evolutionary Computation.

[9]  Mohamed E. El-Hawary,et al.  Emission-Economic Dispatch using a Novel Constraint Handling Particle Swarm Optimization Strategy , 2006, 2006 Canadian Conference on Electrical and Computer Engineering.

[10]  Thomas Werner,et al.  The distribution control centre in a SmartGrid , 2009 .

[11]  Cameron W. Potter,et al.  Building a smarter smart grid through better renewable energy information , 2009, 2009 IEEE/PES Power Systems Conference and Exposition.

[12]  S. Khamsawang,et al.  Solving the Economic Dispatch Problem using Novel Particle Swarm Optimization , 2009 .

[13]  J. R. Roncero.  Integration is key to Smart Grid management , 2008 .

[14]  Wadaed Uturbey,et al.  Optimal power flow with inter-temporal constraints as an aiding tool for demand-side management , 2002 .

[15]  Mohammed H. Albadi,et al.  A summary of demand response in electricity markets , 2008 .

[16]  Hassan Nouri,et al.  Economic dispatch of power system using particle swarm optimization with constriction factor , 2009 .