Reserve Constrained Dynamic Environmental/Economic Dispatch: A New Multiobjective Self-Adaptive Learning Bat Algorithm
- 16 April 2013
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Systems Journal
- Vol. 7 (4), 763-776
- https://doi.org/10.1109/jsyst.2012.2225732
Abstract
This paper proposes a new multiobjective self-adaptive learning bat-inspired algorithm to solve practical reserve constrained dynamic environmental/economic dispatch that considers realistic constraints such as valve-point effects, transmission losses, and ramp rate limits over a short-term time period. Furthermore, to ensure secure real-time power system operations, the system operator must schedule sufficient resources to meet energy demand and operating reserve requirements simultaneously. The proposed problem is a complex nonlinear nonsmooth and nonconvex multiobjective optimization problem whose complexity is increased when considering the above constraints. To this end, this paper utilizes a newly developed meta-heuristic bat inspired algorithm to achieve the set of nondominated (Pareto-optimal) solutions. This algorithm is equipped with a novel self-adaptive learning to increase the population diversity and amend the convergence criteria. The initial population of the proposed framework is generated by a chaos-based strategy. In addition, a tournament crowded selection approach is implemented to choose the population such that the Pareto-optimal front is distributed uniformly, while the extreme points of the tradeoff surface are achieved simultaneously. Numerical results evaluate the performances of the framework for real-size test systems.Keywords
This publication has 36 references indexed in Scilit:
- Dynamic economic emission dispatch based on group search optimizer with multiple producersElectric Power Systems Research, 2012
- $\theta$-Multiobjective Teaching–Learning-Based Optimization for Dynamic Economic Emission DispatchIEEE Systems Journal, 2012
- Bat-Inspired Optimization Approach for the Brushless DC Wheel Motor ProblemIEEE Transactions on Magnetics, 2012
- Optimal Electric Network Design for a Large Offshore Wind Farm Based on a Modified Genetic Algorithm ApproachIEEE Systems Journal, 2011
- Adaptive particle swarm optimization approach for static and dynamic economic load dispatchEnergy Conversion and Management, 2008
- Pareto-Based Multiobjective Machine Learning: An Overview and Case StudiesIEEE Transactions on Systems, Man and Cybernetics, Part C (Applications and Reviews), 2008
- Multiobjective Particle Swarm Algorithm With Fuzzy Clustering for Electrical Power DispatchIEEE Transactions on Evolutionary Computation, 2008
- Simulated Annealing Technique for Dynamic Economic DispatchElectric Power Components and Systems, 2006
- Handling multiple objectives with particle swarm optimizationIEEE Transactions on Evolutionary Computation, 2004
- Chaotic sequences to improve the performance of evolutionary algorithmsIEEE Transactions on Evolutionary Computation, 2003