Paper Info
Title
Reserve Constrained Dynamic Environmental/Economic Dispatch: A New Multiobjective Self-Adaptive Learning Bat Algorithm
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.
Year
DOI
Venue
2013
10.1109/JSYST.2012.2225732
Systems Journal, IEEE
Keywords
DocType
Volume
Pareto optimisation,concave programming,environmental factors,learning (artificial intelligence),power engineering computing,power generation dispatch,Pareto optimal solution,complex nonlinear multiobjective optimization,multiobjective self-adaptive learning bat algorithm,nonconvex multiobjective optimization metaheuristic bat inspired algorithm,nondominated solution,nonsmooth multiobjective optimization,ramp rate limits,real time power system operation,reserve constrained dynamic economic dispatch,reserve constrained dynamic environmental dispatch,transmission loss,valve point effect,Bat-inspired algorithm,reserve constrained dynamic environmental/economic dispatch,self-adaptive learning,spinning reserve constraint,valve-point effects
Journal
7
Issue
ISSN
Citations 
4
1932-8184
15
PageRank 
References 
Authors
1.02
11
4
Name
Order
Citations
PageRank
Taher Niknam1201.81
Rasoul Azizipanah-Abarghooee2151.02
Mohsen Zare3151.02
Bahman Bahmani Firouzi4151.36