Journal
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
Volume 47, Issue -, Pages 351-367Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.ijepes.2012.10.069
Keywords
Dynamic economic emission dispatch; Fuzzy set; Particle swarm optimization; Self-adaptive probabilistic mutation strategy; Uncertainty; Wind turbine
Categories
Funding
- Ministry of Science of Spain under CICYT [ENE2012-30679]
Ask authors/readers for more resources
This study protracts the multi-objective dynamic economic emission dispatch (DEED) problem by integrating wind power output of wind turbines. DEED simultaneously minimizes total electrical energy costs and emissions over a 24-h time span. In order to model the random nature of load demand and wind forecast errors, a scenario-based stochastic programming framework is presented. A scenario set is generated by a roulette wheel mechanism based on the probability distribution functions of these input uncertain variables. Therewith, the stochastic DEED (SDEED) problem is transformed into an equivalent deterministic scenario-based DEED. Thus, to solve the complicated nonlinear, non-smooth, and non-differentiable SDEED, an enhanced particle swarm optimization (PSO) algorithm is applied to obtain the best solution for the corresponding scenarios. In order to improve the quality of the solutions attained by PSO a self-adaptive probabilistic mutation strategy is used to escape from local minima. The proposed framework is successfully applied to four test systems with small, medium, and large-scale characteristics. In this regard, some metrics are used in order to characterize the effective performance of the solution method. (C) 2012 Elsevier Ltd. All rights reserved.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available