A multi-objective multi-verse optimization algorithm for dynamic load dispatch problems

• Published in: Knowledge-based systems Vol. 231; p. 107411
• Main Authors: Acharya, Srinivasa, Ganesan, S., Kumar, D. Vijaya, Subramanian, S.
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 14.11.2021; Elsevier Science Ltd
• Subjects: Algorithms; Cost function; DELD problems; Dynamic loads; Economics; Emission; Emission cost; Energy sources; Fuel cost; Load distribution (forces); Multiple objective analysis; MVO algorithm; Optimization; Power dispatch; Robustness (mathematics); Thermal and solar power generation system; DELD problems; Emission cost; Fuel cost; Thermal and solar power generation system; MVO algorithm
• ISSN: 0950-7051; 1872-7409
• DOI: 10.1016/j.knosys.2021.107411

In power system operation, optimal economic dispatch is imposed by the costs of increasing power generation, the increasing demand for electrical energy and the scarcity of energy resources. By satisfying all constraints, the most important thing is the economical load distribution in order to enable the generators used in the system to generate optimal power. The non-smooth cost function and emission with nonlinear constraints are the practical economic load dispatch issues that create a challenge that is effectively reduced. This paper presents a multi-objective multi-verse optimization scheme to minimize the dynamic economic load dispatch issue using valve-point effects. Along with all other necessary constraints, this algorithm preserves the ramp of unit required rate constraint. However, it maintains these limitations via the transaction duration to the next time horizon to eliminate the power system operation’s discontinuity, not only for its time horizon. The objective of this method is by satisfying various operational constraints and the power generator has the load requirement along with the minimization of cost. The proposed algorithm is tested on two test systems by varying the generating units as 40, 80, and 160. Simulation results are performed under the MATLAB environment and, the acquired results are compared with many existing algorithms in terms of fuel cost, emission cost, and robustness. The proposed scheme is very encouraging and proves the effectiveness of solving various dynamic economical load dispatch problems depending on the numerical outcomes.