Multiverse optimisation based technique for solving economic dispatch in power system

Abstract

Economic dispatch (ED) is one of the many important components in a power system operation. It is designed to calculate the exact amount of power generation needed to ensure a minimum cost of generation. A power system with multiple generators should be running under an economic condition. The operating cost has to be minimised for any feasible load demand. The increase of power demand is getting higher throughout the year. Economic dispatch is used to schedule and control all output of the fossil-fuel or coal-generators to satisfy the system load demand at a minimum cost. This paper presents the Multiverse Optimisation (MVO) for solving the economic dispatch in a power system. The proposed Multiverse optimisation engine developed in this study is implemented on the IEEE 30-Bus Reliability Test System (RTS). It has five generators, all of which are denoted as the control variables for the optimisation process. To reveal the superiority of MVO, a similar process was conducted using Evolutionary Programming (EP). Results from both techniques were compared, and it was revealed that MVO had outperformed EP in terms of reduced cost of generation for the system.

Evolutionary algorithm solution for economic dispatch problems

“…Typically, ED is considered an  ISSN: 2088-8708 important area of the control and operation of power systems as its main objective of the ED plant is to schedule the operations of the generating units to ensure maximum performance at the minimum operation cost; this amounts to low-cost electricity on the side of the customers and possible gain on the side of the service provider in the electricity market. Being that the generated power by the generating units cannot be stored as other types of products, coupled with the need for transmission and distribution networks to get the generated power to the consumers, it is becoming difficult to accurately determine the cost of electric power generation and services [3], [4]. The study by Touma [5] proposed the whale optimization approach of finding a solution to the ED problem.…”