Özet:
Regardless of energy type that we need today, it is important to use it efficiently and
economically in the production, transmission and distribution stages. In line with the
developing technology and needs, a new energy concept has emerged in which different energy
types managed together in the past were managed independently. In this concept, energy
infrastructures of more than one energy carrier such as electricity, gas and heat are met as
Energy Hub (EH) to supply the demands such as electricity, gas, heating, cooling and
compressed air by means of energy conversion, distribution and storage devices. EHs are
expected to meet the demands energy with low operating costs. Energy hub economic dispatch
problem (EHEDP) is a non-linear, non-convex, uniform and non-differential multidimensional
optimization problem. In this study, the energy cost of the system is minimized by using the
Coyote Optimization Algorithm (COA) for the solution of the EHEDP. The results obtained with
COA have been compared with the results of heuristic algorithms such as Genetic Algorithm
(GA), Particle Swarm Optimization (PSO), Moth Swarm Algorithm (MSA) and Symbiotic
Organisms Search Algorithm (SOS) in the literature. The compared results showed that COA
performed better than other algorithms in solving EHED problem.