Abstract
The issue of optimal operation control of microgrids is a very important problem. As a result of changing weather conditions and the demand for the power of individual consumers, generation units and energy storage devices must constantly adjust their operation states. The optimization of the microgrid operation states can simultaneously provide the required level of power and energy and, for example, minimization of power losses or costs associated with the operation of this type of system. Among many available optimization methods, author of a paper decided to test the CLONALG algorithm, which is an implementation of artificial immune system. The article will presents the characteristics of selected CLONALG algorithm, and the description of the test microgrid together with the considered optimization criteria and constraints. The presentation and analysis of the obtained results from optimization calculations will be the main part of the paper. At the end of the paper observations and conclusion will be presented.
Highlights
The growing demand for electricity causes that an increasing number of consumers are considering installation of local distributed energy sources and storage units
As a conclusion the clonal selection algorithm (CLONALG) algorithm was used in three tasks of optimization of operation points in hybrid AC/DC test microgrid
The results shows that the algorithm strives to find the smallest value of the objective functions for different initial conditions
Summary
The growing demand for electricity causes that an increasing number of consumers are considering installation of local distributed energy sources and storage units. Most of installed microsources as well as energy storage units require the use of bidirectional electronic power converters ( multistage converters) to connect them to the AC power grid. Deprived of these drawbacks is the concept of hybrid AC/DC microgrid, presented in [2]. Some exemplary applications and power management strategies of hybrid microgrids are presented in [6]
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