Adjustment of the Fuzzy Logic controller parameters of the energy management strategy of a grid-tied domestic electro-thermal microgrid using the Cuckoo search algorithm

Abstract

During the last century, population growth, together with economic development, has considerably increased the energy demand and, although renewable energies are becoming an alternative, still total energy supply is mainly non-renewable, causing well-known negative effects such as pollution and global warming. On the other hand, technological advances have allowed the development of increasingly efficient distributed generation systems and the emergence of microgrids, whose studies have been focused on architecture, elements, and objectives of the associated energy management strategies. In this regard, energy management strategies based on a Fuzzy Logic controller have been developed for electro-thermal microgrids where parameter optimization has been carried out through heuristic procedures of trial and error with acceptable results but involving a high computational cost. To solve the aforementioned drawbacks, in the present work the use of Cuckoo Search optimization nature-inspired algorithm that allows the adjustment of Fuzzy Logic controller parameters and ensures a higher quality of energy management is proposed. Obtained results show encouraging outcomes for the use of these meta-heuristic optimization algorithms.

Performance analysis of optimized controllers with bio-inspired algorithms

“…These insects base their behavior on mutual collaboration to carry out multiple tasks that would be impossible to perform from an individual ant. A very important skill that many species of ants have lies in the expertise of finding the shortest route between their anthill and the nearest food source [3][4][5][6][7].…”

Experts versus Algorithms? Optimized Fuzzy Logic Energy Management of Autonomous PV Hybrid Systems with Battery and H2 Storage

“…These include off-grid PV battery diesel [16][17][18][19][20] or fuel cell systems [21], and battery fuel cell hybrid energy storage systems in electric vehicles [4,5,22]. Moreover, in [23,24] batteries are used to smoothen grid power injection with the help of a fuzzy logic controller. In this case, the grid can be considered a long-term storage system with infinite capacity.…”

“…Hence, it is not surprising that the tuning of rules and membership functions has been combined with several different, mostly heuristic, optimization methods, such as genetic algorithms, particle swarm algorithms, cuckoo search algorithms etc. [5,15,[19][20][21]23,24,29]. In these cases, though, the interpretability of the resulting fuzzy logic controller is lost.…”