Single and multi-objective operation management of micro-grid using krill herd optimization and ant lion optimizer algorithms

Abstract

In this paper, two recent heuristic optimization algorithms are presented to optimally manage the operation of the microgrid (MG) with installed renewable energy sources (RESs); krill herd (KH) optimization and ant lion optimizer (ALO) algorithms. The first algorithm is used for solving single-objective function represents either total operation cost or total pollutant emission injected from the installed generating units while ALO is applied to solve the multi-objective function of both total operating cost and emission. The problem is formulated as nonlinear constrained objective function with equality and inequality constraints. In this work; the devices installed in MGs are photovoltaic panel (PV), wind turbine (WT), microturbine (MT), fuel cell (FC), battery and grid. Two scenarios are studied; the first one is optimizing MG with installing all RESs within specified limits in addition to grid, while the second scenario is operating both PV and WT at their rated powers. The obtained results are compared with different reported algorithms like genetic algorithm (GA), Fuzzy self-adaptive PSO (FSAPSO) and others programmed like particle swarm optimization (PSO), grey-wolf optimizer (GWO) and whale optimization algorithm (WOA). For first scenario; the proposed KH gives the best optimal cost of 105.94 €ct while the best emission is 420.57 kg, the best optimal cost and emission of 592.86 €ct 339.71 kg are obtained via KH in the second scenario.

Ant Lion Optimization: Variants, Hybrids, and Applications

“…Fathy and Abdelaziz [180] used Krill Herd (KH) and ALO to mange both Single & Multi-Objective operation management. They formulated the problem as nonlinear constrained function.…”

Robust Energy Management and Economic Analysis of Microgrids Considering Different Battery Characteristics

“…Ruiz-Cortés et al [25] developed a genetic algorithm-based approach to determine the optimal charge/discharge daily scheduling of batteries in gridconnected MG taking into account energy exchange loss minimization. Fathy and Abdelaziz [26] presented both single and multi-objective design algorithms to manage the operation of an MG. The single objective function aimed to minimize the total operating cost and emissions from the MG individually using krill herd (KHS) optimization.…”

“…Also, the amount of charged power with the efficiency (η bat ) of the battery considered should be equal to the amount of the discharged power as represented by (25). The state of charge of the battery (SOC t ) is based on the previous state of charge of the battery (SOC t−1 ) and the discharge and charge quantity at time t as given in (26). It should be noted that, in the first period (t = 1), the initial SOC (SOC 0 ) needs to be considered.…”

Combining routing and virtual machine selection algorithm based on multi‐hop cloud wireless access network of mobile edge computing

“…Gandomi and Alavi proposed the KH algorithm in 2012 by studying the activity of krill group [25, 26]. The algorithm uses the position status of krill to represent the solution of the optimisation problem and finds the optimal solution continuously by simulating the change of individual position during the foraging process of krill.…”