Modeling and managing of micro grid connected system using Improved Artificial Bee Colony algorithm

• We determine the microgrid combinations with reduced cost by using IABC technique.
• We enhance the scout bee phase of the ABC algorithm by using the GSA technique.
• We examine the optimal combination of the microgrids for various load demands.
• We analyze the cost factors of the microgrid combinations with various techniques.

This paper introduces an Improved Artificial Bee Colony algorithm for modeling and managing Micro Grid (MG) connected system. IABC differs from ABC because of its inclusion of Gravitational search algorithm (GSA) in the scout bee phase. Hence, the scout bee phase is substantially improved as the gravitational constant of GSA increases searching accuracy. As already ABC works with memory, IABC tackles drawbacks occur due to memory-less search entertained by GSA. In the proposed technique, optimal MG’s configuration is determined based on load demand by reducing the fuel cost, emission factors, operating and maintenance cost. By using the input of MG’s configuration such as Wind Turbine (WT), Photovoltaic array (PV), Fuel Cell (FC), Micro Turbine (MT), Diesel Generator (DG) and battery storage and the corresponding cost functions, the proposed method achieves the required multi-objective function. The performance of the proposed method is examined by comparing with other techniques that are recently reported in the literature. The comparison results demonstrate the superiority of the proposed technique and confirm its potential to solve the problem.