Optimal Sizing of an Island Hybrid Microgrid Based on Improved Multi-Objective Grey Wolf Optimizer

The hybrid renewable energy system is a promising and significant technology for clean and sustainable island power supply. Among the abundant ocean energy sources, tidal current energy appears to be very valuable due to its excellent predictability and stability, particularly compared with the intermittent wind and solar energy. In this paper, an island hybrid energy microgrid composed of photovoltaic, wind, tidal current, battery and diesel is constructed according to the actual energy sources. A sizing optimization method based on improved multi-objective grey wolf optimizer (IMOGWO) is presented to optimize the hybrid energy system. The proposed method is applied to determine the optimal system size, which is a multi-objective problem including the minimization of annualized cost of system (CACS) and deficiency of power supply probability (DPSP). MATLAB software is utilized to program and simulate the hybrid energy system. Optimization results confirm that IMOGWO is feasible to optimally size the system, and the energy management strategy effectively matches the requirements of system operation. Furthermore, comparison of hybrid systems with and without tidal current turbines is undertaken to confirm that the utilization of tidal current turbines can contribute to enhancing system reliability and reducing system investment, especially in areas with abundant tidal energy sources.

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MULTI-OBJECTIVE OPTIMIZATION FOR OPTIMAL HYBRID RENEWABLE ENERGY SOURCE SELECTION IN HYBRID RENEWABLE ENERGY SYSTEMS

Psychology and Education Journal ◽

10.17762/pae.v58i1.1496 ◽

2021 ◽

Vol 58 (1) ◽

pp. 4283-4288

Author(s):

Shilaja C, Dr. S. Jeyanthi

Keyword(s):

Renewable Energy ◽

Evolutionary Algorithm ◽

System Optimization ◽

Energy System ◽

World Population ◽

Power Demand ◽

Hybrid Energy System ◽

Hybrid Energy ◽

Multi Objective ◽

Hybrid Renewable Energy

Power generation is more important to fulfill power demand throughout the world. Population and their electric power demand are increasing day by day. Achieve the energy demand from end-users, and recent research works have concentrated on designing a hybrid energy system. This paper proposed a multi-objective optimized model of a hybrid renewable energy system for a grid. The optimal model can choose a suitable design model of solar, wind, diesel, and batteries interconnected in the hybrid energy system. Optimization is applied for minimizing the system cost, fuel cost and diminish the fuel emission. It also aimed to improve the reliability of renewable sources. Initially, the problem is defined as a multi-objective problem and solved by a multi-objective evolutionary algorithm. From the simulation results, it is identified that the proposed multi-objective evolutionary algorithm performs better.

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Multi-Objective Sizing Optimization of Hybrid Renewable Energy Microgrid in a Stand-Alone Marine Context

Electronics ◽

10.3390/electronics10020174 ◽

2021 ◽

Vol 10 (2) ◽

pp. 174

Author(s):

Wenqiang Zhu ◽

Jiang Guo ◽

Guo Zhao

Keyword(s):

Renewable Energy ◽

Optimization Problem ◽

System Optimization ◽

Economic Benefits ◽

Grey Wolf Optimizer ◽

Grey Wolf ◽

Energy Management Strategy ◽

Sizing Optimization ◽

Multi Objective ◽

Hybrid Renewable Energy

Islands are the main platforms for exploration and utilization of marine resources. In this paper, an island hybrid renewable energy microgrid devoted to a stand-alone marine application is established. The specific microgrid is composed of wind turbines, tidal current turbines, and battery storage systems considering the climate resources and precious land resources. A multi-objective sizing optimization method is proposed comprehensively considering the economy, reliability and energy utilization indexes. Three optimization objectives are presented: minimizing the Loss of Power Supply Probability, the Cost of Energy and the Dump Energy Probability. An improved multi-objective grey wolf optimizer based on Halton sequence and social motivation strategy (HSMGWO) is proposed to solve the proposed sizing optimization problem. MATLAB software is utilized to program and simulate the optimization problem of the hybrid energy system. Optimization results confirm that the proposed method and improved algorithm are feasible to optimally size the system, and the energy management strategy effectively matches the requirements of system operation. The proposed HSMGWO shows better convergence and coverage than standard multi-objective grey wolf optimizer (MOGWO) and multi-objective particle swarm optimization (MOPSO) in solving multi-objective sizing problems. Furthermore, the annual operation of the system is simulated, the power generation and economic benefits of each component are analyzed, as well as the sensitivity.

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