Analysis of optimal scheduling and energy-saving measures for shipyard microgrid based on IMOPSO algorithm
DOI:
https://doi.org/10.4108/ew.13144Keywords:
Microgrid Optimization, MOPSO Algorithm, Shipyard Energy Consumption, Energy-saving Measures, Multi-objective Trade-offsAbstract
INTRODUCTION: This research study presents the development of a microgrid system specifically designed for a shipyard environment based on the energy consumption characteristics of major shipyard equipment.
OBJECTIVES: The algorithm simultaneously optimizes three different objectives as follows: (1) economic cost; (2) carbon emission; and (3) power fluctuation (stability).
METHODS: To accomplish the objective of creating an optimal microgrid configuration, the IMOPSO was used to solve the microgrid model.
RESULTS: Results indicate that there are considerable trade-offs between economic cost versus carbon emission and between economic cost versus power fluctuation, which require optimally balanced approaches in order to meet all the different objectives. Among various energy-saving measures, the adoption of the dehumidification system with heat recovery wheel proves especially effective in reducing power consumption, economic cost and carbon emission.
CONCLUSION: Pareto front analysis reveals that the weak emission-fluctuation conflict creates an opportunity to effectively balance the critical cost-emission trade-off for obtaining superior solutions. Equipment energy-saving measures, particularly the dehumidification with heat recovery and hybrid welding, significantly improve the microgrid's economic and environmental performance.
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