Capacity Planning and Energy Management Strategy of Residential Multi-microgrid System Considering Uncertainty

Nurul Nadia Ibrahim, Jasrul Jamani Jamian, Madihah Md Rasid

Abstract


This study investigates the optimal capacity and performance of residential multi-microgrid systems (MMGs) integrating photovoltaic (PV), wind turbine (WT), and energy storage system (ESS) under uncertain solar irradiance and wind speed data. It utilizes an Iterative Pareto Fuzzy (IPF) technique for capacity optimization, balancing reliability, overall cost, and dump load size as objective functions, and incorporates an Energy Management Strategy (EMS) for operational efficiency. The IEEE 33-bus test system is modified into five autonomous microgrids for analysis. Optimization results reveal trade-offs between objectives: MG 3 boasts the highest reliability but incurs the highest overall cost, while MG 1 and MG 5 showcase more cost-effective designs. Robustness analysis conducted with Gaussian and Weibull noise models demonstrates the resilience of the proposed residential MMG design to data uncertainty with self-sufficiency index (SSI) exceeding 80 percent. This study provides valuable insights into designing and operating effective residential MMG for increased energy autonomy and resilience.


Keywords


Residential multi-microgrid; capacity optimization; Iterative-Pareto-Fuzzy; energy management strategy; multi-objective function

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DOI (PDF): https://doi.org/10.20508/ijrer.v16i3.15495.g9251

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