article · Sustainability
A probabilistic multiobjective optimisation framework evaluates reactive power planning strategies for islanded microgrids facing extreme contingencies. Tested on the IEEE 33-bus distribution system, the framework models uncertainties in renewable generation and demand while balancing technical reliability, economic costs, environmental sustainability, and social resilience. The findings demonstrate that reactive power configurations designed for standard grid-connected operation perform poorly during islanded emergencies. Among five evaluated support strategies, a dedicated distribution static synchronous compensator (D-STATCOM) configuration yields the highest overall performance. This approach preserves 87.2 percent of total load, safeguards 93.7 percent of critical loads, and provides an 8.7-hour survival time while eliminating severe load-shedding incidents. Furthermore, this method reduces event-related economic losses by over 75 percent and cuts life-cycle carbon dioxide emission intensity by 62.5 percent compared with conventional baselines.
Extreme weather and grid failures can cut off central power supplies, forcing local microgrids to operate independently. Ensuring these islanded systems remain stable without collapsing is critical for powering essential infrastructure such as hospitals and emergency services. This research provides a planning method that protects critical community services, cuts economic losses from outages, and lowers environmental impacts during extended emergency power disconnections.
This methodology is an applied simulation tested on a standard IEEE 33-bus benchmark network, placing it at an early stage of development prior to field trials. The planning framework could be used by distribution network operators, microgrid developers, and utility planners to design resilient infrastructure. It specifically informs capital investment decisions regarding D-STATCOM hardware deployment to prevent catastrophic outages and reduce downtime costs during islanded conditions.
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This paper presents a resilience-driven probabilistic multiobjective framework for reactive power planning in islanded microgrids under extreme contingencies, explicitly integrating sustainability objectives and alignment with the United Nations Sustainable Development Goals (SDGs). The proposed planning framework simultaneously optimizes technical reliability, economic viability, environmental sustainability, and social resilience using the IEEE 33-bus distribution system as a representative test network. Uncertainties associated with solar irradiance, wind speed, and load demand are modeled using the Two-Point Estimation Method (2PEM), while the Non-dominated Sorting Genetic Algorithm II (NSGA-II) determines Pareto optimal planning solutions for five reactive power support strategies. The results demonstrate that planning solutions optimized for grid-connected operation are not necessarily the most effective under islanded conditions. Within the adopted multi-criteria evaluation framework, the dedicated D-STATCOM strategy achieves the highest overall normalized performance, providing 87.2% load preservation, 93.7% critical-load protection, and an 8.7 h representative survival time, while reducing total load shedding to 12.8% and eliminating high-risk shedding events (>30%). Furthermore, it decreases event-related economic losses by more than 75% and achieves the lowest environmental impact, with a 62.5% reduction in life-cycle CO2 emission intensity relative to the conventional grid baseline. A normalization sensitivity analysis confirms that the comparative ranking of the investigated strategies remains unchanged under alternative normalization methods, demonstrating the robustness of the proposed evaluation framework. From a sustainability perspective, the proposed framework contributes to SDG 7 (Affordable and Clean Energy) through reliable low-carbon microgrid operation, SDG 9 (Industry, Innovation and Infrastructure) through resilient power system planning, SDG 11 (Sustainable Cities and Communities) by enhancing the continuity of critical urban services, SDG 13 (Climate Action) through reduced life-cycle emissions, and SDG 8 (Decent Work and Economic Growth) by supporting local employment associated with distributed energy deployment.
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DOI: 10.3390/su18168362
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