Response-function framework for evaluating converter topologies in renewable energy integration

Converter-dominated power systems play a key role in renewable energy integration, yet selecting suitable converter topologies under complex operating and fault conditions remains challenging. This brief study introduces a multi-criteria response modeling framework for evaluating modular multilevel converter (MMC) topologies. The method models nonlinear relationships between engineering indicators—voltage difference, reliability, compactness, cost, and control complexity—and topology adaptability using linear, saturating, and bell-shaped response functions. A hybrid weighting mechanism combining analytic hierarchy process and entropy theory balances expert judgment with data variability. Case studies across distributed renewable access, rail traction, and inter-city HVDC systems verify the framework’s capability to capture topology–scenario matching. Results indicate that half-bridge MMCs excel in compact low-cost applications, symmetric hybrids perform best in high-reliability scenarios, and asymmetric hybrids show advantages under high-voltage interconnection requiring fault ride-through. The proposed method provides a concise, data-driven decision tool for renewable-dominated converter selection, supporting future HVDC planning and flexible grid development.