The 1966–1972 period marks the emergence of mathematics-based optimization as the backbone of power-system analysis. Foundational methods introduced automatic adjustment of control variables to minimize costs or losses under physical constraints, using Newton-based iteration to solve nonlinear power-flow problems and enforce limits. At the same time, the static-state concept crystallized as the primary descriptor of system status, enabling exact estimation from diverse meter readings and underpinning real-time monitoring and reliability assessments. Linear programming began to inform transmission-network design and reinforcement strategies, guiding capacity expansion with near-minimal circuit miles. Finally, analytic techniques for dynamic modeling—such as modal analysis for electromechanical equivalents—started to yield scalable representations for stability calculations, bridging generator dynamics with network response. Historical Significance: These breakthroughs planted enduring seeds for future evolution of power-system optimization and diagnostics. The Optimal Power Flow concept provided a rigorous framework for combining cost, losses, and constraints in operation and planning. Static-State Estimation established the feasibility and value of real-time state tracking from noisy measurements, catalyzing reliability analysis and control. Linear programming-based transmission planning introduced a quantitative basis for expansion decisions, while electromechanical dynamic equivalents enabled scalable, accurate simulations of system stability. Collectively, these developments unified planning and operation through mathematical modeling and set the stage for the modern, optimization-driven discipline of power systems.