The "solution" to a reliability problem, therefore, is not a single number but a that quantify the frequency, duration, and magnitude of failures. Billinton famously argued that a deterministic "margin" (e.g., 15% spare capacity) is a poor solution because it ignores the stochastic nature of component failure and load variation.
This comprehensive toolkit of techniques (from probability distributions to Markov processes) has been applied in a wide range of real-world problems, underpinning everything from power grid planning to the evaluation of systems with renewable energy.
These CSR tools, many of which build on Billinton's initial concepts, are now essential for planning and operating reliable and economically efficient power systems. The "solution" to a reliability problem, therefore, is
Billinton and Allan dedicated entire chapters of their book to the "solution techniques." There is no single algorithm; rather, a toolbox.
If you want, I can produce a sample reliability study outline, a short literature summary with publication years, or a worked example computing EENS for a small system. These CSR tools, many of which build on
The book's structure provides a logical and progressive path to mastering reliability evaluation. The key chapters build upon one another to form a complete "solution strategy":
[ Engineering System Design ] | +---------------+---------------+ | | [ Deterministic Rules ] [ Probabilistic Methods ] - Worst-case focus - Quantifiable risk - Binary (safe/unsafe) - Statistical profiles - Often over-engineered - Optimized economics The book's structure provides a logical and progressive
– Billinton’s favorite for power systems