Book

As the world races toward a renewable-energy-dominant grid to meet net-zero targets, a hidden cost emerges: declining system inertia, and with it, growing frequency instability. This book tackles that challenge head-on. Drawing on doctoral research in electrical engineering, Frequency Instability in Renewable Power Systems develops a series of multi-objective optimisation models — built as mixed-integer quadratic constrained programming (MIQCP) problems and solved using CPLEX in GAMS — that balance system inertia, cost, and CO2 emissions in modern power grids. The models are progressively extended: from core inertia-aware planning, to joint generation-transmission expansion planning with emission-reduction incentives, to feed-in tariff sensitivity analysis, and finally to a scenario-based treatment of renewable energy uncertainty using real wind and solar data from South Africa's Free State province. The results are striking: up to a 24% increase in system inertia, a 9.62% reduction in CO2 emissions, and measurable cost savings when inertia and renewable variability are properly accounted for in planning — offering a practical, data-driven path for power system planners and researchers navigating the transition to a low-carbon grid. This book is essential reading for power system engineers, energy policy researchers, and postgraduate students working at the intersection of renewable energy integration, grid stability, and optimisation modelling.