Discover how modern techniques have shaped complex power system expansion planning with this one-stop resource from two experts in the field

Probabilistic Power System Expansion Planning with Renewable Energy Resources and Energy Storage Systems delivers a comprehensive collection of innovative approaches to the probabilistic planning of generation and transmission systems under uncertainties. The book includes renewables and energy storage calculations when using probabilistic and deterministic reliability techniques to assess system performance from a long-term expansion planning viewpoint.

Divided into two sections, the book first covers topics related to Generation Expansion Planning, with chapters on cost assessment, methodology and optimization, and more. The second and final section provides information on Transmission System Expansion Planning, with chapters on reliability constraints, probabilistic production cost simulation, and more.

Probabilistic Power System Expansion Planning compares the optimization and methodology across dynamic, linear, and integer programming and explores the branch and bound algorithm. Along with case studies to demonstrate how the techniques described within have been applied in complex power system expansion planning problems, readers will enjoy:

• A thorough discussion of generation expansion planning, including cost assessment, methodology and optimization, and probabilistic production cost
• An exploration of transmission system expansion planning, including the branch and bound algorithm, probabilistic production cost simulation for TEP, and TEP with reliability constraints
• An examination of fuzzy decision making applied to transmission system expansion planning
• A treatment of probabilistic reliability-based grid expansion planning of power systems including wind turbine generators

Perfect for power and energy systems designers, planners, operators, consultants, practicing engineers, software developers, and researchers, Probabilistic Power System Expansion Planning with Renewable Energy Resources and Energy Storage Systems will also earn a place in the libraries of practicing engineers who regularly deal with optimization problems.